Tag Archives: drones

Another Attack Against Driverless Cars

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/07/another_attack_.html

In this piece of research, attackers successfully attack a driverless car system — Renault Captur’s “Level 0” autopilot (Level 0 systems advise human drivers but do not directly operate cars) — by following them with drones that project images of fake road signs in 100ms bursts. The time is too short for human perception, but long enough to fool the autopilot’s sensors.

Boing Boing post.

Drone Denial-of-Service Attack against Gatwick Airport

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/12/drone_denial-of.html

Someone is flying a drone over Gatwick Airport in order to disrupt service:

Chris Woodroofe, Gatwick’s chief operating officer, said on Thursday afternoon there had been another drone sighting which meant it was impossible to say when the airport would reopen.

He told BBC News: “There are 110,000 passengers due to fly today, and the vast majority of those will see cancellations and disruption. We have had within the last hour another drone sighting so at this stage we are not open and I cannot tell you what time we will open.

“It was on the airport, seen by the police and corroborated. So having seen that drone that close to the runway it was unsafe to reopen.”

The economics of this kind of thing isn’t in our favor. A drone is cheap. Closing an airport for a day is very expensive.

I don’t think we’re going to solve this by jammers, or GPS-enabled drones that won’t fly over restricted areas. I’ve seen some technologies that will safely disable drones in flight, but I’m not optimistic about those in the near term. The best defense is probably punitive penalties for anyone doing something like this — enough to discourage others.

There are a lot of similar security situations, in which the cost to attack is vastly cheaper than 1) the damage caused by the attack, and 2) the cost to defend. I have long believed that this sort of thing represents an existential threat to our society.

EDITED TO ADD (12/23): The airport has deployed some ant-drone technology and reopened.

Autonomous drones (only slightly flammable)

Post Syndicated from Liz Upton original https://www.raspberrypi.org/blog/autonomous-drones-only-slightly-flammable/

I had an email a little while ago, which opened: “I don’t know if you remember me, but…”

As it happens, I remembered Andy Baker very well, in large part because an indoor autonomous drone demo he ran at a Raspberry Pi birthday party a couple of years ago ACTUALLY CAUGHT FIRE. Here’s a refresher.

Raspberry Pi Party Autonomous drone demo + fire

At the Raspberry Pi IV party and there is a great demo of an Autonomous drone which is very impressive with only using a Pi. However it caught on fire. But i believe it does actually work.

We’ve been very careful since then to make sure that speakers are always accompanied by a fire extinguisher.

I love stories like Andy’s. He started working with the Raspberry Pi shortly after our first release in 2012, and had absolutely no experience with drones or programming them; there’s nothing more interesting than watching someone go from a standing start to something really impressive. It’s been a couple of years since we were last in touch, but Andy mailed me last week to let me know he’s just completed his piDrone project, after years of development. I thought you’d like to hear about it too. Over to Andy!

Building an autonomous drone from scratch

I suffer from “terminal boredom syndrome”; I always need a challenging hobby to keep me sane. In 2012, the Raspberry Pi was launched just as my previous hobby had come to an end. After six months of playing (including a Raspberry Pi version of a BBC Micro Turtle robot I did at school 30+ years ago), I was looking for something really challenging. DIY drones were emerging, so I set out making one with a Raspberry Pi and Python, from absolute ignorance but loads of motivation.  Six years later, with only one fire (at the Raspberry Pi 4th Birthday Party, no less!), the job is done.

Here’s smaller Zoë, larger Hermione and their remote-controller, Ivy:

Zoë (as in “Ball”), the smallest drone, is based on a Pi ZeroW, supporting preset- and manual-flight controls. Hermione (as in “Granger”) is a Pi3 drone, supporting the above along with GPS and obstacle-avoidance.

Penelope (as in “Pitstop”), not shown above, is a B3+ with mix of the two above.

Development history

It probably took four years(!) to get the drone to simply hover stably for more than a few seconds. For example, the accelerometer (IMU) tells gravity and acceleration in 3D; and from sum math(s), angles, speed and distance. But IMU output is very noisy. It drifts with temperature, and because gravity is huge compared to the propeller changes, it doesn’t take long before the calculated speed and distance values drift significantly. It took a lot of time, experimentation and guesswork to get accelerometer, gyrometer, ground-facing LiDAR and a Raspberry Pi camera to work together to get a stable hover for minutes rather than seconds. And during that experimentation, there were plenty of crashes: replacement parts were needed many many times! However, with a sixty-second stable hover finally working, adding cool features like GPS tracking, object avoidance and human control were trivial in comparison.

GNSS waypoint tracked successfully!

See http://blog.pistuffing.co.uk/whoohoo/

Obstruction avoidance test 2 – PASSED!!!!!

Details at http://pidrone.io/posts/obstruction-avoidance-test-2-passed/

Human control (iPhone)

See http://pidrone.io/posts/human-i-am-human/

In passing, I’m a co-founder and assistant at the Cotswold Raspberry Jam (cotswoldjam.org). I’m hoping to take Zoë to the next event on September 15th – tickets are free – and there’s so much more learn, interact and play with beyond the piDrone.

