Personalized Reputation Model in Cooperative Distributed Systems

Reputation systems provide a promising way to build trust relationships between users in distributed cooperation systems, such as file sharing, streaming, distributed computing and social network, through which a user can distinguish good services or users from malicious ones and cooperate with them. However, most reputation models mainly focus on evaluating the qualities of different services in one dimension, but care less about the preferences of different users. This paper proposes a personalized reputation model which provides each user a personalized trust view on others according to his preference. In our approach, we aggregate the users´ preferences with collaborative filtering method and qualify it with user similarity which is integrated into the computing of reputation values. The experimental results suggest that our model can resist possible kinds of malicious behaviors efficiently.