Briefs

Data Mining Software Fingers Both Perpetrators and Accomplices

PITTSBURGH, Dec. 5 (AScribe Newswire) -- Computer scientists at Carnegie Mellon University are using data mining techniques to identify perpetrators of fraud among online auction users as well as their otherwise unknown accomplices.

The new method analyzes publicly available histories of transactions posted by online auction sites such as eBay and identifies suspicious online behaviors and dubious associations among users.

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Perpetrators of these frauds have distinctive online behaviors that cause them to be readily purged from an online auction site, said Computer Science Professor Christos Faloutsos. The software developed by his research team - Network Detection via Propagation of Beliefs, or NetProbe - could prevent future frauds by identifying their accomplices, who can lurk on a site indefinitely and enable new generations of fraudsters.

In a test analysis of about one million transactions between almost 66,000 eBay users, NetProbe correctly detected 10 previously identified perpetrators, as well as more than a dozen probable fraudsters and several dozen apparent accomplices.

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