The Workshop on Economics of Information Security will be online this year. Register here.
Entries Tagged "economics of security"
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For decades, we have prized efficiency in our economy. We strive for it. We reward it. In normal times, that’s a good thing. Running just at the margins is efficient. A single just-in-time global supply chain is efficient. Consolidation is efficient. And that’s all profitable. Inefficiency, on the other hand, is waste. Extra inventory is inefficient. Overcapacity is inefficient. Using many small suppliers is inefficient. Inefficiency is unprofitable.
But inefficiency is essential security, as the COVID-19 pandemic is teaching us. All of the overcapacity that has been squeezed out of our healthcare system; we now wish we had it. All of the redundancy in our food production that has been consolidated away; we want that, too. We need our old, local supply chains — not the single global ones that are so fragile in this crisis. And we want our local restaurants and businesses to survive, not just the national chains.
We have lost much inefficiency to the market in the past few decades. Investors have become very good at noticing any fat in every system and swooping down to monetize those redundant assets. The winner-take-all mentality that has permeated so many industries squeezes any inefficiencies out of the system.
This drive for efficiency leads to brittle systems that function properly when everything is normal but break under stress. And when they break, everyone suffers. The less fortunate suffer and die. The more fortunate are merely hurt, and perhaps lose their freedoms or their future. But even the extremely fortunate suffer — maybe not in the short term, but in the long term from the constriction of the rest of society.
Efficient systems have limited ability to deal with system-wide economic shocks. Those shocks are coming with increased frequency. They’re caused by global pandemics, yes, but also by climate change, by financial crises, by political crises. If we want to be secure against these crises and more, we need to add inefficiency back into our systems.
I don’t simply mean that we need to make our food production, or healthcare system, or supply chains sloppy and wasteful. We need a certain kind of inefficiency, and it depends on the system in question. Sometimes we need redundancy. Sometimes we need diversity. Sometimes we need overcapacity.
The market isn’t going to supply any of these things, least of all in a strategic capacity that will result in resilience. What’s necessary to make any of this work is regulation.
First, we need to enforce antitrust laws. Our meat supply chain is brittle because there are limited numbers of massive meatpacking plants — now disease factories — rather than lots of smaller slaughterhouses. Our retail supply chain is brittle because a few national companies and websites dominate. We need multiple companies offering alternatives to a single product or service. We need more competition, more niche players. We need more local companies, more domestic corporate players, and diversity in our international suppliers. Competition provides all of that, while monopolies suck that out of the system.
The second thing we need is specific regulations that require certain inefficiencies. This isn’t anything new. Every safety system we have is, to some extent, an inefficiency. This is true for fire escapes on buildings, lifeboats on cruise ships, and multiple ways to deploy the landing gear on aircraft. Not having any of those things would make the underlying systems more efficient, but also less safe. It’s also true for the internet itself, originally designed with extensive redundancy as a Cold War security measure.
With those two things in place, the market can work its magic to provide for these strategic inefficiencies as cheaply and as effectively as possible. As long as there are competitors who are vying with each other, and there aren’t competitors who can reduce the inefficiencies and undercut the competition, these inefficiencies just become part of the price of whatever we’re buying.
The government is the entity that steps in and enforces a level playing field instead of a race to the bottom. Smart regulation addresses the long-term need for security, and ensures it’s not continuously sacrificed to short-term considerations.
We have largely been content to ignore the long term and let Wall Street run our economy as efficiently as it can. That’s no longer sustainable. We need inefficiency — the right kind in the right way — to ensure our security. No, it’s not free. But it’s worth the cost.
This essay previously appeared in Quartz.
EDITED TO ADD (7/14): A related piece by Dan Geer.
Today is the second day of the thirteenth Workshop on Security and Human Behavior. It’s being hosted by the University of Cambridge, which in today’s world means we’re all meeting on Zoom.
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 forty or so attendees 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.
Our goal is always to maximize discussion and interaction. We do that by putting everyone on panels, and limiting talks to six to eight minutes, with the rest of the time for open discussion. We’ve done pretty well translating this format to video chat, including using the random breakout feature to put people into small groups.
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.