Finally, a few years ago, my goal became getting the piDrone exploring a maze: all but minor tweaks are now in places. Sadly, piDrone battery power for exploring a large maze currently doesn’t exist. Perhaps my next project will be designing a nuclear-fusion battery pack?  Deuterium oxide (heavy water) is surprisingly cheap, it seems…

More resources

If you want to learn more, there’s years of development on Andy’s blog at http://pidrone.io, and he’s made considerable documentation available at GitHub if you want to explore things further after this blog post. Thanks Andy!

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New – Machine Learning Inference at the Edge Using AWS Greengrass

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/new-machine-learning-inference-at-the-edge-using-aws-greengrass/

What happens when you combine the Internet of Things, Machine Learning, and Edge Computing? Before I tell you, let’s review each one and discuss what AWS has to offer.

Internet of Things (IoT) – Devices that connect the physical world and the digital one. The devices, often equipped with one or more types of sensors, can be found in factories, vehicles, mines, fields, homes, and so forth. Important AWS services include AWS IoT Core, AWS IoT Analytics, AWS IoT Device Management, and Amazon FreeRTOS, along with others that you can find on the AWS IoT page.

Machine Learning (ML) – Systems that can be trained using an at-scale dataset and statistical algorithms, and used to make inferences from fresh data. At Amazon we use machine learning to drive the recommendations that you see when you shop, to optimize the paths in our fulfillment centers, fly drones, and much more. We support leading open source machine learning frameworks such as TensorFlow and MXNet, and make ML accessible and easy to use through Amazon SageMaker. We also provide Amazon Rekognition for images and for video, Amazon Lex for chatbots, and a wide array of language services for text analysis, translation, speech recognition, and text to speech.

Edge Computing – The power to have compute resources and decision-making capabilities in disparate locations, often with intermittent or no connectivity to the cloud. AWS Greengrass builds on AWS IoT, giving you the ability to run Lambda functions and keep device state in sync even when not connected to the Internet.

ML Inference at the Edge
Today I would like to toss all three of these important new technologies into a blender! You can now perform Machine Learning inference at the edge using AWS Greengrass. This allows you to use the power of the AWS cloud (including fast, powerful instances equipped with GPUs) to build, train, and test your ML models before deploying them to small, low-powered, intermittently-connected IoT devices running in those factories, vehicles, mines, fields, and homes that I mentioned.

Here are a few of the many ways that you can put Greengrass ML Inference to use:

Precision Farming – With an ever-growing world population and unpredictable weather that can affect crop yields, the opportunity to use technology to increase yields is immense. Intelligent devices that are literally in the field can process images of soil, plants, pests, and crops, taking local corrective action and sending status reports to the cloud.

Physical Security – Smart devices (including the AWS DeepLens) can process images and scenes locally, looking for objects, watching for changes, and even detecting faces. When something of interest or concern arises, the device can pass the image or the video to the cloud and use Amazon Rekognition to take a closer look.

Industrial Maintenance – Smart, local monitoring can increase operational efficiency and reduce unplanned downtime. The monitors can run inference operations on power consumption, noise levels, and vibration to flag anomalies, predict failures, detect faulty equipment.

Greengrass ML Inference Overview
There are several different aspects to this new AWS feature. Let’s take a look at each one:

Machine Learning ModelsPrecompiled TensorFlow and MXNet libraries, optimized for production use on the NVIDIA Jetson TX2 and Intel Atom devices, and development use on 32-bit Raspberry Pi devices. The optimized libraries can take advantage of GPU and FPGA hardware accelerators at the edge in order to provide fast, local inferences.

Model Building and Training – The ability to use Amazon SageMaker and other cloud-based ML tools to build, train, and test your models before deploying them to your IoT devices. To learn more about SageMaker, read Amazon SageMaker – Accelerated Machine Learning.

Model Deployment – SageMaker models can (if you give them the proper IAM permissions) be referenced directly from your Greengrass groups. You can also make use of models stored in S3 buckets. You can add a new machine learning resource to a group with a couple of clicks:

These new features are available now and you can start using them today! To learn more read Perform Machine Learning Inference.

Jeff;

 

HackSpace magazine 3: Scrap Heap Hacking

Post Syndicated from Andrew Gregory original https://www.raspberrypi.org/blog/hackspace-magazine-3-scrap-heap-hacking/

We’re making with a purpose in issue 3 of HackSpace magazine. Not only are we discovering ways in which 3D printing is helping to save resources — and in some case lives — in the developing world, we’re also going all out with recycling. While others might be content with separating their glass and plastic waste, we’re going much, much further by making useful things out of discarded old bits of rubbish you can find at your local scrapyard.

Hackspaces

We’re going to Cheltenham Hackspace to learn how to make a leather belt, to Liverpool to discover the ways in which an open-source design and some bits and bobs from IKEA are protecting our food supply, and we also take a peek through the doors of Nottingham Hackspace.

Tutorials

The new issue also has the most tutorials you’ll have seen anywhere since…well, since HackSpace magazine issue 2! Guides to 3D-printing on fabric, Arduino programming, and ESP8266 hacking are all to be found in issue 3. Plus, we’ve come up with yet another way to pipe numbers from the internet into big, red, glowing boxes — it’s what LEDs were made for.



With the addition of racing drones, an angry reindeer, and an intelligent toaster, we think we’ve definitely put together an issue you’ll enjoy.

