Entries Tagged "risks"

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Buzzword Watch: Prosilience

Summer Fowler at CMU has invented a new word: prosilience:

I propose that we build operationally PROSILIENT organizations. If operational resilience, as we like to say, is risk management “all grown up,” then prosilience is resilience with consciousness of environment, self-awareness, and the capacity to evolve. It is not about being able to operate through disruption, it is about anticipating disruption and adapting before it even occurs—a proactive version of resilience. Nascent prosilient capabilities include exercises (tabletop or technical) that simulate how organizations would respond to a scenario. The goal, however, is to automate, expand, and perform continuous exercises based on real-world indicators rather than on scenarios.

I have long been a big fan of resilience as a security concept, and the property we should be aiming for. I’m not sure prosilience buys me anything new, but this is my first encounter with this new buzzword. It would certainly make for a best-selling business-book title.

Posted on March 2, 2017 at 6:08 AM • View Comments

How the Media Influences Our Fear of Terrorism

Good article that crunches the data and shows that the press’s coverage of terrorism is disproportional to its comparative risk.

This isn’t new. I’ve written about it before, and wrote about it more generally when I wrote about the psychology of risk, fear, and security. Basically, the issue is the availability heuristic. We tend to infer the probability of something by how easy it is to bring examples of the thing to mind. So if we can think of a lot of tiger attacks in our community, we infer that the risk is high. If we can’t think of many lion attacks, we infer that the risk is low. But while this is a perfectly reasonable heuristic when living in small family groups in the East African highlands in 100,000 BC, it fails in the face of modern media. The media makes the rare seem more common by spending a lot of time talking about it. It’s not the media’s fault. By definition, news is “something that hardly ever happens.” But when the coverage of terrorist deaths exceeds the coverage of homicides, we have a tendency to mistakenly inflate the risk of the former while discount the risk of the latter.

Our brains aren’t very good at probability and risk analysis. We tend to exaggerate spectacular, strange and rare events, and downplay ordinary, familiar and common ones. We think rare risks are more common than they are. We fear them more than probability indicates we should.

There is a lot of psychological research that tries to explain this, but one of the key findings is this: People tend to base risk analysis more on stories than on data. Stories engage us at a much more visceral level, especially stories that are vivid, exciting or personally involving.

If a friend tells you about getting mugged in a foreign country, that story is more likely to affect how safe you feel traveling to that country than reading a page of abstract crime statistics will.

Novelty plus dread plus a good story equals overreaction.

It’s not just murders. It’s flying vs. driving: the former is much safer, but accidents are so more spectacular when they occur.

Posted on January 24, 2017 at 6:31 AM • View Comments

Class Breaks

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

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

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

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

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

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

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

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

Posted on January 3, 2017 at 6:50 AM • View Comments

Confusing Security Risks with Moral Judgments

Interesting research that shows we exaggerate the risks of something when we find it morally objectionable.

From an article about and interview with the researchers:

To get at this question experimentally, Thomas and her collaborators created a series of vignettes in which a parent left a child unattended for some period of time, and participants indicated the risk of harm to the child during that period. For example, in one vignette, a 10-month-old was left alone for 15 minutes, asleep in the car in a cool, underground parking garage. In another vignette, an 8-year-old was left for an hour at a Starbucks, one block away from her parent’s location.

To experimentally manipulate participants’ moral attitude toward the parent, the experimenters varied the reason the child was left unattended across a set of six experiments with over 1,300 online participants. In some cases, the child was left alone unintentionally (for example, in one case, a mother is hit by a car and knocked unconscious after buckling her child into her car seat, thereby leaving the child unattended in the car seat). In other cases, the child was left unattended so the parent could go to work, do some volunteering, relax or meet a lover.

Not surprisingly, the parent’s reason for leaving a child unattended affected participants’ judgments of whether the parent had done something immoral: Ratings were over 3 on a 10-point scale even when the child was left unattended unintentionally, but they skyrocketed to nearly 8 when the parent left to meet a lover. Ratings for the other cases fell in between.

The more surprising result was that perceptions of risk followed precisely the same pattern. Although the details of the cases were otherwise the same -­ that is, the age of the child, the duration and location of the unattended period, and so on -­ participants thought children were in significantly greater danger when the parent left to meet a lover than when the child was left alone unintentionally. The ratings for the other cases, once again, fell in between. In other words, participants’ factual judgments of how much danger the child was in while the parent was away varied according to the extent of their moral outrage concerning the parent’s reason for leaving.

