Tag Archives: economicsofsecurity

Research on Human Honesty

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

New research from Science: “Civic honesty around the globe“:

Abstract: Civic honesty is essential to social capital and economic development, but is often in conflict with material self-interest. We examine the trade-off between honesty and self-interest using field experiments in 355 cities spanning 40 countries around the globe. We turned in over 17,000 lost wallets with varying amounts of money at public and private institutions, and measured whether recipients contacted the owner to return the wallets. In virtually all countries citizens were more likely to return wallets that contained more money. Both non-experts and professional economists were unable to predict this result. Additional data suggest our main findings can be explained by a combination of altruistic concerns and an aversion to viewing oneself as a thief, which increase with the material benefits of dishonesty.

I am surprised, too.

Security and Human Behavior (SHB) 2019

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/06/security_and_hu_8.html

Today is the second day of the twelfth Workshop on Security and Human Behavior, which I am hosting at Harvard University.

SHB is a small, annual, invitational workshop of people studying various aspects of the human side of security, organized each year by Alessandro Acquisti, Ross Anderson, and myself. The 50 or so people in the room include psychologists, economists, computer security researchers, sociologists, political scientists, criminologists, neuroscientists, designers, lawyers, philosophers, anthropologists, business school professors, and a smattering of others. It’s not just an interdisciplinary event; most of the people here are individually interdisciplinary.

The goal is to maximize discussion and interaction. We do that by putting everyone on panels, and limiting talks to 7-10 minutes. The rest of the time is left to open discussion. Four hour-and-a-half panels per day over two days equals eight panels; six people per panel means that 48 people get to speak. We also have lunches, dinners, and receptions — all designed so people from different disciplines talk to each other.

I invariably find this to be the most intellectually stimulating two days of my professional year. It influences my thinking in many different, and sometimes surprising, ways.

This year’s program is here. This page lists the participants and includes links to some of their work. As he does every year, Ross Anderson is liveblogging the talks — remotely, because he was denied a visa earlier this year.

Here are my posts on the first, second, third, fourth, fifth, sixth, seventh, eighth, ninth, tenth, and eleventh SHB workshops. Follow those links to find summaries, papers, and occasionally audio recordings of the various workshops. Ross also maintains a good webpage of psychology and security resources.

The Cost of Cybercrime

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/06/the_cost_of_cyb_1.html

Really interesting paper calculating the worldwide cost of cybercrime:

Abstract: In 2012 we presented the first systematic study of the costs of cybercrime. In this paper,we report what has changed in the seven years since. The period has seen major platform evolution, with the mobile phone replacing the PC and laptop as the consumer terminal of choice, with Android replacing Windows, and with many services moving to the cloud.The use of social networks has become extremely widespread. The executive summary is that about half of all property crime, by volume and by value, is now online. We hypothesised in 2012 that this might be so; it is now established by multiple victimisation studies.Many cybercrime patterns appear to be fairly stable, but there are some interesting changes.Payment fraud, for example, has more than doubled in value but has fallen slightly as a proportion of payment value; the payment system has simply become bigger, and slightly more efficient. Several new cybercrimes are significant enough to mention, including business email compromise and crimes involving cryptocurrencies. The move to the cloud means that system misconfiguration may now be responsible for as many breaches as phishing. Some companies have suffered large losses as a side-effect of denial-of-service worms released by state actors, such as NotPetya; we have to take a view on whether they count as cybercrime.The infrastructure supporting cybercrime, such as botnets, continues to evolve, and specific crimes such as premium-rate phone scams have evolved some interesting variants. The over-all picture is the same as in 2012: traditional offences that are now technically ‘computercrimes’ such as tax and welfare fraud cost the typical citizen in the low hundreds of Euros/dollars a year; payment frauds and similar offences, where the modus operandi has been completely changed by computers, cost in the tens; while the new computer crimes cost in the tens of cents. Defending against the platforms used to support the latter two types of crime cost citizens in the tens of dollars. Our conclusions remain broadly the same as in 2012:it would be economically rational to spend less in anticipation of cybercrime (on antivirus, firewalls, etc.) and more on response. We are particularly bad at prosecuting criminals who operate infrastructure that other wrongdoers exploit. Given the growing realisation among policymakers that crime hasn’t been falling over the past decade, merely moving online, we might reasonably hope for better funded and coordinated law-enforcement action.

Richard Clayton gave a presentation on this yesterday at WEIS. His final slide contained a summary.