Get your copy

The physical copy of HackSpace magazine is available at all good UK newsagents today, and you can order it online from the Raspberry Pi Press store wherever you are based. Moreover, you can download the free PDF version from our website. And if you’ve read our first two issues and enjoyed what you’ve seen, be sure to subscribe!

Write for us

Are you working on a cool project? Do you want to share your skills with the world, inspire others, and maybe show off a little? HackSpace magazine wants your article! Send an outline of your piece to us, and we’ll get back to you about including it in a future issue.

The post HackSpace magazine 3: Scrap Heap Hacking appeared first on Raspberry Pi.

Detecting Drone Surveillance with Traffic Analysis

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/01/detecting_drone.html

This is clever:

Researchers at Ben Gurion University in Beer Sheva, Israel have built a proof-of-concept system for counter-surveillance against spy drones that demonstrates a clever, if not exactly simple, way to determine whether a certain person or object is under aerial surveillance. They first generate a recognizable pattern on whatever subject­ — a window, say — someone might want to guard from potential surveillance. Then they remotely intercept a drone’s radio signals to look for that pattern in the streaming video the drone sends back to its operator. If they spot it, they can determine that the drone is looking at their subject.

In other words, they can see what the drone sees, pulling out their recognizable pattern from the radio signal, even without breaking the drone’s encrypted video.

The details have to do with the way drone video is compressed:

The researchers’ technique takes advantage of an efficiency feature streaming video has used for years, known as “delta frames.” Instead of encoding video as a series of raw images, it’s compressed into a series of changes from the previous image in the video. That means when a streaming video shows a still object, it transmits fewer bytes of data than when it shows one that moves or changes color.

That compression feature can reveal key information about the content of the video to someone who’s intercepting the streaming data, security researchers have shown in recent research, even when the data is encrypted.

Research paper and video.

Hello World Issue 4: Professional Development

Post Syndicated from Carrie Anne Philbin original https://www.raspberrypi.org/blog/hello-world-issue-4/

Another new year brings with it thoughts of setting goals and targets. Thankfully, there is a new issue of Hello World packed with practical advise to set you on the road to success.

Hello World is our magazine about computing and digital making for educators, and it’s a collaboration between the Raspberry Pi Foundation and Computing at School, which is part of the British Computing Society.

Hello World 4 Professional Development Raspberry Pi CAS

In issue 4, our international panel of educators and experts recommends approaches to continuing professional development in computer science education.

Approaches to professional development, and much more

With recommendations for more professional development in the Royal Society’s report, and government funding to support this, our cover feature explores some successful approaches. In addition, the issue is packed with other great resources, guides, features, and lesson plans to support educators.

Hello World 4 Professional Development Raspberry Pi CAS
Hello World 4 Professional Development Raspberry Pi CAS
Hello World 4 Professional Development Raspberry Pi CAS
Hello World 4 Professional Development Raspberry Pi CAS

Highlights include:

  • The Royal Society: After the Reboot — learn about the latest report and its findings about computing education
  • The Cyber Games — a new programme looking for the next generation of security experts
  • Engaging Students with Drones
  • Digital Literacy: Lost in Translation?
  • Object-oriented Coding with Python

Get your copy of Hello World 4

Hello World is available as a free Creative Commons download for anyone around the world who is interested in computer science and digital making education. You can get the latest issue as a PDF file straight from the Hello World website.

Thanks to the very generous sponsorship of BT, we are able to offer free print copies of the magazine to serving educators in the UK. It’s for teachers, Code Club volunteers, teaching assistants, teacher trainers, and others who help children and young people learn about computing and digital making. So remember to subscribe to have your free print magazine posted directly to your home — 6000 educators have already signed up to receive theirs!

Could you write for Hello World?

By sharing your knowledge and experience of working with young people to learn about computing, computer science, and digital making in Hello World, you will help inspire others to get involved. You will also help bring the power of digital making to more and more educators and learners.

The computing education community is full of people who lend their experience to help colleagues. Contributing to Hello World is a great way to take an active part in this supportive community, and you’ll be adding to a body of free, open-source learning resources that are available for anyone to use, adapt, and share. It’s also a tremendous platform to broadcast your work: Hello World digital versions alone have been downloaded more than 50000 times!

Wherever you are in the world, get in touch with us by emailing our editorial team about your article idea.

The post Hello World Issue 4: Professional Development appeared first on Raspberry Pi.

Is blockchain a security topic? (Opensource.com)

Post Syndicated from jake original https://lwn.net/Articles/740929/rss

At Opensource.com, Mike Bursell looks at blockchain security from the angle of trust. Unlike cryptocurrencies, which are pseudonymous typically, other kinds of blockchains will require mapping users to real-life identities; that raises the trust issue.

What’s really interesting is that, if you’re thinking about moving to a permissioned blockchain or distributed ledger with permissioned actors, then you’re going to have to spend some time thinking about trust. You’re unlikely to be using a proof-of-work system for making blocks—there’s little point in a permissioned system—so who decides what comprises a “valid” block that the rest of the system should agree on? Well, you can rotate around some (or all) of the entities, or you can have a random choice, or you can elect a small number of über-trusted entities. Combinations of these schemes may also work.