Here are my posts on the first, second, third, fourth, fifth, sixth, seventh, eighth, ninth, tenth, eleventh, and twelfth 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.
Interesting article discussing cyber-warranties, and whether they are an effective way to transfer risk (as envisioned by Akerlof’s “market for lemons”) or a marketing trick.
Warranties must transfer non-negligible amounts of liability to vendors in order to meaningfully overcome the market for lemons. Our preliminary analysis suggests the majority of cyber warranties cover the cost of repairing the device alone. Only cyber-incident warranties cover first-party costs from cyber-attacks — why all such warranties were offered by firms selling intangible products is an open question. Consumers should question whether warranties can function as a costly signal when narrow coverage means vendors accept little risk.
Worse still, buyers cannot compare across cyber-incident warranty contracts due to the diversity of obligations and exclusions. Ambiguous definitions of the buyer’s obligations and excluded events create uncertainty over what is covered. Moving toward standardized terms and conditions may help consumers, as has been pursued in cyber insurance, but this is in tension with innovation and product diversity.
Theoretical work suggests both the breadth of the warranty and the price of a product determine whether the warranty functions as a quality signal. Our analysis has not touched upon the price of these products. It could be that firms with ineffective products pass the cost of the warranty on to buyers via higher prices. Future studies could analyze warranties and price together to probe this issue.
In conclusion, cyber warranties — particularly cyber-product warranties — do not transfer enough risk to be a market fix as imagined in Woods. But this does not mean they are pure marketing tricks either. The most valuable feature of warranties is in preventing vendors from exaggerating what their products can do. Consumers who read the fine print can place greater trust in marketing claims so long as the functionality is covered by a cyber-incident warranty.
Technologists and policymakers largely inhabit two separate worlds. It’s an old problem, one that the British scientist CP Snow identified in a 1959 essay entitled The Two Cultures. He called them sciences and humanities, and pointed to the split as a major hindrance to solving the world’s problems. The essay was influential — but 60 years later, nothing has changed.
When Snow was writing, the two cultures theory was largely an interesting societal observation. Today, it’s a crisis. Technology is now deeply intertwined with policy. We’re building complex socio-technical systems at all levels of our society. Software constrains behavior with an efficiency that no law can match. It’s all changing fast; technology is literally creating the world we all live in, and policymakers can’t keep up. Getting it wrong has become increasingly catastrophic. Surviving the future depends in bringing technologists and policymakers together.
Consider artificial intelligence (AI). This technology has the potential to augment human decision-making, eventually replacing notoriously subjective human processes with something fairer, more consistent, faster and more scalable. But it also has the potential to entrench bias and codify inequity, and to act in ways that are unexplainable and undesirable. It can be hacked in new ways, giving attackers from criminals and nation states new capabilities to disrupt and harm. How do we avoid the pitfalls of AI while benefiting from its promise? Or, more specifically, where and how should government step in and regulate what is largely a market-driven industry? The answer requires a deep understanding of both the policy tools available to modern society and the technologies of AI.
But AI is just one of many technological areas that needs policy oversight. We also need to tackle the increasingly critical cybersecurity vulnerabilities in our infrastructure. We need to understand both the role of social media platforms in disseminating politically divisive content, and what technology can and cannot to do mitigate its harm. We need policy around the rapidly advancing technologies of bioengineering, such as genome editing and synthetic biology, lest advances cause problems for our species and planet. We’re barely keeping up with regulations on food and water safety — let alone energy policy and climate change. Robotics will soon be a common consumer technology, and we are not ready for it at all.
Addressing these issues will require policymakers and technologists to work together from the ground up. We need to create an environment where technologists get involved in public policy – where there is a viable career path for what has come to be called “public-interest technologists.”
The concept isn’t new, even if the phrase is. There are already professionals who straddle the worlds of technology and policy. They come from the social sciences and from computer science. They work in data science, or tech policy, or public-focused computer science. They worked in Bush and Obama’s White House, or in academia and NGOs. The problem is that there are too few of them; they are all exceptions and they are all exceptional. We need to find them, support them, and scale up whatever the process is that creates them.
