Tag Archives: voting

New – AWS SAM Local (Beta) – Build and Test Serverless Applications Locally

Post Syndicated from Randall Hunt original https://aws.amazon.com/blogs/aws/new-aws-sam-local-beta-build-and-test-serverless-applications-locally/

Today we’re releasing a beta of a new tool, SAM Local, that makes it easy to build and test your serverless applications locally. In this post we’ll use SAM local to build, debug, and deploy a quick application that allows us to vote on tabs or spaces by curling an endpoint. AWS introduced Serverless Application Model (SAM) last year to make it easier for developers to deploy serverless applications. If you’re not already familiar with SAM my colleague Orr wrote a great post on how to use SAM that you can read in about 5 minutes. At it’s core, SAM is a powerful open source specification built on AWS CloudFormation that makes it easy to keep your serverless infrastructure as code – and they have the cutest mascot.

SAM Local takes all the good parts of SAM and brings them to your local machine.

There are a couple of ways to install SAM Local but the easiest is through NPM. A quick npm install -g aws-sam-local should get us going but if you want the latest version you can always install straight from the source: go get github.com/awslabs/aws-sam-local (this will create a binary named aws-sam-local, not sam).

I like to vote on things so let’s write a quick SAM application to vote on Spaces versus Tabs. We’ll use a very simple, but powerful, architecture of API Gateway fronting a Lambda function and we’ll store our results in DynamoDB. In the end a user should be able to curl our API curl https://SOMEURL/ -d '{"vote": "spaces"}' and get back the number of votes.

Let’s start by writing a simple SAM template.yaml:

AWSTemplateFormatVersion : '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Resources:
  VotesTable:
    Type: "AWS::Serverless::SimpleTable"
  VoteSpacesTabs:
    Type: "AWS::Serverless::Function"
    Properties:
      Runtime: python3.6
      Handler: lambda_function.lambda_handler
      Policies: AmazonDynamoDBFullAccess
      Environment:
        Variables:
          TABLE_NAME: !Ref VotesTable
      Events:
        Vote:
          Type: Api
          Properties:
            Path: /
            Method: post

So we create a [dynamo_i] table that we expose to our Lambda function through an environment variable called TABLE_NAME.

To test that this template is valid I’ll go ahead and call sam validate to make sure I haven’t fat-fingered anything. It returns Valid! so let’s go ahead and get to work on our Lambda function.

import os
import os
import json
import boto3
votes_table = boto3.resource('dynamodb').Table(os.getenv('TABLE_NAME'))

def lambda_handler(event, context):
    print(event)
    if event['httpMethod'] == 'GET':
        resp = votes_table.scan()
        return {'body': json.dumps({item['id']: int(item['votes']) for item in resp['Items']})}
    elif event['httpMethod'] == 'POST':
        try:
            body = json.loads(event['body'])
        except:
            return {'statusCode': 400, 'body': 'malformed json input'}
        if 'vote' not in body:
            return {'statusCode': 400, 'body': 'missing vote in request body'}
        if body['vote'] not in ['spaces', 'tabs']:
            return {'statusCode': 400, 'body': 'vote value must be "spaces" or "tabs"'}

        resp = votes_table.update_item(
            Key={'id': body['vote']},
            UpdateExpression='ADD votes :incr',
            ExpressionAttributeValues={':incr': 1},
            ReturnValues='ALL_NEW'
        )
        return {'body': "{} now has {} votes".format(body['vote'], resp['Attributes']['votes'])}

So let’s test this locally. I’ll need to create a real DynamoDB database to talk to and I’ll need to provide the name of that database through the enviornment variable TABLE_NAME. I could do that with an env.json file or I can just pass it on the command line. First, I can call:
$ echo '{"httpMethod": "POST", "body": "{\"vote\": \"spaces\"}"}' |\
TABLE_NAME="vote-spaces-tabs" sam local invoke "VoteSpacesTabs"

to test the Lambda – it returns the number of votes for spaces so theoritically everything is working. Typing all of that out is a pain so I could generate a sample event with sam local generate-event api and pass that in to the local invocation. Far easier than all of that is just running our API locally. Let’s do that: sam local start-api. Now I can curl my local endpoints to test everything out.
I’ll run the command: $ curl -d '{"vote": "tabs"}' http://127.0.0.1:3000/ and it returns: “tabs now has 12 votes”. Now, of course I did not write this function perfectly on my first try. I edited and saved several times. One of the benefits of hot-reloading is that as I change the function I don’t have to do any additional work to test the new function. This makes iterative development vastly easier.

Let’s say we don’t want to deal with accessing a real DynamoDB database over the network though. What are our options? Well we can download DynamoDB Local and launch it with java -Djava.library.path=./DynamoDBLocal_lib -jar DynamoDBLocal.jar -sharedDb. Then we can have our Lambda function use the AWS_SAM_LOCAL environment variable to make some decisions about how to behave. Let’s modify our function a bit:

import os
import json
import boto3
if os.getenv("AWS_SAM_LOCAL"):
    votes_table = boto3.resource(
        'dynamodb',
        endpoint_url="http://docker.for.mac.localhost:8000/"
    ).Table("spaces-tabs-votes")
else:
    votes_table = boto3.resource('dynamodb').Table(os.getenv('TABLE_NAME'))

Now we’re using a local endpoint to connect to our local database which makes working without wifi a little easier.

SAM local even supports interactive debugging! In Java and Node.js I can just pass the -d flag and a port to immediately enable the debugger. For Python I could use a library like import epdb; epdb.serve() and connect that way. Then we can call sam local invoke -d 8080 "VoteSpacesTabs" and our function will pause execution waiting for you to step through with the debugger.

Alright, I think we’ve got everything working so let’s deploy this!

First I’ll call the sam package command which is just an alias for aws cloudformation package and then I’ll use the result of that command to sam deploy.

$ sam package --template-file template.yaml --s3-bucket MYAWESOMEBUCKET --output-template-file package.yaml
Uploading to 144e47a4a08f8338faae894afe7563c3  90570 / 90570.0  (100.00%)
Successfully packaged artifacts and wrote output template to file package.yaml.
Execute the following command to deploy the packaged template
aws cloudformation deploy --template-file package.yaml --stack-name 
$ sam deploy --template-file package.yaml --stack-name VoteForSpaces --capabilities CAPABILITY_IAM
Waiting for changeset to be created..
Waiting for stack create/update to complete
Successfully created/updated stack - VoteForSpaces

Which brings us to our API:
.

I’m going to hop over into the production stage and add some rate limiting in case you guys start voting a lot – but otherwise we’ve taken our local work and deployed it to the cloud without much effort at all. I always enjoy it when things work on the first deploy!

You can vote now and watch the results live! http://spaces-or-tabs.s3-website-us-east-1.amazonaws.com/

We hope that SAM Local makes it easier for you to test, debug, and deploy your serverless apps. We have a CONTRIBUTING.md guide and we welcome pull requests. Please tweet at us to let us know what cool things you build. You can see our What’s New post here and the documentation is live here.

Randall

New – Amazon Connect and Amazon Lex Integration

Post Syndicated from Randall Hunt original https://aws.amazon.com/blogs/aws/new-amazon-connect-and-amazon-lex-integration/

I’m really excited to share some recent enhancements to two of my favorite services: Amazon Connect and Amazon Lex. Amazon Connect is a self-service, cloud-based contact center service that makes it easy for any business to deliver better customer service at lower cost. Amazon Lex is a service for building conversational interfaces using voice and text. By integrating these two services you can take advantage of Lex‘s automatic speech recognition (ASR) and natural language processing/understading (NLU) capabilities to create great self-service experiences for your customers. To enable this integration the Lex team added support for 8kHz speech input – more on that later. Why should you care about this? Well, if the a bot can solve the majority of your customer’s requests your customers spend less time waiting on hold and more time using your products.

If you need some more background on Amazon Connect or Lex I strongly recommend Jeff’s previous posts[1][2] on these services – especially if you like LEGOs.


Let’s dive in and learn to use this new integration. We’ll take an application that we built on our Twitch channel and modify it for this blog. At the application’s core a user calls an Amazon Connect number which connects them to an Lex bot which invokes an AWS Lambda function based on an intent from Lex. So what does our little application do?

I want to finally settle the question of what the best code editor is: I like vim, it’s a spectacular editor that does one job exceptionally well – editing code (it’s the best). My colleague Jeff likes emacs, a great operating system editor… if you were born with extra joints in your fingers. My colleague Tara loves Visual Studio and sublime. Rather than fighting over what the best editor is I thought we might let you, dear reader, vote. Don’t worry you can even vote for butterflies.

Interested in voting? Call +1 614-569-4019 and tell us which editor you’re voting for! We don’t store your number or record your voice so feel free to vote more than once for vim. Want to see the votes live? http://best-editor-ever.s3-website-us-east-1.amazonaws.com/.

Now, how do we build this little contraption? We’ll cover each component but since we’ve talked about Lex and Lambda before we’ll focus mostly on the Amazon Connect component. I’m going to assume you already have a connect instance running.

Amazon Lex

Let’s start with the Lex side of things. We’ll create a bot named VoteEditor with two intents: VoteEditor with a single slot called editor and ConnectToAgent with no slots. We’ll populate our editor slot full of different code editor names (maybe we’ll leave out emacs).

AWS Lambda

Our Lambda function will also be fairly simple. First we’ll create a Amazon DynamoDB table to store our votes. Then we’ll make a helper method to respond to Lex (build_response) – it will just wrap our message in a Lex friendly response format. Now we just have to figure out our flow logic.


def lambda_handler(event, context):
    if 'ConnectToAgent' == event['currentIntent']['name']:
        return build_response("Ok, connecting you to an agent.")
    elif 'VoteEditor' == event['currentIntent']['name']:
        editor = event['currentIntent']['slots']['editor']
        resp = ddb.update_item(
            Key={"name": editor.lower()},
            UpdateExpression="SET votes = :incr + if_not_exists(votes, :default)",
            ExpressionAttributeValues={":incr": 1, ":default": 0},
            ReturnValues="ALL_NEW"
        )
        msg = "Awesome, now {} has {} votes!".format(
            resp['Attributes']['name'],
            resp['Attributes']['votes'])
        return build_response(msg)

Let’s make sure we understand the code. So, if we got a vote for an editor and it doesn’t exist yet then we add that editor with 1 vote. Otherwise we increase the number of votes on that editor by 1. If we get a request for an agent, we terminate the flow with a nice message. Easy. Now we just tell our Lex bot to use our Lambda function to fulfill our intents. We can test that everything is working over text in the Lex console before moving on.

Amazon Connect

Before we can use our Lex bot in a Contact Flow we have to make sure our Amazon Connect instance has access to it. We can do this by hopping over to the Amazon Connect service console, selecting our instance, and navigating to “Contact Flows”. There should be a section called Lex where you can add your bots!

