Detecting Malicious Users In P2P Streaming Systems By Using Feedback Correlations

摘要

The trust and reputation models were introduced to restrain the impacts caused by rational but selfish peers in P2P streaming systems. However, these models face with two major challenges from dishonest feedback and strategic altering behaviors. To answer these challenges, we present a global trust model based on network community, evaluation correlations, and punishment mechanism. We also propose a two-layered overlay to provide the function of peers behaviors collection and malicious detection. The simulation results show that our trust framework can successfully filter out dishonest feedbacks by using correlation coefficients.