Entries Tagged "economics of security"

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The Economics of Spam

Excellent paper on the economics of spam. The authors infiltrated the Storm worm and monitored its doings.

After 26 days, and almost 350 million e-mail messages, only 28 sales resulted—a conversion rate of well under 0.00001%. Of these, all but one were for male-enhancement products and the average purchase price was close to $100. Taken together, these conversions would have resulted in revenues of $2,731.88—a bit over $100 a day for the measurement period or $140 per day for periods when the campaign was active. However, our study interposed on only a small fraction of the overall Storm network—we estimate roughly 1.5 percent based on the fraction of worker bots we proxy. Thus, the total daily revenue attributable to Storm’s pharmacy campaign is likely closer to $7000 (or $9500 during periods of campaign activity). By the same logic, we estimate that Storm self-propagation campaigns can produce between 3500 and 8500 new bots per day.

Under the assumption that our measurements are representative over time (an admittedly dangerous assumption when dealing with such small samples), we can extrapolate that, were it sent continuously at the same rate, Storm-generated pharmaceutical spam would produce roughly 3.5 million dollars of revenue in a year. This number could be even higher if spam-advertised pharmacies experience repeat business. A bit less than “millions of dollars every day,” but certainly a healthy enterprise.

Of course, the authors point out that it’s dangerous to make these sorts of generalizations:

We would be the first to admit that these results represent a single data point and are not necessarily representative of spam as a whole. Different campaigns, using different tactics and marketing different products will undoubtedly produce different outcomes. Indeed, we caution strongly against researchers using the conversion rates we have measured for these Storm-based campaigns to justify assumptions in any other context.

Spam is all about economics. When sending junk mail costs a dollar in paper, list rental, and postage, a marketer needs a reasonable conversion rate to make the campaign worthwhile. When sending junk mail is almost free, a one in ten million conversion rate is acceptable.

News articles.

Posted on November 12, 2008 at 6:52 AM • View Comments

Horrible Identity Theft Story

This is a story of how smart people can be neutralized through stupid procedures.

Here’s the part of the story where some poor guy’s account get’s completely f-ed. This thief had been bounced to the out-sourced to security so often that he must have made a check list of any possible questions they would ask him. Through whatever means, he managed to get the answers to these questions. Now when he called, he could give us the information we were asking for, but by this point we knew his voice so well that we still tried to get him to security. It worked like this: We put him on hold and dial the extension for security. We get a security rep and start to explain the situation; we tell them he was able to give the right information, but that we know is the same guy that’s been calling for weeks and we are certain he is not the account holder. They begrudgingly take the call. Minutes later another one of us gets a call from a security rep saying they are giving us a customer who has been cleared by them. And here the thief was back in our department. For those of us who had come to know him, the fight waged on night after night.

Posted on October 30, 2008 at 12:10 PM • View Comments

Barack Obama Discusses Security Trade-Offs

I generally avoid commenting on election politics—that’s not what this blog is about—but this comment by Barack Obama is worth discussing:

[Q] I have been collecting accounts of your meeting with David Petraeus in Baghdad. And you had [inaudible] after he had made a really strong pitch [inaudible] for maximum flexibility. A lot of politicians at that moment would have said [inaudible] but from what I hear, you pushed back.

[BO] I did. I remember the conversation, pretty precisely. He made the case for maximum flexibility and I said you know what if I were in your shoes I would be making the exact same argument because your job right now is to succeed in Iraq on as favorable terms as we can get. My job as a potential commander in chief is to view your counsel and your interests through the prism of our overall national security which includes what is happening in Afghanistan, which includes the costs to our image in the middle east, to the continued occupation, which includes the financial costs of our occupation, which includes what it is doing to our military. So I said look, I described in my mind at list an analogous situation where I am sure he has to deal with situations where the commanding officer in [inaudible] says I need more troops here now because I really think I can make progress doing x y and z. That commanding officer is doing his job in Ramadi, but Petraeus’s job is to step back and see how does it impact Iraq as a whole. My argument was I have got to do the same thing here. And based on my strong assessment particularly having just come from Afghanistan were going to have to make a different decision. But the point is that hopefully I communicated to the press my complete respect and gratitude to him and Proder who was in the meeting for their outstanding work. Our differences don’t necessarily derive from differences in sort of, or my differences with him don’t derive from tactical objections to his approach. But rather from a strategic framework that is trying to take into account the challenges to our national security and the fact that we’ve got finite resources.

