Threat Analysis and malicious user detection in reputation systems using Mean Bisector Analysis and Cosine Similarity (MBACS)

H. K. Jnanamurthy, Chirag Warty, Sanjay Singh

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

2 Citations (Scopus)

Abstract

Feedback reputation systems are gaining popularity as dealing with unfair ratings in reputation systems has been recognized as an important but difficult task. This problem is challenging when the number of true user ratings is relatively small and unfair ratings plays majority in rated values. In this paper, we propose a new method to find malicious users in online reputation systems using Mean Bisector Analysis and Cosine Similarity (MBACS). Here the effort is mainly concentrated on abnormals in both rating-values domain and the malicious users domain. MBACS is very efficient to detect malicious user ratings and aggregate trustful ratings. The proposed reputation system is evaluated through simulations, MBACS system can significantly reduce the impact of unfair ratings.

Original languageEnglish
Title of host publication2013 Annual IEEE India Conference, INDICON 2013
DOIs
Publication statusPublished - 01-12-2013
Event10th Annual Conference of the IEEE India Council, INDICON 2013 - Mumbai, India
Duration: 13-12-201315-12-2013

Conference

Conference10th Annual Conference of the IEEE India Council, INDICON 2013
CountryIndia
CityMumbai
Period13-12-1315-12-13

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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