  • Payment fraud is up, but credit card sales are up even more — so we’re winning.
  • Cryptocurrencies are enabling new scams, but the bit money is still being list in more traditional investment fraud.

  • Telcom fraud is down, basically because Skype is free.

  • Anti-virus fraud has almost disappeared, but tech support scams are growing very rapidly.

  • The big money is still in tax fraud, welfare fraud, VAT fraud, and so on.

  • We spend more money on cyber defense than we do on the actual losses.

  • Criminals largely act with impunity. They don’t believe they will get caught, and mostly that’s correct.

Bottom line: the technology has changed a lot since 2012, but the economic considerations remain unchanged.

The Concept of "Return on Data"

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/05/the_concept_of_.html

This law review article by Noam Kolt, titled “Return on Data,” proposes an interesting new way of thinking of privacy law.

Abstract: Consumers routinely supply personal data to technology companies in exchange for services. Yet, the relationship between the utility (U) consumers gain and the data (D) they supply — “return on data” (ROD) — remains largely unexplored. Expressed as a ratio, ROD = U / D. While lawmakers strongly advocate protecting consumer privacy, they tend to overlook ROD. Are the benefits of the services enjoyed by consumers, such as social networking and predictive search, commensurate with the value of the data extracted from them? How can consumers compare competing data-for-services deals? Currently, the legal frameworks regulating these transactions, including privacy law, aim primarily to protect personal data. They treat data protection as a standalone issue, distinct from the benefits which consumers receive. This article suggests that privacy concerns should not be viewed in isolation, but as part of ROD. Just as companies can quantify return on investment (ROI) to optimize investment decisions, consumers should be able to assess ROD in order to better spend and invest personal data. Making data-for-services transactions more transparent will enable consumers to evaluate the merits of these deals, negotiate their terms and make more informed decisions. Pivoting from the privacy paradigm to ROD will both incentivize data-driven service providers to offer consumers higher ROD, as well as create opportunities for new market entrants.

Prices for Zero-Day Exploits Are Rising

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/01/prices_for_zero.html

Companies are willing to pay ever-increasing amounts for good zero-day exploits against hard-to-break computers and applications:

On Monday, market-leading exploit broker Zerodium said it would pay up to $2 million for zero-click jailbreaks of Apple’s iOS, $1.5 million for one-click iOS jailbreaks, and $1 million for exploits that take over secure messaging apps WhatsApp and iMessage. Previously, Zerodium was offering $1.5 million, $1 million, and $500,000 for the same types of exploits respectively. The steeper prices indicate not only that the demand for these exploits continues to grow, but also that reliably compromising these targets is becoming increasingly hard.

Note that these prices are for offensive uses of the exploit. Zerodium — and others — sell exploits to companies who make surveillance tools and cyber-weapons for governments. Many companies have bug bounty programs for those who want the exploit used for defensive purposes — i.e., fixed — but they pay orders of magnitude less. This is a problem.

Back in 2014, Dan Geer said that that the US should corner the market on software vulnerabilities:

“There is no doubt that the U.S. Government could openly corner the world vulnerability market,” said Geer, “that is, we buy them all and we make them all public. Simply announce ‘Show us a competing bid, and we’ll give you [10 times more].’ Sure, there are some who will say ‘I hate Americans; I sell only to Ukrainians,’ but because vulnerability finding is increasingly automation-assisted, the seller who won’t sell to the Americans knows that his vulns can be rediscovered in due course by someone who will sell to the Americans who will tell everybody, thus his need to sell his product before it outdates is irresistible.”

I don’t know about the 10x, but in theory he’s right. There’s no other way to solve this.

Security Vulnerabilities in Cell Phone Systems

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/01/security_vulner_19.html

Good essay on the inherent vulnerabilities in the cell phone standards and the market barriers to fixing them.

So far, industry and policymakers have largely dragged their feet when it comes to blocking cell-site simulators and SS7 attacks. Senator Ron Wyden, one of the few lawmakers vocal about this issue, sent a letter in August encouraging the Department of Justice to “be forthright with federal courts about the disruptive nature of cell-site simulators.” No response has ever been published.

The lack of action could be because it is a big task — there are hundreds of companies and international bodies involved in the cellular network. The other reason could be that intelligence and law enforcement agencies have a vested interest in exploiting these same vulnerabilities. But law enforcement has other effective tools that are unavailable to criminals and spies. For example, the police can work directly with phone companies, serving warrants and Title III wiretap orders. In the end, eliminating these vulnerabilities is just as valuable for law enforcement as it is for everyone else.

