基于节点兴趣相似度的P2P信任模型

Li Yang, Yu-sen Zhang, Chang-you Xing, Zhang Tao
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引用次数: 8

摘要

基于信誉的信任模型是解决P2P网络中节点间不合作和恶意行为的重要途径。现有的单一信任模型隐藏了节点在不同领域的行为细节,无法防御恶意节点的战略攻击。提出了一种基于节点兴趣相似度的P2P信任模型(isttrust),该模型考虑了节点在每个兴趣域的兴趣偏差和声誉,并利用兴趣域声誉向量来维护节点在特定兴趣域的行为。在计算其他节点的信誉时,利用节点之间的兴趣相似度来加权域本地信任推荐,从而抑制恶意节点的诽谤和夸大攻击,并给予良好的节点在多个领域提供贡献的激励。仿真结果表明,itrust算法比EigenRep算法更高效、更安全。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A node Interest Similarity based P2P Trust Model
Reputation based trust model is an important way to solve the non-cooperation and malicious behaviors of nodes in P2P networks. Current single trust model hides the behavior details of nodes in different field, thus it cannot defend the strategic attack of malicious nodes. A node Interest Similarity based P2P Trust Model (ISTrust) is proposed, which takes both node interest bias and reputations in each interest domain into consideration, and uses interest domain reputation vector to maintain the behaviors of node in specific interest domain. When calculating reputations of other nodes, ISTrust uses interest similarity between nodes to weight domain local trust recommendation, thus restrains the slandering and exaggeration attacks of malicious nodes, and gives good nodes incentives to provide contribution in many domains. Simulation results show that ISTrust is more efficient and secure than EigenRep.
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