PeerStrategy: A local strategy for peers to evaluate their neighbors
Trust management is receiving more and more attention recently, which is also critical to the wide acceptance of P2P computing. Some applications, especially E-commerce, need a mechanism to evaluate the trustworthiness of participating peers and combat the dishonest, selfish, and malicious behavior. Reputation-based trust mechanism has been identified in the literature as a viable solution to the problem. Most reputationbased systems rely on personal feedbacks to generate global trust. Therefore, its important for feedbacks to reflect peers character, good or malicious. However, the existence of strategic peers who cheat out of several interactions and human judgment error is a great challenge. Current personal feedback calculation methods cant defend strategic peers as well as neglecting human judgment error. In this paper, we propose a local strategy, named PeerStrategy, to calculate personal feedbacks about neighbors, which can combat strategic peers as well as tolerate the influence of human judgment error. We compare current feedback calculation methods with PeerStrategy in the same experiment settings and find PeerStrategy performs the best. Our simulation shows that PeerStrategy can significantly diminish estimation error in global trust estimation by way of improving the accuracy of feedbacks.
Peer-to-Peer networks Trust management Reputation system Personal feedback
Zhen Xie Jingping Bi
Institute of Computing Technology Chinese Academy of Sciences Beijing, China
国际会议
第七届网格与协同计算国际会议(Seventh International Conference on Grid and Cooperative Computing GCC 2008)
深圳
英文
386-391
2008-10-24（万方平台首次上网日期，不代表论文的发表时间）