As it stands, there is no government agency that has the power, funding and mission to fix the problems. Large companies such as AT&T, Verizon, Google and Apple have not been public about their efforts, if any exist.

Machine Learning to Detect Software Vulnerabilities

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/01/machine_learnin.html

No one doubts that artificial intelligence (AI) and machine learning (ML) will transform cybersecurity. We just don’t know how, or when. While the literature generally focuses on the different uses of AI by attackers and defenders ­ and the resultant arms race between the two ­ I want to talk about software vulnerabilities.

All software contains bugs. The reason is basically economic: The market doesn’t want to pay for quality software. With a few exceptions, such as the space shuttle, the market prioritizes fast and cheap over good. The result is that any large modern software package contains hundreds or thousands of bugs.

Some percentage of bugs are also vulnerabilities, and a percentage of those are exploitable vulnerabilities, meaning an attacker who knows about them can attack the underlying system in some way. And some percentage of those are discovered and used. This is why your computer and smartphone software is constantly being patched; software vendors are fixing bugs that are also vulnerabilities that have been discovered and are being used.

Everything would be better if software vendors found and fixed all bugs during the design and development process, but, as I said, the market doesn’t reward that kind of delay and expense. AI, and machine learning in particular, has the potential to forever change this trade-off.

The problem of finding software vulnerabilities seems well-suited for ML systems. Going through code line by line is just the sort of tedious problem that computers excel at, if we can only teach them what a vulnerability looks like. There are challenges with that, of course, but there is already a healthy amount of academic literature on the topic — and research is continuing. There’s every reason to expect ML systems to get better at this as time goes on, and some reason to expect them to eventually become very good at it.

Finding vulnerabilities can benefit both attackers and defenders, but it’s not a fair fight. When an attacker’s ML system finds a vulnerability in software, the attacker can use it to compromise systems. When a defender’s ML system finds the same vulnerability, he or she can try to patch the system or program network defenses to watch for and block code that tries to exploit it.

But when the same system is in the hands of a software developer who uses it to find the vulnerability before the software is ever released, the developer fixes it so it can never be used in the first place. The ML system will probably be part of his or her software design tools and will automatically find and fix vulnerabilities while the code is still in development.

Fast-forward a decade or so into the future. We might say to each other, “Remember those years when software vulnerabilities were a thing, before ML vulnerability finders were built into every compiler and fixed them before the software was ever released? Wow, those were crazy years.” Not only is this future possible, but I would bet on it.

Getting from here to there will be a dangerous ride, though. Those vulnerability finders will first be unleashed on existing software, giving attackers hundreds if not thousands of vulnerabilities to exploit in real-world attacks. Sure, defenders can use the same systems, but many of today’s Internet of Things systems have no engineering teams to write patches and no ability to download and install patches. The result will be hundreds of vulnerabilities that attackers can find and use.

But if we look far enough into the horizon, we can see a future where software vulnerabilities are a thing of the past. Then we’ll just have to worry about whatever new and more advanced attack techniques those AI systems come up with.

This essay previously appeared on SecurityIntelligence.com.

Measuring the Rationality of Security Decisions

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/08/measuring_the_r.html

Interesting research: “Dancing Pigs or Externalities? Measuring the Rationality of
Security Decisions
“:

Abstract: Accurately modeling human decision-making in security is critical to thinking about when, why, and how to recommend that users adopt certain secure behaviors. In this work, we conduct behavioral economics experiments to model the rationality of end-user security decision-making in a realistic online experimental system simulating a bank account. We ask participants to make a financially impactful security choice, in the face of transparent risks of account compromise and benefits offered by an optional security behavior (two-factor authentication). We measure the cost and utility of adopting the security behavior via measurements of time spent executing the behavior and estimates of the participant’s wage. We find that more than 50% of our participants made rational (e.g., utility optimal) decisions, and we find that participants are more likely to behave rationally in the face of higher risk. Additionally, we find that users’ decisions can be modeled well as a function of past behavior (anchoring effects), knowledge of costs, and to a lesser extent, users’ awareness of risks and context (R2=0.61). We also find evidence of endowment effects, as seen in other areas of economic and psychological decision-science literature, in our digital-security setting. Finally, using our data, we show theoretically that a “one-size-fits-all” emphasis on security can lead to market losses, but that adoption by a subset of users with higher risks or lower costs can lead to market gains

GCHQ on Quantum Key Distribution

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/08/gchq_on_quantum.html

The UK’s GCHQ delivers a brutally blunt assessment of quantum key distribution:

QKD protocols address only the problem of agreeing keys for encrypting data. Ubiquitous on-demand modern services (such as verifying identities and data integrity, establishing network sessions, providing access control, and automatic software updates) rely more on authentication and integrity mechanisms — such as digital signatures — than on encryption.

