Reliable object rating framework for content sharing system

Recently, with the development of cloud computing, business opportunities emerge gradually for some internet service providers. Content sharing service will grow dramatically with the convenience of consuming cloud resources. But the traditional security threats toward content sharing systems are still not solved. Malicious adversaries can inject a massive number of spam, advertisements, or even viruses into the content sharing systems. Traditional voting based online content ranking and reputation system cannot solve this problem effectively due to Sybil attack and collusive attack. In this paper, with the help of a user-defined trust network, we develop a novel deceiving resistant content rating framework to mitigate pollution attack in content sharing system. The simulation result shows that our system is efficient to aggregate votes from honest peers and is effective to filter out bogus votes from tricky collusive deceivers.