If these entities all exist within one trust domain, which you control, then fine, but what if they’re distributors, or customers, or partners, or other banks, or manufacturers, or semi-autonomous drones, or vehicles in a commercial fleet? You really need to ensure that the trust relationships that you’re encoding into your implementation/deployment truly reflect the legal and IRL [in real life] trust relationships that you have with the entities that are being represented in your system.

And the problem is that, once you’ve deployed that system, it’s likely to be very difficult to backtrack, adjust, or reset the trust relationships that you’ve designed.”

NSA "Red Disk" Data Leak

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/11/nsa_red_disk_da.html

ZDNet is reporting about another data leak, this one from US Army’s Intelligence and Security Command (INSCOM), which is also within to the NSA.

The disk image, when unpacked and loaded, is a snapshot of a hard drive dating back to May 2013 from a Linux-based server that forms part of a cloud-based intelligence sharing system, known as Red Disk. The project, developed by INSCOM’s Futures Directorate, was slated to complement the Army’s so-called distributed common ground system (DCGS), a legacy platform for processing and sharing intelligence, surveillance, and reconnaissance information.

[…]

Red Disk was envisioned as a highly customizable cloud system that could meet the demands of large, complex military operations. The hope was that Red Disk could provide a consistent picture from the Pentagon to deployed soldiers in the Afghan battlefield, including satellite images and video feeds from drones trained on terrorists and enemy fighters, according to a Foreign Policy report.

[…]

Red Disk was a modular, customizable, and scalable system for sharing intelligence across the battlefield, like electronic intercepts, drone footage and satellite imagery, and classified reports, for troops to access with laptops and tablets on the battlefield. Marking files found in several directories imply the disk is “top secret,” and restricted from being shared to foreign intelligence partners.

A couple of points. One, this isn’t particularly sensitive. It’s an intelligence distribution system under development. It’s not raw intelligence. Two, this doesn’t seem to be classified data. Even the article hedges, using the unofficial term of “highly sensitive.” Three, it doesn’t seem that Chris Vickery, the researcher that discovered the data, has published it.

Chris Vickery, director of cyber risk research at security firm UpGuard, found the data and informed the government of the breach in October. The storage server was subsequently secured, though its owner remains unknown.

This doesn’t feel like a big deal to me.

Slashdot thread.

IoT Cybersecurity: What’s Plan B?

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/10/iot_cybersecuri.html

In August, four US Senators introduced a bill designed to improve Internet of Things (IoT) security. The IoT Cybersecurity Improvement Act of 2017 is a modest piece of legislation. It doesn’t regulate the IoT market. It doesn’t single out any industries for particular attention, or force any companies to do anything. It doesn’t even modify the liability laws for embedded software. Companies can continue to sell IoT devices with whatever lousy security they want.

What the bill does do is leverage the government’s buying power to nudge the market: any IoT product that the government buys must meet minimum security standards. It requires vendors to ensure that devices can not only be patched, but are patched in an authenticated and timely manner; don’t have unchangeable default passwords; and are free from known vulnerabilities. It’s about as low a security bar as you can set, and that it will considerably improve security speaks volumes about the current state of IoT security. (Full disclosure: I helped draft some of the bill’s security requirements.)

The bill would also modify the Computer Fraud and Abuse and the Digital Millennium Copyright Acts to allow security researchers to study the security of IoT devices purchased by the government. It’s a far narrower exemption than our industry needs. But it’s a good first step, which is probably the best thing you can say about this legislation.

However, it’s unlikely this first step will even be taken. I am writing this column in August, and have no doubt that the bill will have gone nowhere by the time you read it in October or later. If hearings are held, they won’t matter. The bill won’t have been voted on by any committee, and it won’t be on any legislative calendar. The odds of this bill becoming law are zero. And that’s not just because of current politics — I’d be equally pessimistic under the Obama administration.

But the situation is critical. The Internet is dangerous — and the IoT gives it not just eyes and ears, but also hands and feet. Security vulnerabilities, exploits, and attacks that once affected only bits and bytes now affect flesh and blood.

Markets, as we’ve repeatedly learned over the past century, are terrible mechanisms for improving the safety of products and services. It was true for automobile, food, restaurant, airplane, fire, and financial-instrument safety. The reasons are complicated, but basically, sellers don’t compete on safety features because buyers can’t efficiently differentiate products based on safety considerations. The race-to-the-bottom mechanism that markets use to minimize prices also minimizes quality. Without government intervention, the IoT remains dangerously insecure.

The US government has no appetite for intervention, so we won’t see serious safety and security regulations, a new federal agency, or better liability laws. We might have a better chance in the EU. Depending on how the General Data Protection Regulation on data privacy pans out, the EU might pass a similar security law in 5 years. No other country has a large enough market share to make a difference.

Sometimes we can opt out of the IoT, but that option is becoming increasingly rare. Last year, I tried and failed to purchase a new car without an Internet connection. In a few years, it’s going to be nearly impossible to not be multiply connected to the IoT. And our biggest IoT security risks will stem not from devices we have a market relationship with, but from everyone else’s cars, cameras, routers, drones, and so on.

We can try to shop our ideals and demand more security, but companies don’t compete on IoT safety — and we security experts aren’t a large enough market force to make a difference.

We need a Plan B, although I’m not sure what that is. E-mail me if you have any ideas.

This essay previously appeared in the September/October issue of IEEE Security & Privacy.