QKD technology cannot replace the flexible authentication mechanisms provided by contemporary public key signatures. QKD also seems unsuitable for some of the grand future challenges such as securing the Internet of Things (IoT), big data, social media, or cloud applications.

I agree with them. It’s a clever idea, but basically useless in practice. I don’t even think it’s anything more than a niche solution in a world where quantum computers have broken our traditional public-key algorithms.

Read the whole thing. It’s short.

On Financial Fraud

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/07/on_financial_fr.html

There are some good lessons in this article on financial fraud:

That’s how we got it so wrong. We were looking for incidental breaches of technical regulations, not systematic crime. And the thing is, that’s normal. The nature of fraud is that it works outside your field of vision, subverting the normal checks and balances so that the world changes while the picture stays the same. People in financial markets have been missing the wood for the trees for as long as there have been markets.

[..]

Trust — particularly between complete strangers, with no interactions beside relatively anonymous market transactions — is the basis of the modern industrial economy. And the story of the development of the modern economy is in large part the story of the invention and improvement of technologies and institutions for managing that trust.

And as industrial society develops, it becomes easier to be a victim. In The Wealth of Nations, Adam Smith described how prosperity derived from the division of labour — the 18 distinct operations that went into the manufacture of a pin, for example. While this was going on, the modern world also saw a growing division of trust. The more a society benefits from the division of labour in checking up on things, the further you can go into a con game before you realise that you’re in one.

[…]

Libor teaches us a valuable lesson about commercial fraud — that unlike other crimes, it has a problem of denial as well as one of detection. There are very few other criminal acts where the victim not only consents to the criminal act, but voluntarily transfers the money or valuable goods to the criminal. And the hierarchies, status distinctions and networks that make up a modern economy also create powerful psychological barriers against seeing fraud when it is happening. White-collar crime is partly defined by the kind of person who commits it: a person of high status in the community, the kind of person who is always given the benefit of the doubt.

[…]

Fraudsters don’t play on moral weaknesses, greed or fear; they play on weaknesses in the system of checks and balances — the audit processes that are meant to supplement an overall environment of trust. One point that comes up again and again when looking at famous and large-scale frauds is that, in many cases, everything could have been brought to a halt at a very early stage if anyone had taken care to confirm all the facts. But nobody does confirm all the facts. There are just too bloody many of them. Even after the financial rubble has settled and the arrests been made, this is a huge problem.

Department of Commerce Report on the Botnet Threat

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/07/department_of_c.html

Last month, the US Department of Commerce released a report on the threat of botnets and what to do about it. I note that it explicitly said that the IoT makes the threat worse, and that the solutions are largely economic.

The Departments determined that the opportunities and challenges in working toward dramatically reducing threats from automated, distributed attacks can be summarized in six principal themes.

  1. Automated, distributed attacks are a global problem. The majority of the compromised devices in recent noteworthy botnets have been geographically located outside the United States. To increase the resilience of the Internet and communications ecosystem against these threats, many of which originate outside the United States, we must continue to work closely with international partners.
  2. Effective tools exist, but are not widely used. While there remains room for improvement, the tools, processes, and practices required to significantly enhance the resilience of the Internet and communications ecosystem are widely available, and are routinely applied in selected market sectors. However, they are not part of common practices for product development and deployment in many other sectors for a variety of reasons, including (but not limited to) lack of awareness, cost avoidance, insufficient technical expertise, and lack of market incentives

  3. Products should be secured during all stages of the lifecycle. Devices that are vulnerable at time of deployment, lack facilities to patch vulnerabilities after discovery, or remain in service after vendor support ends make assembling automated, distributed threats far too easy.

  4. Awareness and education are needed. Home users and some enterprise customers are often unaware of the role their devices could play in a botnet attack and may not fully understand the merits of available technical controls. Product developers, manufacturers, and infrastructure operators often lack the knowledge and skills necessary to deploy tools, processes, and practices that would make the ecosystem more resilient.