Now that our Amazon Connect instance can invoke our Lex bot we can create a new Contact Flow that contains our Lex bot. We add the bot to our flow through the “Get customer input” widget from the “Interact” category.

Once we’re on the widget we have a “DTMF” tab for taking input from number keys on a phone or the “Amazon Lex” tab for taking voiceinput and passing it to the Lex service. We’ll use the Lex tab and put in some configuration.

Lots of options, but in short we add the bot we want to use (including the version of the bot), the intents we want to use from our bot, and a short prompt to introduce the bot (and mayb prompt the customer for input).

Our final contact flow looks like this:

A real world example might allow a customer to perform many transactions through a Lex bot. Then on an error or ConnectToAgent intent put the customer into a queue where they could talk to a real person. It could collect and store information about users and populate a rich interface for an agent to use so they could jump right into the conversation with all the context they need.

I want to especially highlight the advantage of 8kHz audio support in Lex. Lex originally only supported speech input that was sampled at a higher rate than the 8 kHz input from the phone. Modern digital communication appliations typically use audio signals sampled at a minimum of 16 kHz. This higher fidelity recroding makes it easier differentiate between sounds like “ess” (/s/) and “eff” (/f/) – or so the audio experts tell me. Phones, however, use a much lower quality recording. Humans, and their ears, are pretty good at using surrounding words to figure out what a voice is saying from a lower quality recording (just check the NASA apollo recordings for proof of this). Most digital phone systems are setup to use 8 kHz sampling by default – it’s a nice tradeoff in bandwidth and fidelity. That’s why your voice sometimes sounds different on the phone. On top of this fundmental sampling rate issue you also have to deal with the fact that a lot of phone call data is already lossy (can you hear me now?). There are thousands of different devices from hundreds of different manufacturers, and tons of different software implentations. So… how do you solve this recognition issue?

The Lex team decided that the best way to address this was to expand the set of models they were using for speech recognition to include an 8kHz model. Support for an 8 kHz telephony audio sampling rate provides increased speech recognition accuracy and fidelity for your contact center interactions. This was a great effort by the team that enables a lot of customers to do more with Amazon Connect.

One final note is that Amazon Connect uses the exact same PostContent endpoint that you can use as an external developer so you don’t have to be a Amazon Connect user to take advantage of this 8kHz feature in Lex.

I hope you guys enjoyed this post and as always the real details are in the docs and API Reference.

Randall

US Voting Machines Hacked At DEF CON – Every One

Post Syndicated from Darknet original http://feedproxy.google.com/~r/darknethackers/~3/2jfq8D4XaNo/

US Voting Machines Hacked, some in minutes at this year’s DEF CON “Voting Village” – not something you want to hear really. Especially with the results of recent elections that the World is currently dealing with the consequences from. Of course with physical access, most machines can be dominated in some way or another – […]

The post US…

Read the full post at darknet.org.uk

Commentary on US Election Security

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/07/commentary_on_u.html

Good commentaries from Ed Felten and Matt Blaze.

Both make a point that I have also been saying: hacks can undermine the legitimacy of an election, even if there is no actual voter or vote manipulation.

Felten:

The second lesson is that we should be paying more attention to attacks that aim to undermine the legitimacy of an election rather than changing the election’s result. Election-stealing attacks have gotten most of the attention up to now — ­and we are still vulnerable to them in some places — ­but it appears that external threat actors may be more interested in attacking legitimacy.

Attacks on legitimacy could take several forms. An attacker could disrupt the operation of the election, for example, by corrupting voter registration databases so there is uncertainty about whether the correct people were allowed to vote. They could interfere with post-election tallying processes, so that incorrect results were reported­ an attack that might have the intended effect even if the results were eventually corrected. Or the attacker might fabricate evidence of an attack, and release the false evidence after the election.

Legitimacy attacks could be easier to carry out than election-stealing attacks, as well. For one thing, a legitimacy attacker will typically want the attack to be discovered, although they might want to avoid having the culprit identified. By contrast, an election-stealing attack must avoid detection in order to succeed. (If detected, it might function as a legitimacy attack.)

Blaze:

A hostile state actor who can compromise a handful of county networks might not even need to alter any actual votes to create considerable uncertainty about an election’s legitimacy. It may be sufficient to simply plant some suspicious software on back end networks, create some suspicious audit files, or add some obviously bogus names to to the voter rolls. If the preferred candidate wins, they can quietly do nothing (or, ideally, restore the compromised networks to their original states). If the “wrong” candidate wins, however, they could covertly reveal evidence that county election systems had been compromised, creating public doubt about whether the election had been “rigged”. This could easily impair the ability of the true winner to effectively govern, at least for a while.

In other words, a hostile state actor interested in disruption may actually have an easier task than someone who wants to undetectably steal even a small local office. And a simple phishing and trojan horse email campaign like the one in the NSA report is potentially all that would be needed to carry this out.

Me:

Democratic elections serve two purposes. The first is to elect the winner. But the second is to convince the loser. After the votes are all counted, everyone needs to trust that the election was fair and the results accurate. Attacks against our election system, even if they are ultimately ineffective, undermine that trust and ­ by extension ­ our democracy.

And, finally, a report from the Brennan Center for Justice on how to secure elections.

NSA Document Outlining Russian Attempts to Hack Voter Rolls

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/06/nsa_document_ou.html

This week brought new public evidence about Russian interference in the 2016 election. On Monday, the Intercept published a top-secret National Security Agency document describing Russian hacking attempts against the US election system. While the attacks seem more exploratory than operational ­– and there’s no evidence that they had any actual effect ­– they further illustrate the real threats and vulnerabilities facing our elections, and they point to solutions.

The document describes how the GRU, Russia’s military intelligence agency, attacked a company called VR Systems that, according to its website, provides software to manage voter rolls in eight states. The August 2016 attack was successful, and the attackers used the information they stole from the company’s network to launch targeted attacks against 122 local election officials on October 27, 12 days before the election.

That is where the NSA’s analysis ends. We don’t know whether those 122 targeted attacks were successful, or what their effects were if so. We don’t know whether other election software companies besides VR Systems were targeted, or what the GRU’s overall plan was — if it had one. Certainly, there are ways to disrupt voting by interfering with the voter registration process or voter rolls. But there was no indication on Election Day that people found their names removed from the system, or their address changed, or anything else that would have had an effect — anywhere in the country, let alone in the eight states where VR Systems is deployed. (There were Election Day problems with the voting rolls in Durham, NC ­– one of the states that VR Systems supports ­– but they seem like conventional errors and not malicious action.)

And 12 days before the election (with early voting already well underway in many jurisdictions) seems far too late to start an operation like that. That is why these attacks feel exploratory to me, rather than part of an operational attack. The Russians were seeing how far they could get, and keeping those accesses in their pocket for potential future use.

Presumably, this document was intended for the Justice Department, including the FBI, which would be the proper agency to continue looking into these hacks. We don’t know what happened next, if anything. VR Systems isn’t commenting, and the names of the local election officials targeted did not appear in the NSA document.

So while this document isn’t much of a smoking gun, it’s yet more evidence of widespread Russian attempts to interfere last year.

The document was, allegedly, sent to the Intercept anonymously. An NSA contractor, Reality Leigh Winner, was arrested Saturday and charged with mishandling classified information. The speed with which the government identified her serves as a caution to anyone wanting to leak official US secrets.

The Intercept sent a scan of the document to another source during its reporting. That scan showed a crease in the original document, which implied that someone had printed the document and then carried it out of some secure location. The second source, according to the FBI’s affidavit against Winner, passed it on to the NSA. From there, NSA investigators were able to look at their records and determine that only six people had printed out the document. (The government may also have been able to track the printout through secret dots that identified the printer.) Winner was the only one of those six who had been in e-mail contact with the Intercept. It is unclear whether the e-mail evidence was from Winner’s NSA account or her personal account, but in either case, it’s incredibly sloppy tradecraft.

With President Trump’s election, the issue of Russian interference in last year’s campaign has become highly politicized. Reports like the one from the Office of the Director of National Intelligence in January have been criticized by partisan supporters of the White House. It’s interesting that this document was reported by the Intercept, which has been historically skeptical about claims of Russian interference. (I was quoted in their story, and they showed me a copy of the NSA document before it was published.) The leaker was even praised by WikiLeaks founder Julian Assange, who up until now has been traditionally critical of allegations of Russian election interference.

This demonstrates the power of source documents. It’s easy to discount a Justice Department official or a summary report. A detailed NSA document is much more convincing. Right now, there’s a federal suit to force the ODNI to release the entire January report, not just the unclassified summary. These efforts are vital.

This hack will certainly come up at the Senate hearing where former FBI director James B. Comey is scheduled to testify Thursday. Last year, there were several stories about voter databases being targeted by Russia. Last August, the FBI confirmed that the Russians successfully hacked voter databases in Illinois and Arizona. And a month later, an unnamed Department of Homeland Security official said that the Russians targeted voter databases in 20 states. Again, we don’t know of anything that came of these hacks, but expect Comey to be asked about them. Unfortunately, any details he does know are almost certainly classified, and won’t be revealed in open testimony.

But more important than any of this, we need to better secure our election systems going forward. We have significant vulnerabilities in our voting machines, our voter rolls and registration process, and the vote tabulation systems after the polls close. In January, DHS designated our voting systems as critical national infrastructure, but so far that has been entirely for show. In the United States, we don’t have a single integrated election. We have 50-plus individual elections, each with its own rules and its own regulatory authorities. Federal standards that mandate voter-verified paper ballots and post-election auditing would go a long way to secure our voting system. These attacks demonstrate that we need to secure the voter rolls, as well.

Democratic elections serve two purposes. The first is to elect the winner. But the second is to convince the loser. After the votes are all counted, everyone needs to trust that the election was fair and the results accurate. Attacks against our election system, even if they are ultimately ineffective, undermine that trust and ­– by extension ­– our democracy. Yes, fixing this will be expensive. Yes, it will require federal action in what’s historically been state-run systems. But as a country, we have no other option.

This essay previously appeared in the Washington Post.

Securing Elections

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/05/securing_electi.html

Technology can do a lot more to make our elections more secure and reliable, and to ensure that participation in the democratic process is available to all. There are three parts to this process.

First, the voter registration process can be improved. The whole process can be streamlined. People should be able to register online, just as they can register for other government services. The voter rolls need to be protected from tampering, as that’s one of the major ways hackers can disrupt the election.

Second, the voting process can be significantly improved. Voting machines need to be made more secure. There are a lot of technical details best left to the voting-security experts who can deal with them, but such machines must include a paper ballot that provides a record verifiable by voters. The simplest and most reliable way to do that is already practiced in 37 states: optical-scan paper ballots, marked by the voters and counted by computer, but recountable by hand.

We need national security standards for voting machines, and funding for states to procure machines that comply with those standards.