I have made this general point again and again—about airline security, about terrorism, about a lot of things—that the person in charge of the security system can’t be the person who decides what resources to devote to that security system. The analogy I like to use is a company: the VP of marketing wants all the money for marketing, the VP of engineering wants all the money for engineering, and so on; and the CEO has to balance all of those needs and do what’s right for the company. So of course the TSA wants to spend all this money on new airplane security systems; that’s their job. Someone above the TSA has to balance the risks to airlines with the other risks our country faces and allocate budget accordingly. Security is a trade-off, and that trade-off has to be made by someone with responsibility over all aspects of that trade-off.

I don’t think I’ve ever heard a politician make this point so explicitly.

EDITED TO ADD (10/27): This is a security blog, not a political blog. As such, I have deleted all political comments below—on both sides.. You are welcome to discuss this notion of security trade-offs and the appropriate level to make them, but not the election or the candidates.

Posted on October 27, 2008 at 6:31 AM • View Comments

ANSI Cyberrisk Calculation Guide

Interesting:

In a nutshell, the guide advocates that organizations calculate cyber security risks and costs by asking questions of every organizational discipline that might be affected: legal, compliance, business operations, IT, external communications, crisis management, and risk management/insurance. The idea is to involve everyone who might be affected by a security breach and collect data on the potential risks and costs.

Once all of the involved parties have weighed in, the guide offers a mathematical formula for calculating financial risk: Essentially, it is a product of the frequency of an event multiplied by its severity, multiplied by the likelihood of its occurrence. If risk can be transferred to other organizations, that part of the risk can be subtracted from the net financial risk.

Guide is here.

Posted on October 24, 2008 at 7:04 AM • View Comments

Cost/Benefit of Terrorism Security

“The terrifying cost of feeling safer,” from the Sydney Morning Herald:

Sandler and his colleagues conducted an analysis of the costs and benefits of five different approaches to combating terrorism. I must warn you that, because of the dearth of information, this study is even more reliant on assumptions than usual. Even so, in three cases the cost of the action so far exceeds the benefits that doubts about the reliability of the estimates recede.

Because the loss of life is so low, they measure the benefits of successful counter-terrorism measures in terms of loss of gross domestic product avoided. Trouble is, terrorism does little to disrupt economic growth, as even September 11 demonstrated.

Using the case of the US, Sandler estimates that simply continuing the present measures involves costs exceeding benefits by a factor of at least 10. Adopting additional defensive measures (such as stepping up security at valuable targets) would, at best, entail costs 3.5 times the benefits. Taking more pro-active measures (such as invading Afghanistan) would have costs at least eight times the benefits.

According to Sandler, only greater international co-operation, or adopting more sensitive foreign policies to project a more positive image abroad, could produce benefits greater than their (minimal) costs.

What’s that? You don’t care what it costs because no one can put a value on saving a human life? Heard of opportunity cost? Taxpayers’ money we waste on excessive counter-terrorism measures is money we can’t spend reducing the gap between white and indigenous health—or, if that doesn’t appeal, on buying Olympic medals.

Posted on September 12, 2008 at 6:32 AM • View Comments

News from the Rock Phish Gang

Definitely interesting:

Based in Europe, the Rock Phish group is a criminal collective that has been targeting banks and other financial institutions since 2004. According to RSA, they are responsible for half of the worldwide phishing attacks and have siphoned tens of millions of dollars from individuals’ bank accounts. The group got its name from a now discontinued quirk in which the phishers used directory paths that contained the word “rock.”

The first sign the group was expanding operations came in April, when it introduced a trojan known alternately as Zeus or WSNPOEM, which steals sensitive financial information in transit from a victim’s machine to a bank. Shortly afterward, the gang added more crimeware, including a custom-made botnet client that was spread, among other means, using the Neosploit infection kit.

