Researchers Develop Tool To Combat Internet Auction Fraud
Carnegie Mellon University researchers are using an old adage to develop anti-fraud software for Internet auction sites like eBay: It’s not what you know, it’s who you know.
Sites like eBay rely on users to warn others if they have a bad experience with a seller by rating their transactions. But the CMU researchers said savvy fraudsters get around that by conducting transactions with friends or even themselves, using alternate user names to give themselves high satisfaction ratings – so unsuspecting customers will still try to buy from them.
The CMU software looks for patterns of users who have repeated transactions with one another, and alerts other users that there is a higher probability of having a fraudulent transaction with them.
The researchers analyzed about 1 million transactions involving 66,000 eBay users to develop graphs – known in statistical circles as bipartite cores – that identify users interacting with unusual frequency.
Online auction fraud – when a seller doesn’t deliver goods or sells a defective product – accounted for 12 percent of the 431,000 computer fraud complaints received last year by Consumer Sentinel, the Federal Trade Commission’s consumer fraud and identity theft database.
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