  5. Market incentives should be more effectively aligned. Market incentives do not currently appear to align with the goal of “dramatically reducing threats perpetrated by automated and distributed attacks.” Product developers, manufacturers, and vendors are motivated to minimize cost and time to market, rather than to build in security or offer efficient security updates. Market incentives must be realigned to promote a better balance between security and convenience when developing products.

  6. Automated, distributed attacks are an ecosystem-wide challenge. No single stakeholder community can address the problem in isolation.

[…]

The Departments identified five complementary and mutually supportive goals that, if realized, would dramatically reduce the threat of automated, distributed attacks and improve the resilience and redundancy of the ecosystem. A list of suggested actions for key stakeholders reinforces each goal. The goals are:

  • Goal 1: Identify a clear pathway toward an adaptable, sustainable, and secure technology marketplace.
  • Goal 2: Promote innovation in the infrastructure for dynamic adaptation to evolving threats.
  • Goal 3: Promote innovation at the edge of the network to prevent, detect, and mitigate automated, distributed attacks.
  • Goal 4: Promote and support coalitions between the security, infrastructure, and operational technology communities domestically and around the world
  • Goal 5: Increase awareness and education across the ecosystem.

Regulating Bitcoin

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/06/regulating_bitc.html

Ross Anderson has a new paper on cryptocurrency exchanges. From his blog:

Bitcoin Redux explains what’s going wrong in the world of cryptocurrencies. The bitcoin exchanges are developing into a shadow banking system, which do not give their customers actual bitcoin but rather display a “balance” and allow them to transact with others. However if Alice sends Bob a bitcoin, and they’re both customers of the same exchange, it just adjusts their balances rather than doing anything on the blockchain. This is an e-money service, according to European law, but is the law enforced? Not where it matters. We’ve been looking at the details.

The paper.

Estimating the Cost of Internet Insecurity

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

It’s really hard to estimate the cost of an insecure Internet. Studies are all over the map. A methodical study by RAND is the best work I’ve seen at trying to put a number on this. The results are, well, all over the map:

Estimating the Global Cost of Cyber Risk: Methodology and Examples“:

Abstract: There is marked variability from study to study in the estimated direct and systemic costs of cyber incidents, which is further complicated by the considerable variation in cyber risk in different countries and industry sectors. This report shares a transparent and adaptable methodology for estimating present and future global costs of cyber risk that acknowledges the considerable uncertainty in the frequencies and costs of cyber incidents. Specifically, this methodology (1) identifies the value at risk by country and industry sector; (2) computes direct costs by considering multiple financial exposures for each industry sector and the fraction of each exposure that is potentially at risk to cyber incidents; and (3) computes the systemic costs of cyber risk between industry sectors using Organisation for Economic Co-operation and Development input, output, and value-added data across sectors in more than 60 countries. The report has a companion Excel-based modeling and simulation platform that allows users to alter assumptions and investigate a wide variety of research questions. The authors used a literature review and data to create multiple sample sets of parameters. They then ran a set of case studies to show the model’s functionality and to compare the results against those in the existing literature. The resulting values are highly sensitive to input parameters; for instance, the global cost of cyber crime has direct gross domestic product (GDP) costs of $275 billion to $6.6 trillion and total GDP costs (direct plus systemic) of $799 billion to $22.5 trillion (1.1 to 32.4 percent of GDP).

Here’s Rand’s risk calculator, if you want to play with the parameters yourself.

Note: I was an advisor to the project.

Separately, Symantec has published a new cybercrime report with their own statistics.

Regulation of the Internet of Things

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2016/11/regulation_of_t.html

Late last month, popular websites like Twitter, Pinterest, Reddit and PayPal went down for most of a day. The distributed denial-of-service attack that caused the outages, and the vulnerabilities that made the attack possible, was as much a failure of market and policy as it was of technology. If we want to secure our increasingly computerized and connected world, we need more government involvement in the security of the “Internet of Things” and increased regulation of what are now critical and life-threatening technologies. It’s no longer a question of if, it’s a question of when.

First, the facts. Those websites went down because their domain name provider — a company named Dyn —­ was forced offline. We don’t know who perpetrated that attack, but it could have easily been a lone hacker. Whoever it was launched a distributed denial-of-service attack against Dyn by exploiting a vulnerability in large numbers ­— possibly millions — of Internet-of-Things devices like webcams and digital video recorders, then recruiting them all into a single botnet. The botnet bombarded Dyn with traffic, so much that it went down. And when it went down, so did dozens of websites.