Posted on August 25, 2016 at 11:12 AM • View Comments

Financial Cyber Risk Is Not Systemic Risk

This interesting essay argues that financial risks are generally not systemic risks, and instead are generally much smaller. That’s certainly been our experience to date:

While systemic risk is frequently invoked as a key reason to be on guard for cyber risk, such a connection is quite tenuous. A cyber event might in extreme cases result in a systemic crisis, but to do so needs highly fortuitous timing.

From the point of view of policymaking, rather than simply asserting systemic consequences for cyber risks, it would be better if the cyber discussion were better integrated into the existing macroprudential dialogue. To us, the overall discussion of cyber and systemic risk seems to be too focused on IT considerations and not enough on economic consequences.

After all, if there are systemic consequences from cyber risk, the chain of causality will be found in the macroprudential domain.

Posted on June 10, 2016 at 12:56 PM • View Comments

Smart Essay on the Limitations of Anti-Terrorism Security

This is good:

Threats constantly change, yet our political discourse suggests that our vulnerabilities are simply for lack of resources, commitment or competence. Sometimes, that is true. But mostly we are vulnerable because we choose to be; because we’ve accepted, at least implicitly, that some risk is tolerable. A state that could stop every suicide bomber wouldn’t be a free or, let’s face it, fun one.

We will simply never get to maximum defensive posture. Regardless of political affiliation, Americans wouldn’t tolerate the delay or intrusion of an urban mass-transit system that required bag checks and pat-downs. After the 2013 Boston Marathon bombing, many wondered how to make the race safe the next year. A heavier police presence helps, but the only truly safe way to host a marathon is to not have one at all. The risks we tolerate, then, are not necessarily bad bargains simply because an enemy can exploit them.

No matter what promises are made on the campaign trail, terrorism will never be vanquished. There is no ideology, no surveillance, no wall that will definitely stop some 24-year-old from becoming radicalized on the Web, gaining access to guns and shooting a soft target. When we don’t admit this to ourselves, we often swing between the extremes of putting our heads in the sand or losing them entirely.

I am reminded of my own 2006 “Refuse to be Terrorized” essay.

Posted on April 3, 2016 at 7:42 PM • View Comments

Data Is a Toxic Asset

Thefts of personal information aren’t unusual. Every week, thieves break into networks and steal data about people, often tens of millions at a time. Most of the time it’s information that’s needed to commit fraud, as happened in 2015 to Experian and the IRS.

Sometimes it’s stolen for purposes of embarrassment or coercion, as in the 2015 cases of Ashley Madison and the US Office of Personnel Management. The latter exposed highly sensitive personal data that affects security of millions of government employees, probably to the Chinese. Always it’s personal information about us, information that we shared with the expectation that the recipients would keep it secret. And in every case, they did not.

The telecommunications company TalkTalk admitted that its data breach last year resulted in criminals using customer information to commit fraud. This was more bad news for a company that’s been hacked three times in the past 12 months, and has already seen some disastrous effects from losing customer data, including £60 million (about $83 million) in damages and over 100,000 customers. Its stock price took a pummeling as well.

People have been writing about 2015 as the year of data theft. I’m not sure if more personal records were stolen last year than in other recent years, but it certainly was a year for big stories about data thefts. I also think it was the year that industry started to realize that data is a toxic asset.

The phrase “big data” refers to the idea that large databases of seemingly random data about people are valuable. Retailers save our purchasing habits. Cell phone companies and app providers save our location information.

Telecommunications providers, social networks, and many other types of companies save information about who we talk to and share things with. Data brokers save everything about us they can get their hands on. This data is saved and analyzed, bought and sold, and used for marketing and other persuasive purposes.

And because the cost of saving all this data is so cheap, there’s no reason not to save as much as possible, and save it all forever. Figuring out what isn’t worth saving is hard. And because someday the companies might figure out how to turn the data into money, until recently there was absolutely no downside to saving everything. That changed this past year.

What all these data breaches are teaching us is that data is a toxic asset and saving it is dangerous.

Saving it is dangerous because it’s highly personal. Location data reveals where we live, where we work, and how we spend our time. If we all have a location tracker like a smartphone, correlating data reveals who we spend our time with­—including who we spend the night with.

