Online in-auction fraud detection using online hybrid model

In this world of emerging technologies, online frauds are rapidly increasing with the increasing popularity of online shopping era. It has been identified in the past research that the shilling is main cause behind online auction frauds. Several researchers have proposed various methods to counter the possibility of shilling in online auction. In this paper we have proposed a mechanism which uses Hidden Markov Model to prevent and detect the online auction from shilling. Hidden Markov model is a statistical model which generates the probability sequence based on the bids applied by users. Further, in this paper we have examined the proposed mechanism by considering the different bidding habits of user and based on that habit we have shown the categorization of different bidding behaviors for different items categories.