[…]

Soon, additional signs appeared pointing to a partnership between Rock Phishers and Asprox. Most notably, the command and control server for the custom Rock Phish crimeware had exactly the same directory structure of many of the Asprox servers, leading RSA researchers to believe Rock Phish and Asprox attacks were using at least one common server. (Researchers from Damballa were able to confirm this finding after observing malware samples from each of the respective botnets establish HTTP proxy server connections to a common set of destination IPs.)

Posted on September 10, 2008 at 7:47 AM • View Comments

Security ROI

Return on investment, or ROI, is a big deal in business. Any business venture needs to demonstrate a positive return on investment, and a good one at that, in order to be viable.

It’s become a big deal in IT security, too. Many corporate customers are demanding ROI models to demonstrate that a particular security investment pays off. And in response, vendors are providing ROI models that demonstrate how their particular security solution provides the best return on investment.

It’s a good idea in theory, but it’s mostly bunk in practice.

Before I get into the details, there’s one point I have to make. “ROI” as used in a security context is inaccurate. Security is not an investment that provides a return, like a new factory or a financial instrument. It’s an expense that, hopefully, pays for itself in cost savings. Security is about loss prevention, not about earnings. The term just doesn’t make sense in this context.

But as anyone who has lived through a company’s vicious end-of-year budget-slashing exercises knows, when you’re trying to make your numbers, cutting costs is the same as increasing revenues. So while security can’t produce ROI, loss prevention most certainly affects a company’s bottom line.

And a company should implement only security countermeasures that affect its bottom line positively. It shouldn’t spend more on a security problem than the problem is worth. Conversely, it shouldn’t ignore problems that are costing it money when there are cheaper mitigation alternatives. A smart company needs to approach security as it would any other business decision: costs versus benefits.

The classic methodology is called annualized loss expectancy (ALE), and it’s straightforward. Calculate the cost of a security incident in both tangibles like time and money, and intangibles like reputation and competitive advantage. Multiply that by the chance the incident will occur in a year. That tells you how much you should spend to mitigate the risk. So, for example, if your store has a 10 percent chance of getting robbed and the cost of being robbed is $10,000, then you should spend $1,000 a year on security. Spend more than that, and you’re wasting money. Spend less than that, and you’re also wasting money.

Of course, that $1,000 has to reduce the chance of being robbed to zero in order to be cost-effective. If a security measure cuts the chance of robbery by 40 percent—to 6 percent a year—then you should spend no more than $400 on it. If another security measure reduces it by 80 percent, it’s worth $800. And if two security measures both reduce the chance of being robbed by 50 percent and one costs $300 and the other $700, the first one is worth it and the second isn’t.

The Data Imperative

The key to making this work is good data; the term of art is “actuarial tail.” If you’re doing an ALE analysis of a security camera at a convenience store, you need to know the crime rate in the store’s neighborhood and maybe have some idea of how much cameras improve the odds of convincing criminals to rob another store instead. You need to know how much a robbery costs: in merchandise, in time and annoyance, in lost sales due to spooked patrons, in employee morale. You need to know how much not having the cameras costs in terms of employee morale; maybe you’re having trouble hiring salespeople to work the night shift. With all that data, you can figure out if the cost of the camera is cheaper than the loss of revenue if you close the store at night—assuming that the closed store won’t get robbed as well. And then you can decide whether to install one.

Cybersecurity is considerably harder, because there just isn’t enough good data. There aren’t good crime rates for cyberspace, and we have a lot less data about how individual security countermeasures—or specific configurations of countermeasures—mitigate those risks. We don’t even have data on incident costs.

One problem is that the threat moves too quickly. The characteristics of the things we’re trying to prevent change so quickly that we can’t accumulate data fast enough. By the time we get some data, there’s a new threat model for which we don’t have enough data. So we can’t create ALE models.

But there’s another problem, and it’s that the math quickly falls apart when it comes to rare and expensive events. Imagine you calculate the cost—reputational costs, loss of customers, etc.—of having your company’s name in the newspaper after an embarrassing cybersecurity event to be $20 million. Also assume that the odds are 1 in 10,000 of that happening in any one year. ALE says you should spend no more than $2,000 mitigating that risk.