This means no Internet voting. While that seems attractive, and certainly a way technology can improve voting, we don’t know how to do it securely. We simply can’t build an Internet voting system that is secure against hacking because of the requirement for a secret ballot. This makes voting different from banking and anything else we do on the Internet, and it makes security much harder. Even allegations of vote hacking would be enough to undermine confidence in the system, and we simply cannot afford that. We need a system of pre-election and post-election security audits of these voting machines to increase confidence in the system.

The third part of the voting process we need to secure is the tabulation system. After the polls close, we aggregate votes — ­from individual machines, to polling places, to precincts, and finally to totals. This system is insecure as well, and we can do a lot more to make it reliable. Similarly, our system of recounts can be made more secure and efficient.

We have the technology to do all of this. The problem is political will. We have to decide that the goal of our election system is for the most people to be able to vote with the least amount of effort. If we continue to enact voter suppression measures like ID requirements, barriers to voter registration, limitations on early voting, reduced polling place hours, and faulty machines, then we are harming democracy more than we are by allowing our voting machines to be hacked.

We have already declared our election system to be critical national infrastructure. This is largely symbolic, but it demonstrates a commitment to secure elections and makes funding and other resources available to states. We can do much more. We owe it to democracy to do it.

This essay previously appeared on TheAtlantic.com.

Chris Lamb elected as Debian project leader

Post Syndicated from jake original https://lwn.net/Articles/720165/rss

The 2017 Debian project leader (DPL) election has completed; Chris Lamb won, over incumbent DPL Mehdi Dogguy. Details of the voting can be found on the election web page. Dogguy posted his last “bits from the DPL” congratulating Lamb, filling the project in on what he has been up to over the last month plus, and more: “Serving as DPL for the past year has been a real honour and a
fantastic experience for me. It also helped me to have a different
perspective on the project and my future involvement.

Last but not least, I wanted to confirm to other fellow Debian
Developers that serving as DPL is not a traumatic experience and I am
still as sane as I was one year ago 🙂 If you have ideas on how to
make Debian a better place, project, OS, community, FOSS citizen, …
please nominate yourself for DPL elections next year! Worst case
scenario, you would contribute to the debate about Debian’s future.”

Weekly roundup: Slog

Post Syndicated from Eevee original https://eev.ee/dev/2017/03/21/weekly-roundup-slog/

Uhhh I am having a hell of a time getting back in the saddle. We had a friend visit, and I think he gave me his cold, and my cat is an asshole, and the dog ate my homework.

  • blog: Some work on some words.

  • art: I haven’t drawn in months. I tried to do it a bit. Results inconclusive.

  • games: I spent a whole day powering through the last 20 or so Strawberry Jam games, just in time for voting to end! Phew! The results (probably NSFW) are in, and, er, I won? This didn’t really occur to me as a thing that could happen and I feel a little guilty about it, hm.

  • gamedev: I merged most of the later fox flux work back into Isaac’s Descent HD, which I’m treating as a central repo for the engine guts I keep reusing. I really, really need to sit down and split the engine stuff out cleanly so I don’t have to keep cherry-picking stuff around, but I haven’t had time yet.

    Also, Mel and I started working on a little PICO-8 toy in an attempt to get ourselves moving again. It’s coming along okay.

Spoilers for next week: I’m doing better this week, finally. My sleep is still wrecked and I still have a cold, but I’m at least sorta doing things.

Australia Copyright Safe Harbour Provision Backed By Prime Minister

Post Syndicated from Andy original https://torrentfreak.com/australia-copyright-safe-harbour-provision-backed-by-prime-minister-170313/

The notion that online service providers should not generally be held liable for the infringing acts of their users is something that has broadly been taken for granted across the United States and Europe.

To keep their immunity, all platforms are expected to respond relatively swiftly to copyright claims, removing content if applicable and dealing with repeat infringers in an appropriate manner, a lesson currently causing problems for ISP Cox in the US.

In Australia, however, the situation is less certain. Due to what some believe amounts to a drafting error in Australia’s implementation of the Australia – US Free Trade Agreement (AUSFTA), so-called safe harbor provisions only apply to commercial Internet service providers.

This means that while local ISPs such as Telstra receive protection from copyright infringement complaints, places like schools, universities, museums, libraries and archives do not. Platforms such as Google, Facebook, and YouTube also face the same potential copyright minefield.

To solve this problem and put Australia on a similar footing to technology companies operating in the United States, proposed amendments to the Copyright Act will see all of the above receiving enhanced safe harbor protections while bringing the country into compliance with AUSFTA.

While technology companies are welcoming the changes, there is significant dissent among artists and other creators. Last October, a coalition of 200 artists including Delta Goodrem and INXS, said that the changes would undermine their work while empowering platforms like Facebook that effectively monetize other people’s content.

But for now, momentum appears to be shifting in favor of the technology platforms. A report in The Australian (paywall) indicates that Prime Minister Malcolm Turnbull has given the safe harbor amendments his support. It won’t be all plain sailing from here, however.

The government is to set up a Senate committee into the copyright amendments to determine whether the amendments will promote piracy as the entertainment industries are warning. The inquiry will launch after the government introduces the Copyright Amendment (Disability Access and Other Measures) Bill into Parliament after March 20.

The Australian suggests that under Schedule 2 of the bill, online platforms would receive immunity for infringing user-uploaded content. However, totally immunity is an unrealistic eventuality that would almost certainly have to be tempered by rules concerning takedowns.

Those details will be examined in-depth as part of the committee inquiry, which will run its course in advance of parliamentary debate and voting.

“The Government has conducted extensive consultation on this proposal including through an exposure draft and is considering the feedback that has been received,” said Communications Minister Mitch Fifield.

“There are highly regarded stakeholders on both sides of the debate. When legislation is introduced, we expect that it would be subject to further scrutiny and industry consultation in the form of a Senate committee inquiry.”

The move towards expanded safe harbor provisions in Australia takes place to a backdrop of a tightening of opinions in both the United States and Europe. The so-called content “value gap” on sites such as YouTube is said to be a product of generous safe harbor, which has led to calls for the DMCA to be tightened and legislative amendments such as Article 13 in Europe.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and ANONYMOUS VPN services.

1984 is the new Bible in the age of Trump

Post Syndicated from Robert Graham original http://blog.erratasec.com/2017/02/1984-is-new-bible.html

In the age of Trump, Orwell’s book 1984 is becoming the new Bible: a religious text which few read, but which many claim supports their beliefs. A good demonstration is this CNN op-ed, in which the author describes Trump as being Orwellian, but mostly just because Trump is a Republican.

Trump’s populist attacks against our (classically) liberal world order is indeed cause for concern. His assault on the truth is indeed a bit Orwellian. But it’s op-eds like this one at CNN that are part of the problem.
While the author of the op-ed spends much time talking about his dogs (“Winston”, “Julia”), and how much he hates Trump, he spends little time on the core thesis “Orwellianism”. When he does, it’s mostly about old political disagreements. For example, the op-ed calls Trump’s cabinet appointees Orwellian simply because they are Republicans:

He has provided us with Betsy DeVos, a secretary of education nominee who is widely believed to oppose public education, and who promotes the truly Orwellian-sounding concept of “school choice,” a plan that seems well-intentioned but which critics complain actually siphons much-needed funds from public to private education institutions.

Calling school-choice “Orwellian” is absurd. Republicans want to privatize more, and the Democrats want the state to run more of the economy. It’s the same disagreement that divides the two parties on almost any policy issue. When you call every little political disagreement “Orwellian” then you devalue the idea. I’m Republican, so of course I’d argue that the it’s the state-run education system giving parents zero choice that is the thing that’s Orwellian here. And now we bicker, both convinced that Orwell is on our side in this debate. #WhatWouldOrwellDo
If something is “Orwellian”, then you need to do a better job demonstrating this, making the analogy clear. For example, last year I showed how in response to a political disagreement, that Wikipedia and old newspaper articles were edited in order to conform to the new political reality. This is a clear example of Winston Smith’s job of changing the past in order to match the present.
But even such clear documentation is probably powerless to change anybody’s mind. Whether “changing the text of old newspaper articles to fit modern politics” is Orwellian depends entirely on your politics, whether the changes agree with your views. Go follow the link [*] and see for yourself and see if you agree with the change (replacing the word “refugee” in old articles with “asylee” instead).
It’s this that Orwell was describing. Doublethink wasn’t something forced onto us by a totalitarian government so much as something we willingly adopted ourselves. The target of Orwell’s criticism wasn’t them, the totalitarian government, but us, the people who willingly went along with it. Doublethink is what people in both parties (Democrats and Republicans) do equally, regardless of the who resides in the White House.
Trump is an alt-Putin. He certainly wants to become a totalitarian. But at this point, his lies are juvenile and transparent, which even his supporters find difficult believing [*]. The most Orwellian thing about him is what he inherits from Obama [*]: the two Party system, perpetual war, omnipresent surveillance, the propaganda system, and our nascent cyber-police-state [*].
Conclusion

Yes, people should read 1984 in the age of Trump, not because he’s created the Orwellian system, but because he’s trying to exploit the system that’s already there. If you believe he’s Orwellian because he’s Republican, as the foolish author of that CNN op-ed believes, then you’ve missed the point of Orwell’s novel completely.

Bonus: Doing a point-by-point rebuttal gets boring, and makes the post long, but ought to be done out of a sense of completeness. The following paragraph contains the most “Orwell” points, but it’s all essentially nonsense:

We are living in this state of flux in real life. Russia was and likely is our nation’s fiercest rival, yet as a candidate, President Trump famously stated, “Russia, if you’re listening, I hope you’re able to find the 30,000 [Clinton] emails that are missing.” He praises Putin but states that perhaps he may not actually like him when they meet. WikiLeaks published DNC data alleged to have been obtained by Russian operatives, but the election was not “rigged.” A recount would be “ridiculous,” yet voter fraud was rampant. Trusted sources of information are “fake news,” and somehow Chelsea Manning, WikiLeaks’ most notable whistleblower, is now an “ungrateful traitor.”

Trump’s asking Russia to find the missing emails was clearly a joke. Trump’s speech is marked by exaggeration and jokes like this. That Trump’s rivals insist his jokes be taken seriously is the problem here, more than what he’s joking about.

The correct Orwellian analogy to draw here is is the Eurasia (Russia) and Eastasia (China) parallels. Under Obama, China was a close trading partner while Russia was sanctioned for invading the Ukraine. Under Trump, it’s China who is our top rival while Russia/Putin is more of our friends. What’s Orwellian is how polls [*] of what Republicans think of Russia have gone through a shift, “We’ve always been at war with Eastasia”.

The above paragraph implies Trump said the election wasn’t “rigged”. No, Trump still says the election was rigged, even after he won it. [*] It’s Democrats who’ve flip-flopped on their opinion whether the election was “rigged” after Trump’s win. Trump attacks the election system because that’s what illiberal totalitarians always do, not because it’s Orwellian.