There are two aspects to creating a scalable career path for public-interest technologists, and you can think of them as the problems of supply and demand. In the long term, supply will almost certainly be the bigger problem. There simply aren’t enough technologists who want to get involved in public policy. This will only become more critical as technology further permeates our society. We can’t begin to calculate the number of them that our society will need in the coming years and decades.
Fixing this supply problem requires changes in educational curricula, from childhood through college and beyond. Science and technology programs need to include mandatory courses in ethics, social science, policy and human-centered design. We need joint degree programs to provide even more integrated curricula. We need ways to involve people from a variety of backgrounds and capabilities. We need to foster opportunities for public-interest tech work on the side, as part of their more traditional jobs, or for a few years during their more conventional careers during designed sabbaticals or fellowships. Public service needs to be part of an academic career. We need to create, nurture and compensate people who aren’t entirely technologists or policymakers, but instead an amalgamation of the two. Public-interest technology needs to be a respected career choice, even if it will never pay what a technologist can make at a tech firm.
But while the supply side is the harder problem, the demand side is the more immediate problem. Right now, there aren’t enough places to go for scientists or technologists who want to do public policy work, and the ones that exist tend to be underfunded and in environments where technologists are unappreciated. There aren’t enough positions on legislative staffs, in government agencies, at NGOs or in the press. There aren’t enough teaching positions and fellowships at colleges and universities. There aren’t enough policy-focused technological projects. In short, not enough policymakers realize that they need scientists and technologists — preferably those with some policy training — as part of their teams.
To make effective tech policy, policymakers need to better understand technology. For some reason, ignorance about technology isn’t seen as a deficiency among our elected officials, and this is a problem. It is no longer okay to not understand how the internet, machine learning — or any other core technologies — work.
This doesn’t mean policymakers need to become tech experts. We have long expected our elected officials to regulate highly specialized areas of which they have little understanding. It’s been manageable because those elected officials have people on their staff who do understand those areas, or because they trust other elected officials who do. Policymakers need to realize that they need technologists on their policy teams, and to accept well-established scientific findings as fact. It is also no longer okay to discount technological expertise merely because it contradicts your political biases.
The evolution of public health policy serves as an instructive model. Health policy is a field that includes both policy experts who know a lot about the science and keep abreast of health research, and biologists and medical researchers who work closely with policymakers. Health policy is often a specialization at policy schools. We live in a world where the importance of vaccines is widely accepted and well-understood by policymakers, and is written into policy. Our policies on global pandemics are informed by medical experts. This serves society well, but it wasn’t always this way. Health policy was not always part of public policy. People lived through a lot of terrible health crises before policymakers figured out how to actually talk and listen to medical experts. Today we are facing a similar situation with technology.
Another parallel is public-interest law. Lawyers work in all parts of government and in many non-governmental organizations, crafting policy or just lawyering in the public interest. Every attorney at a major law firm is expected to devote some time to public-interest cases; it’s considered part of a well-rounded career. No law firm looks askance at an attorney who takes two years out of his career to work in a public-interest capacity. A tech career needs to look more like that.
In his book Future Politics, Jamie Susskind writes: “Politics in the twentieth century was dominated by a central question: how much of our collective life should be determined by the state, and what should be left to the market and civil society? For the generation now approaching political maturity, the debate will be different: to what extent should our lives be directed and controlled by powerful digital systems — and on what terms?”
I teach cybersecurity policy at the Harvard Kennedy School of Government. Because that question is fundamentally one of economics — and because my institution is a product of both the 20th century and that question — its faculty is largely staffed by economists. But because today’s question is a different one, the institution is now hiring policy-focused technologists like me.
If we’re honest with ourselves, it was never okay for technology to be separate from policy. But today, amid what we’re starting to call the Fourth Industrial Revolution, the separation is much more dangerous. We need policymakers to recognize this danger, and to welcome a new generation of technologists from every persuasion to help solve the socio-technical policy problems of the 21st century. We need to create ways to speak tech to power — and power needs to open the door and let technologists in.
This essay previously appeared on the World Economic Forum blog.
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.
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.
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 big money is still being lost 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.
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.
Sidebar photo of Bruce Schneier by Joe MacInnis.