Abstract
Human cheating has been a barrier to establishing trust among e-commerce users, throughout the last two decades. In particular, in online auctions, since all the transactions occur among anonymous users, trust is difficult to establish and maintain. Shill bidding happens when bidders bid exclusively to inflate (in forward auctions) or deflate (in reverse auctions) prices in online auctions. At present, shill bidding is the most severe and persistent form of cheating in online auctions, but still there are only a few or no established techniques for shill defense at run-time. In this paper, I evaluate the strengths and weaknesses of existing approaches to combating shill bidding. I also propose the ShillFree1 auction system to secure and protect auction systems from shill bidders for both forward and reverse auctions. More precisely, by using a variety of bidding behavior and user history, proposed auction system prevents, monitors and detects shill activities in real time. Moreover, to detect shilling thoroughly I propose IP tracking techniques. The system also takes necessary actions against shill activities at run-time. The experimental results demonstrate that, by prevention, detection and response mechanisms, the proposed auction system keeps the auction users secured from shill bidding and therefore establishes trust among online auction users.
Highlights
Among all online crimes, auction frauds are concurrently one of the most reported, about 35.7% in 2007 (IC3, 2007), and the top five in 2011 (IC3, 2011)
Shill bidding refers to artificial price inflating in case of forward auctions (Trevathan & Read, 2005) and price deflating in reverse auctions in order to generate an interest for the auctioned item
Fraudulent activities like shill bidding are damaging the reputation of online auctions, and have already become a serious problem in e-commerce in terms of security and trust
Summary
Auction frauds are concurrently one of the most reported, about 35.7% in 2007 (IC3, 2007), and the top five in 2011 (IC3, 2011). At present all existing auction houses, and most approaches proposed by researchers have no functionality that detects shill bidding in live auctions and do not take any action until a report is made by an auction user. I first evaluate existing solutions for shill detection in online auctions, identify common patterns and approaches of shill bidders and illustrate them through real auction examples. The ShillFree auction system monitors the bidding process during auctions, detects shilling attempts, and responses in real time while the auction is still running. I report on an experiment involving 10 concurrent auctions where the participating users have predefined roles This experiment demonstrates that the ShillFree system is able to detect all four shill bidders who are shilling in seven auctions. I conclude this paper with a discussion of possible future work
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