Toward a comprehensive model in internet auction fraud detection

Bin Zhang, Yi Zhou, Christos Faloutsos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

32 Scopus citations

Abstract

Fraud detection has become a common concern of the online auction websites. Fraudsters often manipulate reputation systems and commit non-delivery fraud. To deal with fraud in group behavior we consider network level features, such as users' beliefs of other users. In this paper we use the loopy belief propagation algorithm and apply it to network level fraud detection, classifying fraudsters, accomplices, as well as honest users. Our method shows good classification accuracy using real data.

Original languageEnglish (US)
Title of host publicationProceedings of the 41st Annual Hawaii International Conference on System Sciences 2008, HICSS
DOIs
StatePublished - Sep 16 2008
Externally publishedYes
Event41st Annual Hawaii International Conference on System Sciences 2008, HICSS - Big Island, HI, United States
Duration: Jan 7 2008Jan 10 2008

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
ISSN (Print)1530-1605

Other

Other41st Annual Hawaii International Conference on System Sciences 2008, HICSS
CountryUnited States
CityBig Island, HI
Period1/7/081/10/08

ASJC Scopus subject areas

  • Engineering(all)

Fingerprint Dive into the research topics of 'Toward a comprehensive model in internet auction fraud detection'. Together they form a unique fingerprint.

  • Cite this

    Zhang, B., Zhou, Y., & Faloutsos, C. (2008). Toward a comprehensive model in internet auction fraud detection. In Proceedings of the 41st Annual Hawaii International Conference on System Sciences 2008, HICSS [4438782] (Proceedings of the Annual Hawaii International Conference on System Sciences). https://doi.org/10.1109/HICSS.2008.455