So far, so good. But maybe your CFO thinks an incident would cost only $10 million. You can’t argue, since we’re just estimating. But he just cut your security budget in half. A vendor trying to sell you a product finds a Web analysis claiming that the odds of this happening are actually 1 in 1,000. Accept this new number, and suddenly a product costing 10 times as much is still a good investment.

It gets worse when you deal with even more rare and expensive events. Imagine you’re in charge of terrorism mitigation at a chlorine plant. What’s the cost to your company, in money and reputation, of a large and very deadly explosion? $100 million? $1 billion? $10 billion? And the odds: 1 in a hundred thousand, 1 in a million, 1 in 10 million? Depending on how you answer those two questions—and any answer is really just a guess—you can justify spending anywhere from $10 to $100,000 annually to mitigate that risk.

Or take another example: airport security. Assume that all the new airport security measures increase the waiting time at airports by—and I’m making this up—30 minutes per passenger. There were 760 million passenger boardings in the United States in 2007. This means that the extra waiting time at airports has cost us a collective 43,000 years of extra waiting time. Assume a 70-year life expectancy, and the increased waiting time has “killed” 620 people per year—930 if you calculate the numbers based on 16 hours of awake time per day. So the question is: If we did away with increased airport security, would the result be more people dead from terrorism or fewer?

Caveat Emptor

This kind of thing is why most ROI models you get from security vendors are nonsense. Of course their model demonstrates that their product or service makes financial sense: They’ve jiggered the numbers so that they do.

This doesn’t mean that ALE is useless, but it does mean you should 1) mistrust any analyses that come from people with an agenda and 2) use any results as a general guideline only. So when you get an ROI model from your vendor, take its framework and plug in your own numbers. Don’t even show the vendor your improvements; it won’t consider any changes that make its product or service less cost-effective to be an “improvement.” And use those results as a general guide, along with risk management and compliance analyses, when you’re deciding what security products and services to buy.

This essay previously appeared in CSO Magazine.

Posted on September 2, 2008 at 6:05 AM • View Comments

Red Light Cameras Don't Work

Interesting: the solution to one problem causes another.

“The rigorous studies clearly show red-light cameras don’t work,” said lead author Barbara Langland-Orban, professor and chair of health policy and management at the USF College of Public Health. “Instead, they increase crashes and injuries as drivers attempt to abruptly stop at camera intersections.”

Comprehensive studies from North Carolina, Virginia, and Ontario have all reported cameras are associated with increases in crashes. The study by the Virginia Transportation Research Council also found that cameras were linked to increased crash costs. The only studies that conclude cameras reduced crashes or injuries contained “major research design flaws,” such as incomplete data or inadequate analyses, and were always conducted by researchers with links to the Insurance Institute for Highway Safety. The IIHS, funded by automobile insurance companies, is the leading advocate for red-light cameras since insurance companies can profit from red-light cameras by way of higher premiums due to increased crashes and citations.

And, of course, the agenda of the government is to increase revenue due to fines:

A 2001 paper by the Office of the Majority Leader of the U.S. House of Representatives reported that red-light cameras are “a hidden tax levied on motorists.” The report came to the same conclusions that all of the other valid studies have, that red-light cameras are associated with increased crashes and that the timings at yellow lights are often set too short to increase tickets for red-light running. That’s right, the state actually tampers with the yellow light settings to make them shorter, and more likely to turn red as you’re driving through them.

In fact, six U.S. cities have been found guilty of shortening the yellow light cycles below what is allowed by law on intersections equipped with cameras meant to catch red-light runners. Those local governments have completely ignored the safety benefit of increasing the yellow light time and decided to install red-light cameras, shorten the yellow light duration, and collect the profits instead.

The cities in question include Union City, CA, Dallas and Lubbock, TX, Nashville and Chattanooga, TN, and Springfield, MO, according to Motorists.org, which collected information from reports from around the country.

Posted on August 25, 2008 at 12:19 PM • View Comments

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Sidebar photo of Bruce Schneier by Joe MacInnis.