Economics Of Cybercrime
DINEI FLORENCIO & CORMAC HERLEY | NYT NEWS SERVICE
IN less than 15 years, cybercrime has moved from obscurity to the spotlight of consumer, corporate and national security concerns. Popular accounts suggest that cybercrime is large, rapidly growing, profitable and highly evolved; annual loss estimates range from billions to nearly $1 trillion.
While other industries stagger under the weight of recession, in cybercrime, business is apparently booming.
Yet in terms of economics, there’s something very wrong with this picture.
Generally the demand for easy money outstrips supply. Is cybercrime an exception? If getting rich were as simple as downloading and running software, wouldn’t more people do it, and thus drive down returns? We have examined cybercrime from an economics standpoint and found a story at odds with the conventional wisdom. A few criminals do well, but cybercrime is a relentless, low-profit struggle for the majority. Spamming, stealing passwords or pillaging bank accounts might appear a perfect business.
Cyber criminals can be thousands of miles from the scene of the crime, they can download everything they need online, and there’s little training or capital outlay required. Almost anyone can do it.
Well, not really. Structurally, the economics of cybercrimes like spam and password-stealing are the same as those of fishing. Economics long ago established that common-access resources make for bad business opportunities.No matter how large the original opportunity, new entrants continue to arrive, driving the average return ever downward. Just as unregulated fish stocks are driven to exhaustion, there is never enough ‘easy money’ to go around.
How do we reconcile this view with stories that cybercrime rivals the global drug trade in size? One recent estimate placed annual direct consumer losses at $114 billion worldwide. It turns out, however, that such widely circulated cybercrime estimates are generated using absurdly bad statistical methods, making them wholly unreliable.
Most cybercrime estimates are based on surveys of consumers and companies.
They borrow credibility from election polls, which we have learned to trust. However, when extrapolating from a surveyed group to the overall population, there is an enormous difference between preference questions (which are used in election polls) and numerical questions (as in cybercrime surveys).
For one thing, in numeric surveys, errors are almost always upward: Since the amounts of estimated losses must be positive, there’s no limit on the upside, but zero is a hard limit on the downside. As a consequence, respondent errors or outright lies cannot be canceled out. Even worse, errors get amplified when researchers scale between the survey group and the overall population.
Suppose we asked 5,000 people to report their cybercrime losses, which we will then extrapolate over a population of 200 million.Every dollar claimed gets multiplied by 40,000. A single individual who falsely claims $25,000 in losses adds a spurious $1 billion to the estimate. And since no one can claim negative losses, the error can’t be canceled.
The cybercrime surveys we have examined exhibit exactly this pattern of enormous, unverified outliers dominating the data. In some, 90 percent of the estimate appears to come from the answers of one or two individuals. In a 2006 survey of identity theft by the Federal Trade Commission, two respondents gave answers that would have added $37 billion to the estimate, dwarfing that of all other respondents combined.
This is not simply a failure to achieve perfection or a matter of a few percentage points; it is the rule, rather than the exception. Among dozens of surveys, from security vendors, industry analysts and government agencies, we have not found one that appears free of this upward bias. As a result, we have very little idea of the size of cybercrime losses.
A cybercrime where profits are slim and competition is ruthless also offers simple explanations of facts that are otherwise puzzling. Credentials and stolen credit-card numbers are offered for sale at pennies on the dollar for the simple reason that they are hard to monetise. Cybercrime billionaires are hard to locate because there aren’t any.
Few people know anyone who has lost substantial money because victims are far rarer than the exaggerated estimates would imply.
Of course, this is not a zero-sum game: the difficulty of getting rich for bad guys doesn’t imply that the consequences are small for good guys. Profit estimates may be enormously exaggerated, but it would be a mistake not to consider cybercrime a serious problem.
Those who’ve had their computers infected with malware or had their email passwords stolen know that cleaning up the mess dwarfs any benefit received by hackers. Many measures that tax the overall population, from baroque password policies to pop-up warnings to ‘prove you are human’ tests, wouldn’t be necessary if cybercriminals weren’t constantly abusing the system.
Still, that doesn’t mean exaggerated loss estimates should be acceptable.
Rather, there needs to be a new focus on how consumers and policymakers assess the problem.
The harm experienced by users rather than the (much smaller) gain achieved by hackers is the true measure of the cybercrime problem. Surveys that perpetuate the myth that cybercrime makes for easy money are harmful because they encourage hopeful, if misinformed, new entrants, who generate more harm for users than profit for themselves.