Filtering Out Unfair Ratings in Bayesian Reputation Systems

Abstract

The quality of a reputation system depends on the integrity of the ratings it receives as input. A fundamental problem is that a rater can rate an agent more positively or more negatively than the real experience with the agent would dictate. When ratings are provided by agents outside the control of the relying party, it is a priori impossible to know when a rater provides such unfair ratings. However, it is often the case that unfair ratings have a different statistical pattern than fair ratings. This paper uses that idea, and describes a statistical filtering technique for excluding unfair ratings, and illustrates its effectiveness through simulations.

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