Our Internet search data reveals what’s important to us, including our hopes, fears, desires and secrets. Communications data reveals who our intimates are, and what we talk about with them. I could go on. Our reading habits, or purchasing data, or data from sensors as diverse as cameras and fitness trackers: All of it can be intimate.

Saving it is dangerous because many people want it. Of course companies want it; that’s why they collect it in the first place. But governments want it, too. In the United States, the National Security Agency and FBI use secret deals, coercion, threats and legal compulsion to get at the data. Foreign governments just come in and steal it. When a company with personal data goes bankrupt, it’s one of the assets that gets sold.

Saving it is dangerous because it’s hard for companies to secure. For a lot of reasons, computer and network security is very difficult. Attackers have an inherent advantage over defenders, and a sufficiently skilled, funded and motivated attacker will always get in.

And saving it is dangerous because failing to secure it is damaging. It will reduce a company’s profits, reduce its market share, hurt its stock price, cause it public embarrassment, and­—in some cases—­result in expensive lawsuits and occasionally, criminal charges.

All this makes data a toxic asset, and it continues to be toxic as long as it sits in a company’s computers and networks. The data is vulnerable, and the company is vulnerable. It’s vulnerable to hackers and governments. It’s vulnerable to employee error. And when there’s a toxic data spill, millions of people can be affected. The 2015 Anthem Health data breach affected 80 million people. The 2013 Target Corp. breach affected 110 million.

This toxic data can sit in organizational databases for a long time. Some of the stolen Office of Personnel Management data was decades old. Do you have any idea which companies still have your earliest e-mails, or your earliest posts on that now-defunct social network?

If data is toxic, why do organizations save it?

There are three reasons. The first is that we’re in the middle of the hype cycle of big data. Companies and governments are still punch-drunk on data, and have believed the wildest of promises on how valuable that data is. The research showing that more data isn’t necessarily better, and that there are serious diminishing returns when adding additional data to processes like personalized advertising, is just starting to come out.

The second is that many organizations are still downplaying the risks. Some simply don’t realize just how damaging a data breach would be. Some believe they can completely protect themselves against a data breach, or at least that their legal and public relations teams can minimize the damage if they fail. And while there’s certainly a lot that companies can do technically to better secure the data they hold about all of us, there’s no better security than deleting the data.

The last reason is that some organizations understand both the first two reasons and are saving the data anyway. The culture of venture-capital-funded start-up companies is one of extreme risk taking. These are companies that are always running out of money, that always know their impending death date.

They are so far from profitability that their only hope for surviving is to get even more money, which means they need to demonstrate rapid growth or increasing value. This motivates those companies to take risks that larger, more established, companies would never take. They might take extreme chances with our data, even flout regulations, because they literally have nothing to lose. And often, the most profitable business models are the most risky and dangerous ones.

We can be smarter than this. We need to regulate what corporations can do with our data at every stage: collection, storage, use, resale and disposal. We can make corporate executives personally liable so they know there’s a downside to taking chances. We can make the business models that involve massively surveilling people the less compelling ones, simply by making certain business practices illegal.

The Ashley Madison data breach was such a disaster for the company because it saved its customers’ real names and credit card numbers. It didn’t have to do it this way. It could have processed the credit card information, given the user access, and then deleted all identifying information.

To be sure, it would have been a different company. It would have had less revenue, because it couldn’t charge users a monthly recurring fee. Users who lost their password would have had more trouble re-accessing their account. But it would have been safer for its customers.

Similarly, the Office of Personnel Management didn’t have to store everyone’s information online and accessible. It could have taken older records offline, or at least onto a separate network with more secure access controls. Yes, it wouldn’t be immediately available to government employees doing research, but it would have been much more secure.

Data is a toxic asset. We need to start thinking about it as such, and treat it as we would any other source of toxicity. To do anything else is to risk our security and privacy.

This essay previously appeared on CNN.com.

Posted on March 4, 2016 at 5:32 AM • View Comments

Terrifying Technologies

I’ve written about the difference between risk perception and risk reality. I thought about that when reading this list of Americans’ top technology fears:

  1. Cyberterrorism
  2. Corporate tracking of personal information
  3. Government tracking of personal information
  4. Robots replacing workforce
  5. Trusting artificial intelligence to do work
  6. Robots
  7. Artificial intelligence
  8. Technology I don’t understand

More at the link.

Posted on December 9, 2015 at 1:48 PM • View Comments

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Sidebar photo of Bruce Schneier by Joe MacInnis.