Poisonedwater: an adaptive approach to reducing the reputation ranking error in P2P networks
This paper preliminarily proposes a reputation ranking algorithm called Poisonedwater to resist front peer attack—peers that gain high reputation values by always cooperating with other peers and then promote their malicious friends through passing most of their reputation values to those malicious peers. Specifically, we introduce a notion of Poisoned Water (PW) that iteratively floods from identified malicious peers in the reverse direction of the incoming trust links towards other peers. Furthermore, we propose the concept of Spreading Factor (SF) that is logistically correlated to each peers PW level. Then, we design the new reputation ranking algorithm seamlessly integrated with peers recommendation ability (represented as SF), to infer the more accurate reputation ranking for each peer. simulation results show that, in comparison with Eigentrust, Poisonedwater can significantly reduce the ranking error ratio up to 20%, when P2P systems exist many malicious peers and front peers.
Yufeng Wang Akihiro Nakao
Nanjing University of Posts and Telecommunication,210003,China National Institute of Information and University of Tokyo,Japan National Institute of Information and Communications Technology (NICT),Jap
国际会议
2009 First International Conference on Future Information Networks(第一届未来信息网络国际会议)
北京
英文
263-268
2009-10-14（万方平台首次上网日期，不代表论文的发表时间）