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Panel Says Data Mining for Terrorists is an Exercise in Futility

Report, commissioned in part by the DHS, also warns of potential privacy problems

By Jaikumar Vijayan, Computerworld

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The NRC committee didn't look specifically at any counterterrorism-related data mining initiatives, nor did it conduct any direct evaluations of behavioral surveillance tools being used by agencies. Instead, the report is based on a generalized study of the effectiveness of such technologies in identifying potential terrorists.

What the report highlights are the severe limitations of automated data mining techniques for counterterrorism purposes and their potential privacy impacts, said committee member Fred Cate, who is the director of the Center for Applied Cybersecurity Research at Indiana University.

Automated data mining tools typically work by searching through mountains of data in large databases for unusual patterns of activity, which are then used to predict future behavior. The tools have proved to be useful for commercial applications such as detecting payment card fraud and predicting purchasing trends, Cate said.

"We can look at 50,000 people buying television sets and know that many of them are going to be buying a DVD at the same time," Cate said. But using the same techniques to try to identify a potential terrorist is futile because there simply isn't enough historical data upon which to base any predictions, he claimed, adding that there is little information available about patterns that could reliably point to terrorist activity.

On the consumer side, "you have millions of examples of the target data you want to emulate, so you know certain patterns look like fraud," Cate said. "With terrorists, we fortunately don't have too many examples."

And unlike shoppers, terrorists are likely to make deliberate attempts to hide their activities, making it even harder to pick them out using an automated pattern-matching program, according to Cate. As a result, data mining tools generate an unacceptably high rate of false positives when used in counterterrorism applications, he said.

Such tools can prove useful in situations in which they are given specific pieces of information â¬ such as a suspect's name â¬ and asked to look for other data, such as purchases made or places visited by the suspect. That could help show if there is any basis for further action, Cate said.

There are similar problems with many behavioral surveillance tools, Cate contended. Such tools are supposed to help counterterrorism efforts by measuring physiological states, including facial expressions, body temperatures and body language, in order to predict terrorist activity. But there is no evidence that the tools work at all, Cate said. He recommended that at the most, they should be used for preliminary screening purposes only.