“Recounts” and “fraudulent votes” aren’t the same thing. Somebody registered to vote, and voting, in multiple states is not something that’ll be detected with a “recount” in any one state, for example. Trump’s position on voter fraud is absurd, but it’s not Orwellian.

Instead of these small things, what’s Orwellian is Trump’s grander story of a huge popular “movement” behind him. That’s why his inauguration numbers are important. That’s why losing the popular vote is important. It’s why he keeps using the word “movement” in all his speeches. It’s the big lie he’s telling that makes him Orwellian, not all the small lies.

Trusted sources of news are indeed “fake news”. The mainstream media has problems, whether it’s their tendency to sensationalism, or the way they uncritically repeat government propaganda (“according to senior government officials”) regardless of which Party controls the White House. Indeed, Orwell himself was a huge critic of the press — sometimes what they report is indeed “fake news”, not simply a mistake but something that violates the press’s own standards.

Yes, the President or high-level government officials have no business attacking the press the way Trump does, regardless if they deserve it. Trump indeed had a few legitimate criticism of the press, but his attacks have quickly devolved to attacking the press whenever it’s simply Truth disagreeing with Trump’s lies. It’s all attacks against the independent press that are the problem, not the label “fake news”.

As Wikipedia documents, “the term “traitor” has been used as a political epithet, regardless of any verifiable treasonable action”. Despite being found not guilty of “aiding the enemy”, Chelsea Manning was convicted of espionage. Reasonable people can disagree about Manning’s action — while you may not like the “traitor” epithet, it’s not an Orwellian term.

Instead, what is Orwellian is insisting Manning was a “whistleblower”. Reasonable people disagree with that description. Manning didn’t release specific diplomatic cables demonstrative of official wrongdoing, but the entire dump of all cables going back more than a decade. It’s okay to call Manning a whistleblower (I might describe her as such), but it’s absurd to claim this is some objective truth. For example, the Wikipedia article [*] on Chelsea Manning documents several people calling her a whistleblower, but does not itself use that term to describe Manning. The struggle between objective and subjective “Truth” is a big part of Orwell’s work.

What I’m demonstrating here in this bonus section is the foolishness of that CNN op-ed. He hates Trump, but entirely misunderstands Orwell. He does a poor job pinning down Trump on exactly how he fits the Orwellian mode. He writes like somebody who hasn’t actually read the book at all.

Security and the Internet of Things

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/02/security_and_th.html

Last year, on October 21, your digital video recorder ­- or at least a DVR like yours ­- knocked Twitter off the internet. Someone used your DVR, along with millions of insecure webcams, routers, and other connected devices, to launch an attack that started a chain reaction, resulting in Twitter, Reddit, Netflix, and many sites going off the internet. You probably didn’t realize that your DVR had that kind of power. But it does.

All computers are hackable. This has as much to do with the computer market as it does with the technologies. We prefer our software full of features and inexpensive, at the expense of security and reliability. That your computer can affect the security of Twitter is a market failure. The industry is filled with market failures that, until now, have been largely ignorable. As computers continue to permeate our homes, cars, businesses, these market failures will no longer be tolerable. Our only solution will be regulation, and that regulation will be foisted on us by a government desperate to “do something” in the face of disaster.

In this article I want to outline the problems, both technical and political, and point to some regulatory solutions. Regulation might be a dirty word in today’s political climate, but security is the exception to our small-government bias. And as the threats posed by computers become greater and more catastrophic, regulation will be inevitable. So now’s the time to start thinking about it.

We also need to reverse the trend to connect everything to the internet. And if we risk harm and even death, we need to think twice about what we connect and what we deliberately leave uncomputerized.

If we get this wrong, the computer industry will look like the pharmaceutical industry, or the aircraft industry. But if we get this right, we can maintain the innovative environment of the internet that has given us so much.

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We no longer have things with computers embedded in them. We have computers with things attached to them.

Your modern refrigerator is a computer that keeps things cold. Your oven, similarly, is a computer that makes things hot. An ATM is a computer with money inside. Your car is no longer a mechanical device with some computers inside; it’s a computer with four wheels and an engine. Actually, it’s a distributed system of over 100 computers with four wheels and an engine. And, of course, your phones became full-power general-purpose computers in 2007, when the iPhone was introduced.

We wear computers: fitness trackers and computer-enabled medical devices ­- and, of course, we carry our smartphones everywhere. Our homes have smart thermostats, smart appliances, smart door locks, even smart light bulbs. At work, many of those same smart devices are networked together with CCTV cameras, sensors that detect customer movements, and everything else. Cities are starting to embed smart sensors in roads, streetlights, and sidewalk squares, also smart energy grids and smart transportation networks. A nuclear power plant is really just a computer that produces electricity, and ­- like everything else we’ve just listed -­ it’s on the internet.

The internet is no longer a web that we connect to. Instead, it’s a computerized, networked, and interconnected world that we live in. This is the future, and what we’re calling the Internet of Things.

Broadly speaking, the Internet of Things has three parts. There are the sensors that collect data about us and our environment: smart thermostats, street and highway sensors, and those ubiquitous smartphones with their motion sensors and GPS location receivers. Then there are the “smarts” that figure out what the data means and what to do about it. This includes all the computer processors on these devices and ­- increasingly ­- in the cloud, as well as the memory that stores all of this information. And finally, there are the actuators that affect our environment. The point of a smart thermostat isn’t to record the temperature; it’s to control the furnace and the air conditioner. Driverless cars collect data about the road and the environment to steer themselves safely to their destinations.

You can think of the sensors as the eyes and ears of the internet. You can think of the actuators as the hands and feet of the internet. And you can think of the stuff in the middle as the brain. We are building an internet that senses, thinks, and acts.

This is the classic definition of a robot. We’re building a world-size robot, and we don’t even realize it.

To be sure, it’s not a robot in the classical sense. We think of robots as discrete autonomous entities, with sensors, brain, and actuators all together in a metal shell. The world-size robot is distributed. It doesn’t have a singular body, and parts of it are controlled in different ways by different people. It doesn’t have a central brain, and it has nothing even remotely resembling a consciousness. It doesn’t have a single goal or focus. It’s not even something we deliberately designed. It’s something we have inadvertently built out of the everyday objects we live with and take for granted. It is the extension of our computers and networks into the real world.

This world-size robot is actually more than the Internet of Things. It’s a combination of several decades-old computing trends: mobile computing, cloud computing, always-on computing, huge databases of personal information, the Internet of Things ­- or, more precisely, cyber-physical systems ­- autonomy, and artificial intelligence. And while it’s still not very smart, it’ll get smarter. It’ll get more powerful and more capable through all the interconnections we’re building.

It’ll also get much more dangerous.

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Computer security has been around for almost as long as computers have been. And while it’s true that security wasn’t part of the design of the original internet, it’s something we have been trying to achieve since its beginning.

I have been working in computer security for over 30 years: first in cryptography, then more generally in computer and network security, and now in general security technology. I have watched computers become ubiquitous, and have seen firsthand the problems ­- and solutions ­- of securing these complex machines and systems. I’m telling you all this because what used to be a specialized area of expertise now affects everything. Computer security is now everything security. There’s one critical difference, though: The threats have become greater.

Traditionally, computer security is divided into three categories: confidentiality, integrity, and availability. For the most part, our security concerns have largely centered around confidentiality. We’re concerned about our data and who has access to it ­- the world of privacy and surveillance, of data theft and misuse.

But threats come in many forms. Availability threats: computer viruses that delete our data, or ransomware that encrypts our data and demands payment for the unlock key. Integrity threats: hackers who can manipulate data entries can do things ranging from changing grades in a class to changing the amount of money in bank accounts. Some of these threats are pretty bad. Hospitals have paid tens of thousands of dollars to criminals whose ransomware encrypted critical medical files. JPMorgan Chase spends half a billion on cybersecurity a year.

Today, the integrity and availability threats are much worse than the confidentiality threats. Once computers start affecting the world in a direct and physical manner, there are real risks to life and property. There is a fundamental difference between crashing your computer and losing your spreadsheet data, and crashing your pacemaker and losing your life. This isn’t hyperbole; recently researchers found serious security vulnerabilities in St. Jude Medical’s implantable heart devices. Give the internet hands and feet, and it will have the ability to punch and kick.

Take a concrete example: modern cars, those computers on wheels. The steering wheel no longer turns the axles, nor does the accelerator pedal change the speed. Every move you make in a car is processed by a computer, which does the actual controlling. A central computer controls the dashboard. There’s another in the radio. The engine has 20 or so computers. These are all networked, and increasingly autonomous.

Now, let’s start listing the security threats. We don’t want car navigation systems to be used for mass surveillance, or the microphone for mass eavesdropping. We might want it to be used to determine a car’s location in the event of a 911 call, and possibly to collect information about highway congestion. We don’t want people to hack their own cars to bypass emissions-control limitations. We don’t want manufacturers or dealers to be able to do that, either, as Volkswagen did for years. We can imagine wanting to give police the ability to remotely and safely disable a moving car; that would make high-speed chases a thing of the past. But we definitely don’t want hackers to be able to do that. We definitely don’t want them disabling the brakes in every car without warning, at speed. As we make the transition from driver-controlled cars to cars with various driver-assist capabilities to fully driverless cars, we don’t want any of those critical components subverted. We don’t want someone to be able to accidentally crash your car, let alone do it on purpose. And equally, we don’t want them to be able to manipulate the navigation software to change your route, or the door-lock controls to prevent you from opening the door. I could go on.

That’s a lot of different security requirements, and the effects of getting them wrong range from illegal surveillance to extortion by ransomware to mass death.

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Our computers and smartphones are as secure as they are because companies like Microsoft, Apple, and Google spend a lot of time testing their code before it’s released, and quickly patch vulnerabilities when they’re discovered. Those companies can support large, dedicated teams because those companies make a huge amount of money, either directly or indirectly, from their software ­ and, in part, compete on its security. Unfortunately, this isn’t true of embedded systems like digital video recorders or home routers. Those systems are sold at a much lower margin, and are often built by offshore third parties. The companies involved simply don’t have the expertise to make them secure.

At a recent hacker conference, a security researcher analyzed 30 home routers and was able to break into half of them, including some of the most popular and common brands. The denial-of-service attacks that forced popular websites like Reddit and Twitter off the internet last October were enabled by vulnerabilities in devices like webcams and digital video recorders. In August, two security researchers demonstrated a ransomware attack on a smart thermostat.

Even worse, most of these devices don’t have any way to be patched. Companies like Microsoft and Apple continuously deliver security patches to your computers. Some home routers are technically patchable, but in a complicated way that only an expert would attempt. And the only way for you to update the firmware in your hackable DVR is to throw it away and buy a new one.

