Detection of Fraudsters in Electronic Auction Using Hidden Markov Model with X-Means Clustering Algorithm 1 T.S. Swathy Lakshmy, 2 Aswathi Sivadasan and 3 L. Nitha 1 Department of Computer Science and I.T, School of Arts and Sciences, Amrita University, Kochi. swathylakshmy1919@gmail.com 2 Department of Computer Science and I.T, School of Arts and Sciences, Amrita University, Kochi. aswathisiva94@gmail.com 3 Department of Computer Science and I.T, School of Arts and Sciences, Amrita University, Kochi. nitha.leeladharan@gmail.com Abstract In this world of new innovations, electronic auction had a vital role in our daily life. Because of its amazing features, people are addicted to online sites. On the other hand, online sites are subjected to fraudulent activities. In this paper, we are detecting fraudulent activities of online auction by analyzing the history of customer’s transaction. In order to detect the fraudsters that demolish the essence of electronic auction, we have proposed an improved mechanism using Hidden Markov Model (HMM) and X-mean clustering algorithm. This algorithm is a modified version of K-means clustering algorithm, which solves the problems using the K-means approach. Hidden Markov model is a statistical model that gives approximate value by accepting less input and it provides a probabilistic behavior of fake bids in online auction. We have compared the results of current model that uses Hidden Markov Model and K-means with our proposed model. By examining the result, it is clear that our model is more efficient in terms of accuracy and consumes less time. Key Words:Online auction, fraud detection, X-means clustering, hidden markov model (HMM). International Journal of Pure and Applied Mathematics Volume 114 No. 11 2017, 157-165 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu Special Issue ijpam.eu 157