Abstract
The current trend of online business enables better and faster service for users and makes it more profitable for merchants. On the other side, the Internet has become the most popular platform for fraudsters to commit online fraud with ease. Several solutions have been proposed in the literature to overcome these online frauds. But, complete and efficient way out from this problem is still in research. In this paper, we have proposed online hybrid model (OHM) which extensively prevents the possibilities of online fraud, and further, if any possibility is present, then it detects and fixes this possibility. The OHM approach is proposed exclusively for in-auction, non-delivery/merchandise and identity theft frauds. OHM further is applicable to several other online frauds. We have evaluated the performance of this model and have shown that OHM is a robust and highly effective online fraud prevention and detection approach.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Prasad, B.: Intelligent techniques for E-Commerce. J. Electron. Commer. Res. 4(2), 65–71 (2003)
U.S. Commerce Department: Forrester Research, Internet Retailer, ComScore., http://www.statisticbrain.com/total-online-sales/
Donga, F., Shatza, S.M., Xub, H.: Combating online in-auction fraud: clues, techniques and challenges. Comput. Sci. Rev. 3(4), 245–258 (2009)
National White Collar crime center: Report on Internet fraud, www.nw3c.org/docs/whitepapers/internet_fraud.pdf?sfvrsn=7, June 2008
Chui, K., Xwick, R.: Auction on the Internet: A Preliminary Study, http://repository.ust.hk/dspace/handle/1783.1/1035, July 2008
Wang, W.L., Hidvègi, Z., Whinston, A.B.: Shill Bidding in English Auctions, Technical report, Emory University, http://oz.stern.nyu.edu/seminar/fa01/1108.pdf (2001)
Wang, W.L., Hidvègi, Z., Whinston, A.B.: Shill Bidding in Multi-Round Online Auctions. In: Proceedings of the 35th Annual Hawaii International Conference on System Sciences, Jan 2002
Porter, R., Shoham, Y.: On cheating in sealed-bid auctions. J. Decis. Support Syst. Special issue of the fourth ACM Conference on Electronic Commerce, 39(1), 41–54 (2005)
Trevathan, J., Read, W.: Detecting Collusive Shill Bidding. In: Proceedings of International Conference on Information Technology: New Generations, pp. 799–808 (2007)
Singh, S.P., Shukla, S.S.P., Rakesh, N., Tyagi, V.: Problem reduction in online payment system using hybrid model. Int. J. Manag. Inf. Technol. 3(3), 62–71 (2011)
Srivastava, A., Kundu, A., Sural, S., Majumdar, A.K.: Credit card fraud detection using hidden Markov model. IEEE Trans. Dependable Secure Comput. 5(1), 1062–1066 (2008)
Internet Crime Complain Center: Internet Crime Report, 2004–2011, http://www.ic3.gov/media/annualreports.aspx
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer India
About this paper
Cite this paper
Mundra, A., Rakesh, N. (2014). Online Hybrid Model for Online Fraud Prevention and Detection. In: Mohapatra, D.P., Patnaik, S. (eds) Intelligent Computing, Networking, and Informatics. Advances in Intelligent Systems and Computing, vol 243. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1665-0_81
Download citation
DOI: https://doi.org/10.1007/978-81-322-1665-0_81
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-1664-3
Online ISBN: 978-81-322-1665-0
eBook Packages: EngineeringEngineering (R0)