Military Robots as a Nature Analog

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/08/military_robots.html

This very interesting essay looks at the future of military robotics and finds many analogs in nature:

Imagine a low-cost drone with the range of a Canada goose, a bird that can cover 1,500 miles in a single day at an average speed of 60 miles per hour. Planet Earth profiled a single flock of snow geese, birds that make similar marathon journeys, albeit slower. The flock of six-pound snow geese was so large it formed a sky-darkening cloud 12 miles long. How would an aircraft carrier battlegroup respond to an attack from millions of aerial kamikaze explosive drones that, like geese, can fly hundreds of miles? A single aircraft carrier costs billions of dollars, and the United States relies heavily on its ten aircraft carrier strike groups to project power around the globe. But as military robots match more capabilities found in nature, some of the major systems and strategies upon which U.S. national security currently relies — perhaps even the fearsome aircraft carrier strike group — might experience the same sort of technological disruption that the smartphone revolution brought about in the consumer world.

US Army Researching Bot Swarms

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

The US Army Research Agency is funding research into autonomous bot swarms. From the announcement:

The objective of this CRA is to perform enabling basic and applied research to extend the reach, situational awareness, and operational effectiveness of large heterogeneous teams of intelligent systems and Soldiers against dynamic threats in complex and contested environments and provide technical and operational superiority through fast, intelligent, resilient and collaborative behaviors. To achieve this, ARL is requesting proposals that address three key Research Areas (RAs):

RA1: Distributed Intelligence: Establish the theoretical foundations of multi-faceted distributed networked intelligent systems combining autonomous agents, sensors, tactical super-computing, knowledge bases in the tactical cloud, and human experts to acquire and apply knowledge to affect and inform decisions of the collective team.

RA2: Heterogeneous Group Control: Develop theory and algorithms for control of large autonomous teams with varying levels of heterogeneity and modularity across sensing, computing, platforms, and degree of autonomy.

RA3: Adaptive and Resilient Behaviors: Develop theory and experimental methods for heterogeneous teams to carry out tasks under the dynamic and varying conditions in the physical world.

Slashdot thread.

And while we’re on the subject, this is an excellent report on AI and national security.

DJI Firmware Hacking Removes Drone Flight Restrictions

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

Drones have been taking over the world, everyone with a passing interest in making videos has one and DJI firmware hacking gives you the ability to remove all restrictions (no-fly zones, height and distance) which under most jurisdictions is illegal (mostly EU and FAA for the US). It’s an interesting subject, and also a controversial…

Read the full post at darknet.org.uk

The Quick vs. the Strong: Commentary on Cory Doctorow’s Walkaway

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

Technological advances change the world. That’s partly because of what they are, but even more because of the social changes they enable. New technologies upend power balances. They give groups new capabilities, increased effectiveness, and new defenses. The Internet decades have been a never-ending series of these upendings. We’ve seen existing industries fall and new industries rise. We’ve seen governments become more powerful in some areas and less in others. We’ve seen the rise of a new form of governance: a multi-stakeholder model where skilled individuals can have more power than multinational corporations or major governments.

Among the many power struggles, there is one type I want to particularly highlight: the battles between the nimble individuals who start using a new technology first, and the slower organizations that come along later.

In general, the unempowered are the first to benefit from new technologies: hackers, dissidents, marginalized groups, criminals, and so on. When they first encountered the Internet, it was transformative. Suddenly, they had access to technologies for dissemination, coordination, organization, and action — things that were impossibly hard before. This can be incredibly empowering. In the early decades of the Internet, we saw it in the rise of Usenet discussion forums and special-interest mailing lists, in how the Internet routed around censorship, and how Internet governance bypassed traditional government and corporate models. More recently, we saw it in the SOPA/PIPA debate of 2011-12, the Gezi protests in Turkey and the various “color” revolutions, and the rising use of crowdfunding. These technologies can invert power dynamics, even in the presence of government surveillance and censorship.

But that’s just half the story. Technology magnifies power in general, but the rates of adoption are different. Criminals, dissidents, the unorganized — all outliers — are more agile. They can make use of new technologies faster, and can magnify their collective power because of it. But when the already-powerful big institutions finally figured out how to use the Internet, they had more raw power to magnify.

This is true for both governments and corporations. We now know that governments all over the world are militarizing the Internet, using it for surveillance, censorship, and propaganda. Large corporations are using it to control what we can do and see, and the rise of winner-take-all distribution systems only exacerbates this.

This is the fundamental tension at the heart of the Internet, and information-based technology in general. The unempowered are more efficient at leveraging new technology, while the powerful have more raw power to leverage. These two trends lead to a battle between the quick and the strong: the quick who can make use of new power faster, and the strong who can make use of that same power more effectively.

This battle is playing out today in many different areas of information technology. You can see it in the security vs. surveillance battles between criminals and the FBI, or dissidents and the Chinese government. You can see it in the battles between content pirates and various media organizations. You can see it where social-media giants and Internet-commerce giants battle against new upstarts. You can see it in politics, where the newer Internet-aware organizations fight with the older, more established, political organizations. You can even see it in warfare, where a small cadre of military can keep a country under perpetual bombardment — using drones — with no risk to the attackers.