The market can’t fix this because neither the buyer nor the seller cares. The owners of the webcams and DVRs used in the denial-of-service attacks don’t care. Their devices were cheap to buy, they still work, and they don’t know any of the victims of the attacks. The sellers of those devices don’t care: They’re now selling newer and better models, and the original buyers only cared about price and features. There is no market solution, because the insecurity is what economists call an externality: It’s an effect of the purchasing decision that affects other people. Think of it kind of like invisible pollution.

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Security is an arms race between attacker and defender. Technology perturbs that arms race by changing the balance between attacker and defender. Understanding how this arms race has unfolded on the internet is essential to understanding why the world-size robot we’re building is so insecure, and how we might secure it. To that end, I have five truisms, born from what we’ve already learned about computer and internet security. They will soon affect the security arms race everywhere.

Truism No. 1: On the internet, attack is easier than defense.

There are many reasons for this, but the most important is the complexity of these systems. More complexity means more people involved, more parts, more interactions, more mistakes in the design and development process, more of everything where hidden insecurities can be found. Computer-security experts like to speak about the attack surface of a system: all the possible points an attacker might target and that must be secured. A complex system means a large attack surface. The defender has to secure the entire attack surface. The attacker just has to find one vulnerability ­- one unsecured avenue for attack -­ and gets to choose how and when to attack. It’s simply not a fair battle.

There are other, more general, reasons why attack is easier than defense. Attackers have a natural agility that defenders often lack. They don’t have to worry about laws, and often not about morals or ethics. They don’t have a bureaucracy to contend with, and can more quickly make use of technical innovations. Attackers also have a first-mover advantage. As a society, we’re generally terrible at proactive security; we rarely take preventive security measures until an attack actually happens. So more advantages go to the attacker.

Truism No. 2: Most software is poorly written and insecure.

If complexity isn’t enough, we compound the problem by producing lousy software. Well-written software, like the kind found in airplane avionics, is both expensive and time-consuming to produce. We don’t want that. For the most part, poorly written software has been good enough. We’d all rather live with buggy software than pay the prices good software would require. We don’t mind if our games crash regularly, or our business applications act weird once in a while. Because software has been largely benign, it hasn’t mattered. This has permeated the industry at all levels. At universities, we don’t teach how to code well. Companies don’t reward quality code in the same way they reward fast and cheap. And we consumers don’t demand it.

But poorly written software is riddled with bugs, sometimes as many as one per 1,000 lines of code. Some of them are inherent in the complexity of the software, but most are programming mistakes. Not all bugs are vulnerabilities, but some are.

Truism No. 3: Connecting everything to each other via the internet will expose new vulnerabilities.

The more we network things together, the more vulnerabilities on one thing will affect other things. On October 21, vulnerabilities in a wide variety of embedded devices were all harnessed together to create what hackers call a botnet. This botnet was used to launch a distributed denial-of-service attack against a company called Dyn. Dyn provided a critical internet function for many major internet sites. So when Dyn went down, so did all those popular websites.

These chains of vulnerabilities are everywhere. In 2012, journalist Mat Honan suffered a massive personal hack because of one of them. A vulnerability in his Amazon account allowed hackers to get into his Apple account, which allowed them to get into his Gmail account. And in 2013, the Target Corporation was hacked by someone stealing credentials from its HVAC contractor.

Vulnerabilities like these are particularly hard to fix, because no one system might actually be at fault. It might be the insecure interaction of two individually secure systems.

Truism No. 4: Everybody has to stop the best attackers in the world.

One of the most powerful properties of the internet is that it allows things to scale. This is true for our ability to access data or control systems or do any of the cool things we use the internet for, but it’s also true for attacks. In general, fewer attackers can do more damage because of better technology. It’s not just that these modern attackers are more efficient, it’s that the internet allows attacks to scale to a degree impossible without computers and networks.

This is fundamentally different from what we’re used to. When securing my home against burglars, I am only worried about the burglars who live close enough to my home to consider robbing me. The internet is different. When I think about the security of my network, I have to be concerned about the best attacker possible, because he’s the one who’s going to create the attack tool that everyone else will use. The attacker that discovered the vulnerability used to attack Dyn released the code to the world, and within a week there were a dozen attack tools using it.

Truism No. 5: Laws inhibit security research.

The Digital Millennium Copyright Act is a terrible law that fails at its purpose of preventing widespread piracy of movies and music. To make matters worse, it contains a provision that has critical side effects. According to the law, it is a crime to bypass security mechanisms that protect copyrighted work, even if that bypassing would otherwise be legal. Since all software can be copyrighted, it is arguably illegal to do security research on these devices and to publish the result.

Although the exact contours of the law are arguable, many companies are using this provision of the DMCA to threaten researchers who expose vulnerabilities in their embedded systems. This instills fear in researchers, and has a chilling effect on research, which means two things: (1) Vendors of these devices are more likely to leave them insecure, because no one will notice and they won’t be penalized in the market, and (2) security engineers don’t learn how to do security better.
Unfortunately, companies generally like the DMCA. The provisions against reverse-engineering spare them the embarrassment of having their shoddy security exposed. It also allows them to build proprietary systems that lock out competition. (This is an important one. Right now, your toaster cannot force you to only buy a particular brand of bread. But because of this law and an embedded computer, your Keurig coffee maker can force you to buy a particular brand of coffee.)

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In general, there are two basic paradigms of security. We can either try to secure something well the first time, or we can make our security agile. The first paradigm comes from the world of dangerous things: from planes, medical devices, buildings. It’s the paradigm that gives us secure design and secure engineering, security testing and certifications, professional licensing, detailed preplanning and complex government approvals, and long times-to-market. It’s security for a world where getting it right is paramount because getting it wrong means people dying.

The second paradigm comes from the fast-moving and heretofore largely benign world of software. In this paradigm, we have rapid prototyping, on-the-fly updates, and continual improvement. In this paradigm, new vulnerabilities are discovered all the time and security disasters regularly happen. Here, we stress survivability, recoverability, mitigation, adaptability, and muddling through. This is security for a world where getting it wrong is okay, as long as you can respond fast enough.

These two worlds are colliding. They’re colliding in our cars -­ literally -­ in our medical devices, our building control systems, our traffic control systems, and our voting machines. And although these paradigms are wildly different and largely incompatible, we need to figure out how to make them work together.

So far, we haven’t done very well. We still largely rely on the first paradigm for the dangerous computers in cars, airplanes, and medical devices. As a result, there are medical systems that can’t have security patches installed because that would invalidate their government approval. In 2015, Chrysler recalled 1.4 million cars to fix a software vulnerability. In September 2016, Tesla remotely sent a security patch to all of its Model S cars overnight. Tesla sure sounds like it’s doing things right, but what vulnerabilities does this remote patch feature open up?

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Until now we’ve largely left computer security to the market. Because the computer and network products we buy and use are so lousy, an enormous after-market industry in computer security has emerged. Governments, companies, and people buy the security they think they need to secure themselves. We’ve muddled through well enough, but the market failures inherent in trying to secure this world-size robot will soon become too big to ignore.

Markets alone can’t solve our security problems. Markets are motivated by profit and short-term goals at the expense of society. They can’t solve collective-action problems. They won’t be able to deal with economic externalities, like the vulnerabilities in DVRs that resulted in Twitter going offline. And we need a counterbalancing force to corporate power.

This all points to policy. While the details of any computer-security system are technical, getting the technologies broadly deployed is a problem that spans law, economics, psychology, and sociology. And getting the policy right is just as important as getting the technology right because, for internet security to work, law and technology have to work together. This is probably the most important lesson of Edward Snowden’s NSA disclosures. We already knew that technology can subvert law. Snowden demonstrated that law can also subvert technology. Both fail unless each work. It’s not enough to just let technology do its thing.

Any policy changes to secure this world-size robot will mean significant government regulation. I know it’s a sullied concept in today’s world, but I don’t see any other possible solution. It’s going to be especially difficult on the internet, where its permissionless nature is one of the best things about it and the underpinning of its most world-changing innovations. But I don’t see how that can continue when the internet can affect the world in a direct and physical manner.

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I have a proposal: a new government regulatory agency. Before dismissing it out of hand, please hear me out.

We have a practical problem when it comes to internet regulation. There’s no government structure to tackle this at a systemic level. Instead, there’s a fundamental mismatch between the way government works and the way this technology works that makes dealing with this problem impossible at the moment.

Government operates in silos. In the U.S., the FAA regulates aircraft. The NHTSA regulates cars. The FDA regulates medical devices. The FCC regulates communications devices. The FTC protects consumers in the face of “unfair” or “deceptive” trade practices. Even worse, who regulates data can depend on how it is used. If data is used to influence a voter, it’s the Federal Election Commission’s jurisdiction. If that same data is used to influence a consumer, it’s the FTC’s. Use those same technologies in a school, and the Department of Education is now in charge. Robotics will have its own set of problems, and no one is sure how that is going to be regulated. Each agency has a different approach and different rules. They have no expertise in these new issues, and they are not quick to expand their authority for all sorts of reasons.

Compare that with the internet. The internet is a freewheeling system of integrated objects and networks. It grows horizontally, demolishing old technological barriers so that people and systems that never previously communicated now can. Already, apps on a smartphone can log health information, control your energy use, and communicate with your car. That’s a set of functions that crosses jurisdictions of at least four different government agencies, and it’s only going to get worse.

Our world-size robot needs to be viewed as a single entity with millions of components interacting with each other. Any solutions here need to be holistic. They need to work everywhere, for everything. Whether we’re talking about cars, drones, or phones, they’re all computers.

This has lots of precedent. Many new technologies have led to the formation of new government regulatory agencies. Trains did, cars did, airplanes did. Radio led to the formation of the Federal Radio Commission, which became the FCC. Nuclear power led to the formation of the Atomic Energy Commission, which eventually became the Department of Energy. The reasons were the same in every case. New technologies need new expertise because they bring with them new challenges. Governments need a single agency to house that new expertise, because its applications cut across several preexisting agencies. It’s less that the new agency needs to regulate -­ although that’s often a big part of it -­ and more that governments recognize the importance of the new technologies.

The internet has famously eschewed formal regulation, instead adopting a multi-stakeholder model of academics, businesses, governments, and other interested parties. My hope is that we can keep the best of this approach in any regulatory agency, looking more at the new U.S. Digital Service or the 18F office inside the General Services Administration. Both of those organizations are dedicated to providing digital government services, and both have collected significant expertise by bringing people in from outside of government, and both have learned how to work closely with existing agencies. Any internet regulatory agency will similarly need to engage in a high level of collaborate regulation -­ both a challenge and an opportunity.

