Interesting article on Technology Review
PITTSBURGH (AP) — Carnegie Mellon University researchers are relying on an old adage to develop anti-fraud software for Internet auction sites: It is not what you know, it is who you know.
At sites like eBay, users warn each other 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 dealings with one another, and alerts other users that there is a higher probability of having a fraudulent transaction with them.”
There’s a lot of commonsense solutions out there, like being more careful about how you screen the sellers,” said Duen Horng ”Polo” Chau, the research associate who developed the software with computer science professor Christos Faloutsos and two other students. ”But because I’m an engineering student, I wanted to come up with a systematic approach” to identify those likely to commit fraud.
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. They plan to publish a paper on their findings early next year and, perhaps, market their software to eBay or otherwise make it available to people who shop online.Catherine England, an eBay spokeswoman, said the company was not aware of the research and would not comment on it. But England said protecting the company’s more than 200 million users from fraud was a top priority.