Your security on the Internet depends on the security of millions of Internet-enabled devices, designed and sold by companies you’ve never heard of to consumers who don’t care about your security.

The technical reason these devices are insecure is complicated, but there is a market failure at work. The Internet of Things is bringing computerization and connectivity to many tens of millions of devices worldwide. These devices will affect every aspect of our lives, because they’re things like cars, home appliances, thermostats, light bulbs, fitness trackers, medical devices, smart streetlights and sidewalk squares. Many of these devices are low-cost, designed and built offshore, then rebranded and resold. The teams building these devices don’t have the security expertise we’ve come to expect from the major computer and smartphone manufacturers, simply because the market won’t stand for the additional costs that would require. These devices don’t get security updates like our more expensive computers, and many don’t even have a way to be patched. And, unlike our computers and phones, they stay around for years and decades.

An additional market failure illustrated by the Dyn attack is that neither the seller nor the buyer of those devices cares about fixing the vulnerability. The owners of those devices don’t care. They wanted a webcam —­ or thermostat, or refrigerator ­— with nice features at a good price. Even after they were recruited into this botnet, they still work fine ­— you can’t even tell they were used in the attack. The sellers of those devices don’t care: They’ve already moved on to selling newer and better models. There is no market solution because the insecurity primarily affects other people. It’s a form of invisible pollution.

And, like pollution, the only solution is to regulate. The government could impose minimum security standards on IoT manufacturers, forcing them to make their devices secure even though their customers don’t care. They could impose liabilities on manufacturers, allowing companies like Dyn to sue them if their devices are used in DDoS attacks. The details would need to be carefully scoped, but either of these options would raise the cost of insecurity and give companies incentives to spend money making their devices secure.

It’s true that this is a domestic solution to an international problem and that there’s no U.S. regulation that will affect, say, an Asian-made product sold in South America, even though that product could still be used to take down U.S. websites. But the main costs in making software come from development. If the United States and perhaps a few other major markets implement strong Internet-security regulations on IoT devices, manufacturers will be forced to upgrade their security if they want to sell to those markets. And any improvements they make in their software will be available in their products wherever they are sold, simply because it makes no sense to maintain two different versions of the software. This is truly an area where the actions of a few countries can drive worldwide change.

Regardless of what you think about regulation vs. market solutions, I believe there is no choice. Governments will get involved in the IoT, because the risks are too great and the stakes are too high. Computers are now able to affect our world in a direct and physical manner.

Security researchers have demonstrated the ability to remotely take control of Internet-enabled cars. They’ve demonstrated ransomware against home thermostats and exposed vulnerabilities in implanted medical devices. They’ve hacked voting machines and power plants. In one recent paper, researchers showed how a vulnerability in smart light bulbs could be used to start a chain reaction, resulting in them all being controlled by the attackers ­— that’s every one in a city. Security flaws in these things could mean people dying and property being destroyed.

Nothing motivates the U.S. government like fear. Remember 2001? A small-government Republican president created the Department of Homeland Security in the wake of the 9/11 terrorist attacks: a rushed and ill-thought-out decision that we’ve been trying to fix for more than a decade. A fatal IoT 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.

In general, the software market demands that products be fast and cheap and that security be a secondary consideration. That was okay when software didn’t matter —­ it was okay that your spreadsheet crashed once in a while. But a software bug that literally crashes your car is another thing altogether. The security vulnerabilities in the Internet of Things are deep and pervasive, and they won’t get fixed if the market is left to sort it out for itself. We need to proactively discuss good regulatory solutions; otherwise, a disaster will impose bad ones on us.

This essay previously appeared in the Washington Post.

Lessons From the Dyn DDoS Attack

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2016/11/lessons_from_th_5.html

A week ago Friday, someone took down numerous popular websites in a massive distributed denial-of-service (DDoS) attack against the domain name provider Dyn. DDoS attacks are neither new nor sophisticated. The attacker sends a massive amount of traffic, causing the victim’s system to slow to a crawl and eventually crash. There are more or less clever variants, but basically, it’s a datapipe-size battle between attacker and victim. If the defender has a larger capacity to receive and process data, he or she will win. If the attacker can throw more data than the victim can process, he or she will win.

The attacker can build a giant data cannon, but that’s expensive. It is much smarter to recruit millions of innocent computers on the internet. This is the “distributed” part of the DDoS attack, and pretty much how it’s worked for decades. Cybercriminals infect innocent computers around the internet and recruit them into a botnet. They then target that botnet against a single victim.