This battle is fundamental to Cory Doctorow’s new novel Walkaway. Our heroes represent the quick: those who have checked out of traditional society, and thrive because easy access to 3D printers enables them to eschew traditional notions of property. Their enemy is the strong: the traditional government institutions that exert their power mostly because they can. This battle rages through most of the book, as the quick embrace ever-new technologies and the strong struggle to catch up.

It’s easy to root for the quick, both in Doctorow’s book and in the real world. And while I’m not going to give away Doctorow’s ending — and I don’t know enough to predict how it will play out in the real world — right now, trends favor the strong.

Centralized infrastructure favors traditional power, and the Internet is becoming more centralized. This is true both at the endpoints, where companies like Facebook, Apple, Google, and Amazon control much of how we interact with information. It’s also true in the middle, where companies like Comcast increasingly control how information gets to us. It’s true in countries like Russia and China that increasingly legislate their own national agenda onto their pieces of the Internet. And it’s even true in countries like the US and the UK, that increasingly legislate more government surveillance capabilities.

At the 1996 World Economic Forum, cyber-libertarian John Perry Barlow issued his “Declaration of the Independence of Cyberspace,” telling the assembled world leaders and titans of Industry: “You have no moral right to rule us, nor do you possess any methods of enforcement that we have true reason to fear.” Many of us believed him a scant 20 years ago, but today those words ring hollow.

But if history is any guide, these things are cyclic. In another 20 years, even newer technologies — both the ones Doctorow focuses on and the ones no one can predict — could easily tip the balance back in favor of the quick. Whether that will result in more of a utopia or a dystopia depends partly on these technologies, but even more on the social changes resulting from these technologies. I’m short-term pessimistic but long-term optimistic.

This essay previously appeared on Crooked Timber.

Community Profile: Jillian Ogle

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/community-profile-jillian-ogle/

This column is from The MagPi issue 53. You can download a PDF of the full issue for free, or subscribe to receive the print edition in your mailbox or the digital edition on your tablet. All proceeds from the print and digital editions help the Raspberry Pi Foundation achieve its charitable goals.

Let’s Robot streams twice a week, Tuesdays and Thursdays, and allows the general public to control a team of robots within an interactive set, often consisting of mazes, clues, challenges, and even the occasional foe. Users work together via the Twitch.tv platform, sending instructions to the robots in order to navigate their terrain and complete the set objectives.

Let's Robot Raspberry Pi Jillian Ogle

Let’s Robot aims to change the way we interact with television, putting the viewer in the driving seat.

Aylobot, the first robot of the project, boasts a LEGO body, while Ninabot, the somewhat 2.0 upgrade of the two, has a gripper, allowing more interaction from users. Both robots have their own cameras that stream to Twitch, so that those in control can see what they’re up to on a more personal level; several new additions have joined the robot team since then, each with their own unique skill.

Let's Robot Raspberry Pi Jillian Ogle

Twice a week, the robots are controlled by the viewers, allowing them the chance to complete tasks such as force-feeding the intern, attempting to write party invitations, and battling in boss fights.

Jillian Ogle

Let’s Robot is the brainchild of Jillian Ogle, who originally set out to make “the world’s first interactive live show using telepresence robots collaboratively controlled by the audience”. However, Jill discovered quite quickly that the robots needed to complete the project simply didn’t exist to the standard required… and so Let’s Robot was born.

After researching various components for the task, Jill decided upon the Raspberry Pi, and it’s this small SBC that now exists within the bodies of Aylobot, Ninabot, and the rest of the Let’s Robot family.

Let's Robot Jillian Ogle Raspberry Pi

“Post-Its I drew for our #LetsRobot subscribers. We put these in the physical sets made for the robots. I still have a lot more to draw…”

In her previous life, Jill worked in art and game design, including a role as art director for Playdom, a subsidiary of Disney Interactive; she moved on to found Aylo Games in 2013 and Let’s Robot in 2015. The hardware side of the builds has been something of a recently discovered skill, with Jill admitting, “Anything I know about hardware I’ve picked up in the last two years while developing this project.”

This was my first ever drone flight, live on #twitch. I think it went well. #letsrobot #robot #robotics #robots #drone #drones #twitchtv #twitchcreative #twitchplays #fail #livestream #raspberrypi #arduino #hardware #mechatronics #mechanicalengineering #makersgonnamake #nailedit #make #electronics

73 Likes, 3 Comments – Jillian Ogle (@letsjill) on Instagram: “This was my first ever drone flight, live on #twitch. I think it went well. #letsrobot #robot…”

Social media funtimes

More recently, as Let’s Robot continues to grow, Jill can be found sharing the antics of the robots across social media, documenting their quests – such as the hilarious attempt to create party invites and the more recent Hillarybot vs Trumpbot balloon head battle, where robots with extendable pin-mounted arms fight to pop each other’s head.

Last night was the robot presidential debate, and here is an early version of candidate #Trump bot. #letsrobot #robotics #robot #raspberrypi #twitch #twitchtv #twitchplays #3dprinting #mechatronics #arduino #iot #robots #crafting #make #battlebots #hardware #twitchcreative #presidentialdebate2016 #donaldtrump #electronics #omgrobots #adafruit #silly

400 Likes, 2 Comments – Jillian Ogle (@letsjill) on Instagram: “Last night was the robot presidential debate, and here is an early version of candidate #Trump bot….”