I don’t think any of us can predict the totality of the regulations we need to ensure the safety of this world, but here’s a few. We need government to ensure companies follow good security practices: testing, patching, secure defaults -­ and we need to be able to hold companies liable when they fail to do these things. We need government to mandate strong personal data protections, and limitations on data collection and use. We need to ensure that responsible security research is legal and well-funded. We need to enforce transparency in design, some sort of code escrow in case a company goes out of business, and interoperability between devices of different manufacturers, to counterbalance the monopolistic effects of interconnected technologies. Individuals need the right to take their data with them. And internet-enabled devices should retain some minimal functionality if disconnected from the internet

I’m not the only one talking about this. I’ve seen proposals for a National Institutes of Health analog for cybersecurity. University of Washington law professor Ryan Calo has proposed a Federal Robotics Commission. I think it needs to be broader: maybe a Department of Technology Policy.

Of course there will be problems. There’s a lack of expertise in these issues inside government. There’s a lack of willingness in government to do the hard regulatory work. Industry is worried about any new bureaucracy: both that it will stifle innovation by regulating too much and that it will be captured by industry and regulate too little. A domestic regulatory agency will have to deal with the fundamentally international nature of the problem.

But government is the entity we use to solve problems like this. Governments have the scope, scale, and balance of interests to address the problems. It’s the institution we’ve built to adjudicate competing social interests and internalize market externalities. Left to their own devices, the market simply can’t. That we’re currently in the middle of an era of low government trust, where many of us can’t imagine government doing anything positive in an area like this, is to our detriment.

Here’s the thing: Governments will get involved, regardless. The risks are too great, and the stakes are too high. Government already regulates dangerous physical systems like cars and medical devices. And nothing motivates the U.S. government like fear. Remember 2001? A nominally small-government Republican president created the Office of Homeland Security 11 days after the terrorist attacks: a rushed and ill-thought-out decision that we’ve been trying to fix for over a decade. A fatal disaster will similarly spur our government into action, and it’s unlikely to be well-considered and thoughtful action. Our choice isn’t between government involvement and no government involvement. Our choice is between smarter government involvement and stupider government involvement. We have to start thinking about this now. Regulations are necessary, important, and complex; and they’re coming. We can’t afford to ignore these issues until it’s too late.

We also need to start disconnecting systems. If we cannot secure complex systems to the level required by their real-world capabilities, then we must not build a world where everything is computerized and interconnected.

There are other models. We can enable local communications only. We can set limits on collected and stored data. We can deliberately design systems that don’t interoperate with each other. We can deliberately fetter devices, reversing the current trend of turning everything into a general-purpose computer. And, most important, we can move toward less centralization and more distributed systems, which is how the internet was first envisioned.

This might be a heresy in today’s race to network everything, but large, centralized systems are not inevitable. The technical elites are pushing us in that direction, but they really don’t have any good supporting arguments other than the profits of their ever-growing multinational corporations.

But this will change. It will change not only because of security concerns, it will also change because of political concerns. We’re starting to chafe under the worldview of everything producing data about us and what we do, and that data being available to both governments and corporations. Surveillance capitalism won’t be the business model of the internet forever. We need to change the fabric of the internet so that evil governments don’t have the tools to create a horrific totalitarian state. And while good laws and regulations in Western democracies are a great second line of defense, they can’t be our only line of defense.

My guess is that we will soon reach a high-water mark of computerization and connectivity, and that afterward we will make conscious decisions about what and how we decide to interconnect. But we’re still in the honeymoon phase of connectivity. Governments and corporations are punch-drunk on our data, and the rush to connect everything is driven by an even greater desire for power and market share. One of the presentations released by Edward Snowden contained the NSA mantra: “Collect it all.” A similar mantra for the internet today might be: “Connect it all.”

The inevitable backlash will not be driven by the market. It will be deliberate policy decisions that put the safety and welfare of society above individual corporations and industries. It will be deliberate policy decisions that prioritize the security of our systems over the demands of the FBI to weaken them in order to make their law-enforcement jobs easier. It’ll be hard policy for many to swallow, but our safety will depend on it.

**********

The scenarios I’ve outlined, both the technological and economic trends that are causing them and the political changes we need to make to start to fix them, come from my years of working in internet-security technology and policy. All of this is informed by an understanding of both technology and policy. That turns out to be critical, and there aren’t enough people who understand both.

This brings me to my final plea: We need more public-interest technologists.

Over the past couple of decades, we’ve seen examples of getting internet-security policy badly wrong. I’m thinking of the FBI’s “going dark” debate about its insistence that computer devices be designed to facilitate government access, the “vulnerability equities process” about when the government should disclose and fix a vulnerability versus when it should use it to attack other systems, the debacle over paperless touch-screen voting machines, and the DMCA that I discussed above. If you watched any of these policy debates unfold, you saw policy-makers and technologists talking past each other.

Our world-size robot will exacerbate these problems. The historical divide between Washington and Silicon Valley -­ the mistrust of governments by tech companies and the mistrust of tech companies by governments ­- is dangerous.

We have to fix this. Getting IoT security right depends on the two sides working together and, even more important, having people who are experts in each working on both. We need technologists to get involved in policy, and we need policy-makers to get involved in technology. We need people who are experts in making both technology and technological policy. We need technologists on congressional staffs, inside federal agencies, working for NGOs, and as part of the press. We need to create a viable career path for public-interest technologists, much as there already is one for public-interest attorneys. We need courses, and degree programs in colleges, for people interested in careers in public-interest technology. We need fellowships in organizations that need these people. We need technology companies to offer sabbaticals for technologists wanting to go down this path. We need an entire ecosystem that supports people bridging the gap between technology and law. We need a viable career path that ensures that even though people in this field won’t make as much as they would in a high-tech start-up, they will have viable careers. The security of our computerized and networked future ­ meaning the security of ourselves, families, homes, businesses, and communities ­ depends on it.

This plea is bigger than security, actually. Pretty much all of the major policy debates of this century will have a major technological component. Whether it’s weapons of mass destruction, robots drastically affecting employment, climate change, food safety, or the increasing ubiquity of ever-shrinking drones, understanding the policy means understanding the technology. Our society desperately needs technologists working on the policy. The alternative is bad policy.

**********

The world-size robot is less designed than created. It’s coming without any forethought or architecting or planning; most of us are completely unaware of what we’re building. In fact, I am not convinced we can actually design any of this. When we try to design complex sociotechnical systems like this, we are regularly surprised by their emergent properties. The best we can do is observe and channel these properties as best we can.

Market thinking sometimes makes us lose sight of the human choices and autonomy at stake. Before we get controlled ­ or killed ­ by the world-size robot, we need to rebuild confidence in our collective governance institutions. Law and policy may not seem as cool as digital tech, but they’re also places of critical innovation. They’re where we collectively bring about the world we want to live in.

While I might sound like a Cassandra, I’m actually optimistic about our future. Our society has tackled bigger problems than this one. It takes work and it’s not easy, but we eventually find our way clear to make the hard choices necessary to solve our real problems.

The world-size robot we’re building can only be managed responsibly if we start making real choices about the interconnected world we live in. Yes, we need security systems as robust as the threat landscape. But we also need laws that effectively regulate these dangerous technologies. And, more generally, we need to make moral, ethical, and political decisions on how those systems should work. Until now, we’ve largely left the internet alone. We gave programmers a special right to code cyberspace as they saw fit. This was okay because cyberspace was separate and relatively unimportant: That is, it didn’t matter. Now that that’s changed, we can no longer give programmers and the companies they work for this power. Those moral, ethical, and political decisions need, somehow, to be made by everybody. We need to link people with the same zeal that we are currently linking machines. “Connect it all” must be countered with “connect us all.”

This essay previously appeared in New York Magazine.

Classifying Elections as "Critical Infrastructure"

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/01/should_election.html

I am co-author on a paper discussing whether elections be classified as “critical infrastructure” in the US, based on experiences in other countries:

Abstract: With the Russian government hack of the Democratic National Convention email servers, and further leaks expected over the coming months that could influence an election, the drama of the 2016 U.S. presidential race highlights an important point: Nefarious hackers do not just pose a risk to vulnerable companies, cyber attacks can potentially impact the trajectory of democracies. Yet, to date, a consensus has not been reached as to the desirability and feasibility of reclassifying elections, in particular voting machines, as critical infrastructure due in part to the long history of local and state control of voting procedures. This Article takes on the debate in the U.S. using the 2016 elections as a case study but puts the issue in a global context with in-depth case studies from South Africa, Estonia, Brazil, Germany, and India. Governance best practices are analyzed by reviewing these differing approaches to securing elections, including the extent to which trend lines are converging or diverging. This investigation will, in turn, help inform ongoing minilateral efforts at cybersecurity norm building in the critical infrastructure context, which are considered here for the first time in the literature through the lens of polycentric governance.

The paper was speculative, but now it’s official. The U.S. election has been classified as critical infrastructure. I am tentatively in favor of this, but what really matter is what happens now. What does this mean? What sorts of increased security will election systems get? Will we finally get rid of computerized touch-screen voting?

EDITED TO ADD (1/16): This is a good article.

2016: The Year In Tech, And A Sneak Peek Of What’s To Come

Post Syndicated from Peter Cohen original https://www.backblaze.com/blog/2016-year-tech-sneak-peek-whats-come/

2016 is safely in our rear-view mirrors. It’s time to take a look back at the year that was and see what technology had the biggest impact on consumers and businesses alike. We also have an eye to 2017 to see what the future holds.

AI and machine learning in the cloud

Truly sentient computers and robots are still the stuff of science fiction (and the premise of one of 2016’s most promising new SF TV series, HBO’s Westworld). Neural networks are nothing new, but 2016 saw huge strides in artificial intelligence and machine learning, especially in the cloud.

Google, Amazon, Apple, IBM, Microsoft and others are developing cloud computing infrastructures designed especially for AI work. It’s this technology that’s underpinning advances in image recognition technology, pattern recognition in cybersecurity, speech recognition, natural language interpretation and other advances.

Microsoft’s newly-formed AI and Research Group is finding ways to get artificial intelligence into Microsoft products like its Bing search engine and Cortana natural language assistant. Some of these efforts, while well-meaning, still need refinement: Early in 2016 Microsoft launched Tay, an AI chatbot designed to mimic the natural language characteristics of a teenage girl and learn from interacting with Twitter users. Microsoft had to shut Tay down after Twitter users exploited vulnerabilities that caused Tay to begin spewing really inappropriate responses. But it paves the way for future efforts that blur the line between man and machine.

Finance, energy, climatology – anywhere you find big data sets you’re going to find uses for machine learning. On the consumer end it can help your grocery app guess what you might want or need based on your spending habits. Financial firms use machine learning to help predict customer credit scores by analyzing profile information. One of the most intriguing uses of machine learning is in security: Pattern recognition helps systems predict malicious intent and figure out where exploits will come from.

Meanwhile we’re still waiting for Rosie the Robot from the Jetsons. And flying cars. So if Elon Musk has any spare time in 2017, maybe he can get on that.

AR Games

Augmented Reality (AR) games have been around for a good long time – ever since smartphone makers put cameras on them, game makers have been toying with the mix of real life and games.