You can imagine how it might work in the real world. If I can trick tens of thousands of others to order pizzas to be delivered to your house at the same time, I can clog up your street and prevent any legitimate traffic from getting through. If I can trick many millions, I might be able to crush your house from the weight. That’s a DDoS attack ­ it’s simple brute force.

As you’d expect, DDoSers have various motives. The attacks started out as a way to show off, then quickly transitioned to a method of intimidation ­ or a way of just getting back at someone you didn’t like. More recently, they’ve become vehicles of protest. In 2013, the hacker group Anonymous petitioned the White House to recognize DDoS attacks as a legitimate form of protest. Criminals have used these attacks as a means of extortion, although one group found that just the fear of attack was enough. Military agencies are also thinking about DDoS as a tool in their cyberwar arsenals. A 2007 DDoS attack against Estonia was blamed on Russia and widely called an act of cyberwar.

The DDoS attack against Dyn two weeks ago was nothing new, but it illustrated several important trends in computer security.

These attack techniques are broadly available. Fully capable DDoS attack tools are available for free download. Criminal groups offer DDoS services for hire. The particular attack technique used against Dyn was first used a month earlier. It’s called Mirai, and since the source code was released four weeks ago, over a dozen botnets have incorporated the code.

The Dyn attacks were probably not originated by a government. The perpetrators were most likely hackers mad at Dyn for helping Brian Krebs identify ­ and the FBI arrest ­ two Israeli hackers who were running a DDoS-for-hire ring. Recently I have written about probing DDoS attacks against internet infrastructure companies that appear to be perpetrated by a nation-state. But, honestly, we don’t know for sure.

This is important. Software spreads capabilities. The smartest attacker needs to figure out the attack and write the software. After that, anyone can use it. There’s not even much of a difference between government and criminal attacks. In December 2014, there was a legitimate debate in the security community as to whether the massive attack against Sony had been perpetrated by a nation-state with a $20 billion military budget or a couple of guys in a basement somewhere. The internet is the only place where we can’t tell the difference. Everyone uses the same tools, the same techniques and the same tactics.

These attacks are getting larger. The Dyn DDoS attack set a record at 1.2 Tbps. The previous record holder was the attack against cybersecurity journalist Brian Krebs a month prior at 620 Gbps. This is much larger than required to knock the typical website offline. A year ago, it was unheard of. Now it occurs regularly.

The botnets attacking Dyn and Brian Krebs consisted largely of unsecure Internet of Things (IoT) devices ­ webcams, digital video recorders, routers and so on. This isn’t new, either. We’ve already seen internet-enabled refrigerators and TVs used in DDoS botnets. But again, the scale is bigger now. In 2014, the news was hundreds of thousands of IoT devices ­ the Dyn attack used millions. Analysts expect the IoT to increase the number of things on the internet by a factor of 10 or more. Expect these attacks to similarly increase.

The problem is that these IoT devices are unsecure and likely to remain that way. The economics of internet security don’t trickle down to the IoT. Commenting on the Krebs attack last month, I wrote:

The market can’t fix this because neither the buyer nor the seller cares. Think of all the CCTV cameras and DVRs used in the attack against Brian Krebs. The owners of those devices don’t care. Their devices were cheap to buy, they still work, and they don’t even know Brian. 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.

To be fair, one company that made some of the unsecure things used in these attacks recalled its unsecure webcams. But this is more of a publicity stunt than anything else. I would be surprised if the company got many devices back. We already know that the reputational damage from having your unsecure software made public isn’t large and doesn’t last. At this point, the market still largely rewards sacrificing security in favor of price and time-to-market.

DDoS prevention works best deep in the network, where the pipes are the largest and the capability to identify and block the attacks is the most evident. But the backbone providers have no incentive to do this. They don’t feel the pain when the attacks occur and they have no way of billing for the service when they provide it. So they let the attacks through and force the victims to defend themselves. In many ways, this is similar to the spam problem. It, too, is best dealt with in the backbone, but similar economics dump the problem onto the endpoints.

We’re unlikely to get any regulation forcing backbone companies to clean up either DDoS attacks or spam, just as we are unlikely to get any regulations forcing IoT manufacturers to make their systems secure. This is me again:

What this all means is that the IoT will remain insecure unless government steps in and fixes the problem. When we have market failures, government is the only solution. The government could impose security regulations on IoT manufacturers, forcing them to make their devices secure even though their customers don’t care. They could impose liabilities on manufacturers, allowing people like Brian Krebs to sue them. Any of these would raise the cost of insecurity and give companies incentives to spend money making their devices secure.

