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Intelligent Computing, Networking, and Informatics pp 805–815Cite as

Online Hybrid Model for Online Fraud Prevention and Detection

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Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 243)

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.

Keywords

  • Auction fraud
  • Credit card fraud
  • Identity theft fraud
  • HMM

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Jaypee University of Information Technology, Waknaghat, Solan, 173234, Himachal Pradesh, India

    Ankit Mundra & Nitin Rakesh

Authors
  1. Ankit Mundra
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  2. Nitin Rakesh
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Corresponding author

Correspondence to Ankit Mundra .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, National Institute of Technology Rourkela, Rourkela, Orissa, India

    Durga Prasad Mohapatra

  2. Computer Science and Engineering, SOA University, Bhubaneswar, India

    Srikanta Patnaik

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© 2014 Springer India

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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

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  • 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)

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