AR games took a giant step forward with a game released in 2016 that you couldn’t get away from, at least for a little while. We’re talking about Pokémon GO, of course. Niantic, makers of another AR game called Ingress, used the framework they built for that game to power Pokémon GO. Kids, parents, young, old, it seemed like everyone with an iPhone that could run the game caught wild Pokémon, hatched eggs by walking, and battled each other in Pokémon gyms.

For a few weeks, anyway.

Technical glitches, problems with scale and limited gameplay value ultimately hurt Pokémon GO’s longevity. Today the game only garners a fraction of the public interest it did at peak. It continues to be successful, albeit not at the stratospheric pace it first set.

Niantic, the game’s developer, was able to tie together several factors to bring such an explosive and – if you’ll pardon the overused euphemism – disruptive – game to bear. One was its previous work with a game called Ingress, another AR-enhanced game that uses geomap data. In fact, Pokémon GO uses the same geomap data as Ingress, so Niantic had already done a huge amount of legwork needed to get Pokémon GO up and running. Niantic cleverly used Google Maps data to form the basis of both games, relying on already-identified public landmarks and other locations tagged by Ingress players (Ingress has been around since 2011).

Then, of course, there’s the Pokémon connection – an intensely meaningful gaming property that’s been popular with generations of video games and cartoon watchers since the 1990s. The dearth of Pokémon-branded games on smartphones meant an instant explosion of popularity upon Pokémon GO’s release.

2016 also saw the introduction of several new virtual reality (VR) headsets designed for home and mobile use. Samsung Gear VR and Google Daydream View made a splash. As these products continue to make consumer inroads, we’ll see more games push the envelope of what you can achieve with VR and AR.

Hybrid Cloud

Hybrid Cloud services combine public cloud storage (like B2 Cloud Storage) or public compute (like Amazon Web Services) with a private cloud platform. Specialized content and file management software glues it all together, making the experience seamless for the user.

Businesses get the instant access and speed they need to get work done, with the ability to fall back on on-demand cloud-based resources when scale is needed. B2’s hybrid cloud integrations include OpenIO, which helps businesses maintain data storage on-premise until it’s designated for archive and stored in the B2 cloud.

The cost of entry and usage of Hybrid Cloud services have continued to fall. For example, small and medium-sized organizations in the post production industry are finding Hybrid Cloud storage is now a viable strategy in managing the large amounts of information they use on a daily basis. This strategy is enabled by the low cost of B2 Cloud Storage that provides ready access to cloud-stored data.

There are practical deployment and scale issues that have kept Hybrid Cloud services from being used widespread in the largest enterprise environments. Small to medium businesses and vertical markets like Media & Entertainment have found promising, economical opportunities to use it, which bodes well for the future.

Inexpensive 3D printers

3D printing, once a rarified technology, has become increasingly commoditized over the past several years. That’s been in part thanks to the “Maker Movement:” Thousands of folks all around the world who love to tinker and build. XYZprinting is out in front of makers and others with its line of inexpensive desktop da Vinci printers.

The da Vinci Mini is a tabletop model aimed at home users which starts at under $300. You can download and tweak thousands of 3D models to build toys, games, art projects and educational items. They’re built using spools of biodegradable, non-toxic plastics derived from corn starch which dispense sort of like the bobbin on a sewing machine. The da Vinci Mini works with Macs and PCs and can connect via USB or Wi-Fi.

DIY Drones

Quadcopter drones have been fun tech toys for a while now, but the new trend we saw in 2016 was “do it yourself” models. The result was Flybrix, which combines lightweight drone motors with LEGO building toys. Flybrix was so successful that they blew out of inventory for the 2016 holiday season and are backlogged with orders into the new year.

Each Flybrix kit comes with the motors, LEGO building blocks, cables and gear you need to build your own quad, hex or octocopter drone (as well as a cheerful-looking LEGO pilot to command the new vessel). A downloadable app for iOS or Android lets you control your creation. A deluxe kit includes a handheld controller so you don’t have to tie up your phone.

If you already own a 3D printer like the da Vinci Mini, you’ll find plenty of model files available for download and modification so you can print your own parts, though you’ll probably need help from one of the many maker sites to know what else you’ll need to aerial flight and control.

5D Glass Storage

Research at the University of Southampton may yield the next big leap in optical storage technology meant for long-term archival. The boffins at the Optoelectronics Research Centre have developed a new data storage technique that embeds information in glass “nanostructures” on a storage disc the size of a U.S. quarter.

A Blu-Ray Disc can hold 50 GB, but one of the new 5D glass storage discs – only the size of a U.S. quarter – can hold 360 TB – 7200 times more. It’s like a super-stable supercharged version of a CD. Not only is the data inscribed on much smaller structures within the glass, but reflected at multiple angles, hence “5D.”

An upside to this is an absence of bit rot: The glass medium is extremely stable, with a shelf life predicted in billions of years. The downside is that this is still a write-once medium, so it’s intended for long term storage.

This tech is still years away from practical use, but it took a big step forward in 2016 when the University announced the development of a practical information encoding scheme to use with it.

Smart Home Tech

Are you ready to talk to your house to tell it to do things? If you’re not already, you probably will be soon. Google’s Google Home is a $129 voice-activated speaker powered by the Google Assistant. You can use it for everything from streaming music and video to a nearby TV to reading your calendar or to do list. You can also tell it to operate other supported devices like the Nest smart thermostat and Philips Hue lights.

Amazon has its own similar wireless speaker product called the Echo, powered by Amazon’s Alexa information assistant. Amazon has differentiated its Echo offerings by making the Dot – a hockey puck-sized device that connects to a speaker you already own. So Amazon customers can begin to outfit their connected homes for less than $50.

Apple’s HomeKit software kit isn’t a speaker like Amazon Echo or Google Home. It’s software. You use the Home app on your iOS 10-equipped iPhone or iPad to connect and configure supported devices. Use Siri, Apple’s own intelligent assistant, on any supported Apple device. HomeKit turns on lights, turns up the thermostat, operates switches and more.

Smart home tech has been coming in fits and starts for a while – the Nest smart thermostat is already in its third generation, for example. But 2016 was the year we finally saw the “Internet of things” coalescing into a smart home that we can control through voice and gestures in a … well, smart way.

Welcome To The Future

It’s 2017, welcome to our brave new world. While it’s anyone’s guess what the future holds, there are at least a few tech trends that are pretty safe to bet on. They include:

  • Internet of Things: More smart-connected devices are coming online in the home and at work every day, and this trend will accelerate in 2017 with more and more devices requiring some form of Internet connectivity to work. Expect to see a lot more appliances, devices, and accessories that make use of the API’s promoted by Google, Amazon, and Apple to help let you control everything in your life just using your voice and a smart speaker setup.
  • Blockchain security: Blockchain is the digital ledger security technology that makes Bitcoin work. Its distribution methodology and validation system help you make certain that no one’s tampered with the records, which make it well-suited for applications besides cryptocurrency, like make sure your smart thermostat (see above) hasn’t been hacked). Expect 2017 to be the year we see more mainstream acceptance, use, and development of blockchain technology from financial institutions, the creation of new private blockchain networks, and improved usability aimed at making blockchain easier for regular consumers to use. Blockchain-based voting is here too. It also wouldn’t surprise us, given all this movement, to see government regulators take a much deeper interest in blockchain, either.
  • 5G: Verizon is field-testing 5G on its wireless network, which it says deliver speeds 30-50 times faster than 4G LTE. We’ll be hearing a lot more about 5G from Verizon and other wireless players in 2017. In fairness, we’re still a few years away from widescale 5G deployment, but field-testing has already started.

Your Predictions?

Enough of our bloviation. Let’s open the floor to you. What do you think were the biggest technology trends in 2016? What’s coming in 2017 that has you the most excited? Let us know in the comments!

The post 2016: The Year In Tech, And A Sneak Peek Of What’s To Come appeared first on Backblaze Blog | Cloud Storage & Cloud Backup.

Class Breaks

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/01/class_breaks.html

There’s a concept from computer security known as a class break. It’s a particular security vulnerability that breaks not just one system, but an entire class of systems. Examples might be a vulnerability in a particular operating system that allows an attacker to take remote control of every computer that runs on that system’s software. Or a vulnerability in Internet-enabled digital video recorders and webcams that allow an attacker to recruit those devices into a massive botnet.

It’s a particular way computer systems can fail, exacerbated by the characteristics of computers and software. It only takes one smart person to figure out how to attack the system. Once he does that, he can write software that automates his attack. He can do it over the Internet, so he doesn’t have to be near his victim. He can automate his attack so it works while he sleeps. And then he can pass the ability to someone­ — or to lots of people — ­without the skill. This changes the nature of security failures, and completely upends how we need to defend against them.

An example: Picking a mechanical door lock requires both skill and time. Each lock is a new job, and success at one lock doesn’t guarantee success with another of the same design. Electronic door locks, like the ones you now find in hotel rooms, have different vulnerabilities. An attacker can find a flaw in the design that allows him to create a key card that opens every door. If he publishes his attack software, not just the attacker, but anyone can now open every lock. And if those locks are connected to the Internet, attackers could potentially open door locks remotely — ­they could open every door lock remotely at the same time. That’s a class break.

It’s how computer systems fail, but it’s not how we think about failures. We still think about automobile security in terms of individual car thieves manually stealing cars. We don’t think of hackers remotely taking control of cars over the Internet. Or, remotely disabling every car over the Internet. We think about voting fraud as unauthorized individuals trying to vote. We don’t think about a single person or organization remotely manipulating thousands of Internet-connected voting machines.

In a sense, class breaks are not a new concept in risk management. It’s the difference between home burglaries and fires, which happen occasionally to different houses in a neighborhood over the course of the year, and floods and earthquakes, which either happen to everyone in the neighborhood or no one. Insurance companies can handle both types of risk, but they are inherently different. The increasing computerization of everything is moving us from a burglary/fire risk model to a flood/earthquake model, which a given threat either affects everyone in town or doesn’t happen at all.

But there’s a key difference between floods/earthquakes and class breaks in computer systems: the former are random natural phenomena, while the latter is human-directed. Floods don’t change their behavior to maximize their damage based on the types of defenses we build. Attackers do that to computer systems. Attackers examine our systems, looking for class breaks. And once one of them finds one, they’ll exploit it again and again until the vulnerability is fixed.

As we move into the world of the Internet of Things, where computers permeate our lives at every level, class breaks will become increasingly important. The combination of automation and action at a distance will give attackers more power and leverage than they have ever had before. Security notions like the precautionary principle­ — where the potential of harm is so great that we err on the side of not deploying a new technology without proofs of security — will become more important in a world where an attacker can open all of the door locks or hack all of the power plants. It’s not an inherently less secure world, but it’s a differently secure world. It’s a world where driverless cars are much safer than people-driven cars, until suddenly they’re not. We need to build systems that assume the possibility of class breaks — and maintain security despite them.