That leaves the victims to pay. This is where we are in much of computer security. Because the hardware, software and networks we use are so unsecure, we have to pay an entire industry to provide after-the-fact security.

There are solutions you can buy. Many companies offer DDoS protection, although they’re generally calibrated to the older, smaller attacks. We can safely assume that they’ll up their offerings, although the cost might be prohibitive for many users. Understand your risks. Buy mitigation if you need it, but understand its limitations. Know the attacks are possible and will succeed if large enough. And the attacks are getting larger all the time. Prepare for that.

This essay previously appeared on the SecurityIntelligence website.

Security Economics of the Internet of Things

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2016/10/security_econom_1.html

Brian Krebs is a popular reporter on the cybersecurity beat. He regularly exposes cybercriminals and their tactics, and consequently is regularly a target of their ire. Last month, he wrote about an online attack-for-hire service that resulted in the arrest of the two proprietors. In the aftermath, his site was taken down by a massive DDoS attack.

In many ways, this is nothing new. Distributed denial-of-service attacks are a family of attacks that cause websites and other Internet-connected systems to crash by overloading them with traffic. The “distributed” part means that other insecure computers on the Internet — sometimes in the millions­ — are recruited to a botnet to unwittingly participate in the attack. The tactics are decades old; DDoS attacks are perpetrated by lone hackers trying to be annoying, criminals trying to extort money, and governments testing their tactics. There are defenses, and there are companies that offer DDoS mitigation services for hire.

Basically, it’s a size vs. size game. If the attackers can cobble together a fire hose of data bigger than the defender’s capability to cope with, they win. If the defenders can increase their capability in the face of attack, they win.

What was new about the Krebs attack was both the massive scale and the particular devices the attackers recruited. Instead of using traditional computers for their botnet, they used CCTV cameras, digital video recorders, home routers, and other embedded computers attached to the Internet as part of the Internet of Things.

Much has been written about how the IoT is wildly insecure. In fact, the software used to attack Krebs was simple and amateurish. What this attack demonstrates is that the economics of the IoT mean that it will remain insecure unless government steps in to fix the problem. This is a market failure that can’t get fixed on its own.

Our computers and smartphones are as secure as they are because there are teams of security engineers working on the problem. 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 such teams because those companies make a huge amount of money, either directly or indirectly, from their software­ — and, in part, compete on its security. 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.

Even worse, most of these devices don’t have any way to be patched. Even though the source code to the botnet that attacked Krebs has been made public, we can’t update the affected devices. Microsoft delivers security patches to your computer once a month. Apple does it just as regularly, but not on a fixed schedule. But the only way for you to update the firmware in your home router is to throw it away and buy a new one.

The security of our computers and phones also comes from the fact that we replace them regularly. We buy new laptops every few years. We get new phones even more frequently. This isn’t true for all of the embedded IoT systems. They last for years, even decades. We might buy a new DVR every five or ten years. We replace our refrigerator every 25 years. We replace our thermostat approximately never. Already the banking industry is dealing with the security problems of Windows 95 embedded in ATMs. This same problem is going to occur all over the Internet of Things.

The market can’t fix this because neither the buyer nor the seller cares. Think of all the CCTV cameras and DVRs used in the attack against Brian Krebs. The owners of those devices don’t care. Their devices were cheap to buy, they still work, and they don’t even know Brian. 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.

What this all means is that the IoT will remain insecure unless government steps in and fixes the problem. When we have market failures, government is the only solution. The government could impose security regulations on IoT manufacturers, forcing them to make their devices secure even though their customers don’t care. They could impose liabilities on manufacturers, allowing people like Brian Krebs to sue them. Any of these would raise the cost of insecurity and give companies incentives to spend money making their devices secure.

Of course, this would only be a domestic solution to an international problem. The Internet is global, and attackers can just as easily build a botnet out of IoT devices from Asia as from the United States. Long term, we need to build an Internet that is resilient against attacks like this. But that’s a long time coming. In the meantime, you can expect more attacks that leverage insecure IoT devices.

This essay previously appeared on Vice Motherboard.

Slashdot thread.

Here are some of the things that are vulnerable.

EDITED TO ADD (10/17: DARPA is looking for IoT-security ideas from the private sector.