Detection and filtering of collaborative malicious users in reputation system using quality repository approach

H. K. Jnanamurthy, Sanjay Singh

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

4 Citations (Scopus)

Abstract

Online reputation system is gaining popularity as it helps a user to be sure about the quality of a product/service he wants to buy. Nonetheless online reputation system is not immune from attack. Dealing with malicious ratings in reputation systems has been recognized as an important but difficult task. This problem is challenging when the number of true user's ratings is relatively small and unfair ratings plays majority in rated values. In this paper, we have proposed a new method to find malicious users in online reputation systems using Quality Repository Approach (QRA). We mainly concentrated on anomaly detection in both rating values and the malicious users. QRA is very efficient to detect malicious user ratings and aggregate true ratings. The proposed reputation system has been evaluated through simulations and it is concluded that the QRA based system significantly reduces the impact of unfair ratings and improve trust on reputation score with lower false positive as compared to other method used for the purpose.

Original languageEnglish
Title of host publicationProceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013
Pages466-471
Number of pages6
DOIs
Publication statusPublished - 01-12-2013
Event2013 2nd International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013 - Mysore, India
Duration: 22-08-201325-08-2013

Conference

Conference2013 2nd International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013
CountryIndia
CityMysore
Period22-08-1325-08-13

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All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems

Cite this

Jnanamurthy, H. K., & Singh, S. (2013). Detection and filtering of collaborative malicious users in reputation system using quality repository approach. In Proceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013 (pp. 466-471). [6637216] https://doi.org/10.1109/ICACCI.2013.6637216