This essay originally appeared on Edge.org as part of their annual question. This year it was: “What scientific term or concept ought to be more widely known?

My Priorities for the Next Four Years

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2016/12/my_priorities_f.html

Like many, I was surprised and shocked by the election of Donald Trump as president. I believe his ideas, temperament, and inexperience represent a grave threat to our country and world. Suddenly, all the things I had planned to work on seemed trivial in comparison. Although Internet security and privacy are not the most important policy areas at risk, I believe he — and, more importantly, his cabinet, administration, and Congress — will have devastating effects in that area, both in the US and around the world.

The election was so close that I’ve come to see the result as a bad roll of the dice. A few minor tweaks here and there — a more enthusiastic Sanders endorsement, one fewer of Comey’s announcements, slightly less Russian involvement — and the country would be preparing for a Clinton presidency and discussing a very different social narrative. That alternative narrative would stress business as usual, and continue to obscure the deep social problems in our society. Those problems won’t go away on their own, and in this alternative future they would continue to fester under the surface, getting steadily worse. This election exposed those problems for everyone to see.

I spent the last month both coming to terms with this reality, and thinking about the future. Here is my new agenda for the next four years:

One, fight the fights. There will be more government surveillance and more corporate surveillance. I expect legislative and judicial battles along several lines: a renewed call from the FBI for backdoors into encryption, more leeway for government hacking without a warrant, no controls on corporate surveillance, and more secret government demands for that corporate data. I expect other countries to follow our lead. (The UK is already more extreme than us.) And if there’s a major terrorist attack under Trump’s watch, it’ll be open season on our liberties. We may lose a lot of these battles, but we need to lose as few as possible and as little of our existing liberties as possible.

Two, prepare for those fights. Much of the next four years will be reactive, but we can prepare somewhat. The more we can convince corporate America to delete their saved archives of surveillance data and to store only what they need for as long as they need it, the safer we’ll all be. We need to convince Internet giants like Google and Facebook to change their business models away from surveillance capitalism. It’s a hard sell, but maybe we can nibble around the edges. Similarly, we need to keep pushing the truism that privacy and security are not antagonistic, but rather are essential for each other.

Three, lay the groundwork for a better future. No matter how bad the next four years get, I don’t believe that a Trump administration will permanently end privacy, freedom, and liberty in the US. I don’t believe that it portends a radical change in our democracy. (Or if it does, we have bigger problems than a free and secure Internet.) It’s true that some of Trump’s institutional changes might take decades to undo. Even so, I am confident — optimistic even — that the US will eventually come around; and when that time comes, we need good ideas in place for people to come around to. This means proposals for non-surveillance-based Internet business models, research into effective law enforcement that preserves privacy, intelligent limits on how corporations can collect and exploit our data, and so on.

And four, continue to solve the actual problems. The serious security issues around cybercrime, cyber-espionage, cyberwar, the Internet of Things, algorithmic decision making, foreign interference in our elections, and so on aren’t going to disappear for four years while we’re busy fighting the excesses of Trump. We need to continue to work towards a more secure digital future. And to the extent that cybersecurity for our military networks and critical infrastructure allies with cybersecurity for everyone, we’ll probably have an ally in Trump.

Those are my four areas. Under a Clinton administration, my list would have looked much the same. Trump’s election just means the threats will be much greater, and the battles a lot harder to win. It’s more than I can possibly do on my own, and I am therefore substantially increasing my annual philanthropy to support organizations like EPIC, EFF, ACLU, and Access Now in continuing their work in these areas.

My agenda is necessarily focused entirely on my particular areas of concern. The risks of a Trump presidency are far more pernicious, but this is where I have expertise and influence.

Right now, we have a defeated majority. Many are scared, and many are motivated — and few of those are applying their motivation constructively. We need to harness that fear and energy to start fixing our society now, instead of waiting four or even eight years, at which point the problems would be worse and the solutions more extreme. I am choosing to proceed as if this were cowpox, not smallpox: fighting the more benign disease today will be much easier than subjecting ourselves to its more virulent form in the future. It’s going to be hard keeping the intensity up for the next four years, but we need to get to work. Let’s use Trump’s victory as the wake-up call and opportunity that it is.

Some notes on a Hamilton election

Post Syndicated from Robert Graham original http://blog.erratasec.com/2016/12/some-notes-on-hamilton-election.html

At least one elector for Trump has promised to switch his vote, becoming a “Hamilton Elector”. Assuming 36 more electors (about 10% of Trump’s total) do likewise, and Trump fails to get the 270 absolute majority, then what happens? Since all of the constitutional law scholars I follow haven’t taken a stab at this, I thought I would write up some notes.

Foreign powers and populists

In Federalist #68, Alexander Hamilton laid out the reasons why electors should switch their vote. The founders feared bad candidates unduly influenced by foreign powers, and demagogues. Trump is unabashedly both. He criticizes our own CIA claiming what every American knows, that Russia interfered in our election. Trump is the worst sort of populist demagogue, offering no solution to problems other than he’ll be a strong leader.

Therefore, electors have good reasons to change their votes. I’m not suggesting they should, only that doing so is consistent with our Constitutional principles and history.

So if 10% of Trump’s electors defect, how would this actually work?

Failure to get 270 vote absolute majority (math)

Well, to start with, let’s count up the number of electors. Each state gets one elector for every House Representative and each Senator. Since there are 435 members of the House and 100 members of the Senate, that comes out to 535. However, the 23rd Amendment adds three more electors for Washington D.C. (so they can vote in the Presidential election but not Congress). So that means the there are 538 total electors.

According to the Constitution, the winner must get an absolute majority, meaning over 50% of the electoral votes cast. Half of 538 is 269, plus one to get more than half to get majority, equals 270. Thus, Trump must get at least 270 electoral votes. If he gets only 269, the election fails.

Trump won 306 electors in the election. To get below 270, then 37 electors must switch their votes, which is a little over 10%.

Electors are free to change their votes

Constitutionally, the electors are free to change their votes. However, for most, it would destroy their political careers. Most are state party people who have spent years building up power and reputation in their respective states. Violating their word would destroy all that — nobody would trust them again. They would certainly never be chosen as an elector again, of course.

Many states have laws against electors changing their votes. It is widely accepted that these laws are unconstitutional and would be struck down the courts, but in the meanwhile, some vote flippers would have to spend considerable time and money defending themselves from the legal punishment.

Electors vote December 19

We’ve only got until December 19th [*] for electors to change their minds. That’s the date they vote. The votes are collected in their various states, then sent to Washington.

Electoral votes counted January 6

Ballots are theoretically sealed until January 6, when the votes are unsealed and counted in front of Congress.

A 26 state majority of House delegations

If the elector college fails to get an absolute majority of 270 votes, then the election is thrown into the House of Representatives. But it’s not a straight up vote among all 435 members of the House. Instead, there are 50 votes — one for each state delegation. Again, the winner must get an absolute majority to win, meaning 26 votes.

This will be the newly elected House of Representatives, which will have been sworn in on January 3, three days earlier. They are instructed to immediately vote, right after the counting of electoral votes fails to deliver a result.

This is where things get a little weird, because the state “delegation”, all the house members from a state, must decide on the vote for their state. The vote is determined by the majority of representatives from each state.

In the outgoing Congress, the Republicans have the most Representatives in the House, with 247 members to the Democrats 188 members. But the question is how many delegations they have, which can be completely different. It’s plausible to have the majority of Representatives and a minority of state delegations. As it turns out, Republicans do have the majority of state delegations, by a 2 to 1 margin, 32 to 16 (with 2 states a tie). These are the old numbers I find on Wikipedia [*], but the next Congress will have substantially the same makeup. Update: According it @KDbyproxy, the incoming congress numbers are 32-17-1, but I haven’t verified the numbers myself.

So, if the electoral college can’t make a decision, then the Republicans will have a 2 to 1 majority in the House, and could easily elect Trump. However, in this case there’s no expectation that they would vote for Trump. While Republicans certainly wouldn’t vote for Hillary, they could vote for a third candidate.

According to the Constitution, the Representatives will vote for the the top 3 recipients of electoral votes, meaning Trump, Hillary, and whoever got the most votes among the “Hamilton electors”.

Here’s where a bunch of Hillary electors are threatening to defect. They are proposing to vote in a bloc for John Kasich instead, the most moderate of the viable Republican candidates (Kasich was #4 in the 2016 Republican primary).

This will give the House a choice between Trump, Hillary, and Kasich. Presumably, all the Democrats would then vote for Kasich, giving him 16 of the needed 26 votes immediately. Then, the Democrats would need to swing another 10 state delegations to Kasich’s side. Since in many state delegations, Republicans hold only a slim majority, and only a few individuals would need to swing their votes, this is not so large a hurdle. Since there’s a good chance many Republicans will prefer Kasich over Trump anyway, this seems a likely outcome. After all, Trump didn’t even win the popular vote in the main election (just the electoral vote), so there’s no “mandate” or anything that says they must vote for Trump.

According to the rules, the House must vote immediately after the electoral count fails to produce a winner. That doesn’t give much time for them to scramble for votes. In practice, we’ll probably know on December 19th how the vote went, in which case they’ll have plenty of time to know what’s coming and to horse trade for votes ahead of time.

If House fails, new VP becomes acting President

What happens if the House doesn’t give any candidate 26 votes? In that case, whoever was elected as the new Vice President will become the acting President.

That means Mike Pence, Trump’s running mate, who won 306 electoral votes for VP. However, the same deal can apply, with 37 electors defecting and voting for a different VP. Instead of going to the house, the vote now goes to the Senate for the top two candidates. Since the top two will certainly be Tim Kaine (Hillary’s running mate) and Mike Pence, and the Senate is solidly Republican, that again means Pence would be elected VP, and hence, become Acting President in case the House fails to vote on a candidate.

Conclusion

One elector, Christopher Suprun, has promised to be a “Hamilton Elector” and not vote for Trump. If 36 more electors do the same, then there’s a good chance Trump won’t become president. The winner won’t be Hillary, but some other Republican, at least Pence, and maybe John Kasich. Kasich has come out publicly and told electors not to vote for him [*], but we’ll see what happens.

36 more electors is a long shot, but then, Trump winning was considered a long shot in the first place. Moreover, Trump has been acting so badly since the election that he’s giving electors good reason to switch their votes. You’d think that as a reasonable person, he’d at least stop tweeting until December 19th.

So here’s the timeline:

  • December 19: electors vote, 37 needed to defect from Trump
  • January 3: new congress sworn in
  • January 6: electoral votes counted, House conducts first vote
  • January 20: President or Acting President (new VP) sworn in

Update: Previous version said the House had until March to decide. This was a clause from the 12th Amendment that apparently was superceded by the 20th. See! This is why constitutional scholars need to do this work, not hackers!!