Gotta catch ’em all

Alongside the robots, Jill has created several other projects that both add to the interactive experience of Let’s Robot and comment on other elements of social trends out in the world. Most notably, there is the Pokémon Go Robot, originally a robot arm that would simulate the throw of an on-screen Poké Ball. It later grew wheels and took to the outside world, hunting down its pocket monster prey.

Let's Robot Pokemon Go Raspberry Pi

Originally sitting on a desk, the Pokémon Go Robot earned itself a new upgrade, gaining the body of a rover to allow it to handle the terrain of the outside world. Paired with the Livestream Goggles, viewers can join in the fun.

It’s also worth noting other builds, such as the WiFi Livestream Goggles that Jill can be seen sporting across several social media posts. The goggles, with a Pi camera fitted between the wearer’s eyes, allow viewers to witness Jill’s work from her perspective. It’s a great build, especially given how open the Let’s Robot team are about their continued work and progression.

Let's Robot Pokemon Go Raspberry Pi

The WiFi-enabled helmet allows viewers the ability to see what Jill sees, offering a new perspective alongside the Let’s Robot bots. The Raspberry Pi camera fits perfectly between the eyes, bringing a true eye level to the viewer. She also created internet-controlled LED eyebrows… see the video!

And finally, one project we are eager to see completed is the ‘in production’ Pi-powered transparent HUD. By incorporating refractive acrylic, Jill aims to create a see-through display that allows her to read user comments via the Twitch live-stream chat, without having to turn her eyes to a separate monitor

Since the publication of this article in The MagPi magazine, Jill and the Let’s Robot team have continued to grow their project. There are some interesting and exciting developments ahead – we’ll cover their progress in a future blog.

The post Community Profile: Jillian Ogle appeared first on Raspberry Pi.

Jumping Airgaps with a Laser and a Scanner

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/04/jumping_airgaps.html

Researchers have configured two computers to talk to each other using a laser and a scanner.

Scanners work by detecting reflected light on their glass pane. The light creates a charge that the scanner translates into binary, which gets converted into an image. But scanners are sensitive to any changes of light in a room­ — even when paper is on the glass pane or when the light source is infrared — which changes the charges that get converted to binary. This means signals can be sent through the scanner by flashing light at its glass pane using either a visible light source or an infrared laser that is invisible to human eyes.

There are a couple of caveats to the attack — the malware to decode the signals has to already be installed on a system on the network, and the lid on the scanner has to be at least partially open to receive the light. It’s not unusual for workers to leave scanner lids open after using them, however, and an attacker could also pay a cleaning crew or other worker to leave the lid open at night.

The setup is that there’s malware on the computer connected to the scanner, and that computer isn’t on the Internet. This technique allows an attacker to communicate with that computer. For extra coolness, the laser can be mounted on a drone.

Here’s the paper. And two videos.

Acoustic Attack Against Accelerometers

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/04/acoustic_attack.html

Interesting acoustic attack against the MEMS accelerometers in devices like FitBits.

Millions of accelerometers reside inside smartphones, automobiles, medical devices, anti-theft devices, drones, IoT devices, and many other industrial and consumer applications. Our work investigates how analog acoustic injection attacks can damage the digital integrity of the capacitive MEMS accelerometer. Spoofing such sensors with intentional acoustic interference enables an out-of-spec pathway for attackers to deliver chosen digital values to microprocessors and embedded systems that blindly trust the unvalidated integrity of sensor outputs. Our contributions include (1) modeling the physics of malicious acoustic interference on MEMS accelerometers, (2) discovering the circuit-level security flaws that cause the vulnerabilities by measuring acoustic injection attacks on MEMS accelerometers as well as systems that employ on these sensors, and (3) two software-only defenses that mitigate many of the risks to the integrity of MEMS accelerometer outputs.

This is not that a big deal with things like FitBits, but as IoT devices get more autonomous — and start making decisions and then putting them into effect automatically — these vulnerabilities will become critical.

Academic paper.

Security Orchestration and Incident Response

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/03/security_orches.html

Last month at the RSA Conference, I saw a lot of companies selling security incident response automation. Their promise was to replace people with computers ­– sometimes with the addition of machine learning or other artificial intelligence techniques ­– and to respond to attacks at computer speeds.

While this is a laudable goal, there’s a fundamental problem with doing this in the short term. You can only automate what you’re certain about, and there is still an enormous amount of uncertainty in cybersecurity. Automation has its place in incident response, but the focus needs to be on making the people effective, not on replacing them ­ security orchestration, not automation.

This isn’t just a choice of words ­– it’s a difference in philosophy. The US military went through this in the 1990s. What was called the Revolution in Military Affairs (RMA) was supposed to change how warfare was fought. Satellites, drones and battlefield sensors were supposed to give commanders unprecedented information about what was going on, while networked soldiers and weaponry would enable troops to coordinate to a degree never before possible. In short, the traditional fog of war would be replaced by perfect information, providing certainty instead of uncertainty. They, too, believed certainty would fuel automation and, in many circumstances, allow technology to replace people.

Of course, it didn’t work out that way. The US learned in Afghanistan and Iraq that there are a lot of holes in both its collection and coordination systems. Drones have their place, but they can’t replace ground troops. The advances from the RMA brought with them some enormous advantages, especially against militaries that didn’t have access to the same technologies, but never resulted in certainty. Uncertainty still rules the battlefield, and soldiers on the ground are still the only effective way to control a region of territory.

But along the way, we learned a lot about how the feeling of certainty affects military thinking. Last month, I attended a lecture on the topic by H.R. McMaster. This was before he became President Trump’s national security advisor-designate. Then, he was the director of the Army Capabilities Integration Center. His lecture touched on many topics, but at one point he talked about the failure of the RMA. He confirmed that military strategists mistakenly believed that data would give them certainty. But he took this change in thinking further, outlining the ways this belief in certainty had repercussions in how military strategists thought about modern conflict.

McMaster’s observations are directly relevant to Internet security incident response. We too have been led to believe that data will give us certainty, and we are making the same mistakes that the military did in the 1990s. In a world of uncertainty, there’s a premium on understanding, because commanders need to figure out what’s going on. In a world of certainty, knowing what’s going on becomes a simple matter of data collection.

I see this same fallacy in Internet security. Many companies exhibiting at the RSA Conference promised to collect and display more data and that the data will reveal everything. This simply isn’t true. Data does not equal information, and information does not equal understanding. We need data, but we also must prioritize understanding the data we have over collecting ever more data. Much like the problems with bulk surveillance, the “collect it all” approach provides minimal value over collecting the specific data that’s useful.

In a world of uncertainty, the focus is on execution. In a world of certainty, the focus is on planning. I see this manifesting in Internet security as well. My own Resilient Systems ­– now part of IBM Security –­ allows incident response teams to manage security incidents and intrusions. While the tool is useful for planning and testing, its real focus is always on execution.

Uncertainty demands initiative, while certainty demands synchronization. Here, again, we are heading too far down the wrong path. The purpose of all incident response tools should be to make the human responders more effective. They need both the ability and the capability to exercise it effectively.

When things are uncertain, you want your systems to be decentralized. When things are certain, centralization is more important. Good incident response teams know that decentralization goes hand in hand with initiative. And finally, a world of uncertainty prioritizes command, while a world of certainty prioritizes control. Again, effective incident response teams know this, and effective managers aren’t scared to release and delegate control.

Like the US military, we in the incident response field have shifted too much into the world of certainty. We have prioritized data collection, preplanning, synchronization, centralization and control. You can see it in the way people talk about the future of Internet security, and you can see it in the products and services offered on the show floor of the RSA Conference.

Automation, too, is fixed. Incident response needs to be dynamic and agile, because you are never certain and there is an adaptive, malicious adversary on the other end. You need a response system that has human controls and can modify itself on the fly. Automation just doesn’t allow a system to do that to the extent that’s needed in today’s environment. Just as the military shifted from trying to replace the soldier to making the best soldier possible, we need to do the same.

For some time, I have been talking about incident response in terms of OODA loops. This is a way of thinking about real-time adversarial relationships, originally developed for airplane dogfights, but much more broadly applicable. OODA stands for observe-orient-decide-act, and it’s what people responding to a cybersecurity incident do constantly, over and over again. We need tools that augment each of those four steps. These tools need to operate in a world of uncertainty, where there is never enough data to know everything that is going on. We need to prioritize understanding, execution, initiative, decentralization and command.

At the same time, we’re going to have to make all of this scale. If anything, the most seductive promise of a world of certainty and automation is that it allows defense to scale. The problem is that we’re not there yet. We can automate and scale parts of IT security, such as antivirus, automatic patching and firewall management, but we can’t yet scale incident response. We still need people. And we need to understand what can be automated and what can’t be.

The word I prefer is orchestration. Security orchestration represents the union of people, process and technology. It’s computer automation where it works, and human coordination where that’s necessary. It’s networked systems giving people understanding and capabilities for execution. It’s making those on the front lines of incident response the most effective they can be, instead of trying to replace them. It’s the best approach we have for cyberdefense.

Automation has its place. If you think about the product categories where it has worked, they’re all areas where we have pretty strong certainty. Automation works in antivirus, firewalls, patch management and authentication systems. None of them is perfect, but all those systems are right almost all the time, and we’ve developed ancillary systems to deal with it when they’re wrong.

Automation fails in incident response because there’s too much uncertainty. Actions can be automated once the people understand what’s going on, but people are still required. For example, IBM’s Watson for Cyber Security provides insights for incident response teams based on its ability to ingest and find patterns in an enormous amount of freeform data. It does not attempt a level of understanding necessary to take people out of the equation.

From within an orchestration model, automation can be incredibly powerful. But it’s the human-centric orchestration model –­ the dashboards, the reports, the collaboration –­ that makes automation work. Otherwise, you’re blindly trusting the machine. And when an uncertain process is automated, the results can be dangerous.

Technology continues to advance, and this is all a changing target. Eventually, computers will become intelligent enough to replace people at real-time incident response. My guess, though, is that computers are not going to get there by collecting enough data to be certain. More likely, they’ll develop the ability to exhibit understanding and operate in a world of uncertainty. That’s a much harder goal.

Yes, today, this is all science fiction. But it’s not stupid science fiction, and it might become reality during the lifetimes of our children. Until then, we need people in the loop. Orchestration is a way to achieve that.

This essay previously appeared on the Security Intelligence blog.