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基于连续行为观察的P2P网络中邻居评价模型
  • 期刊名称:计算机研究与发展
  • 时间:0
  • 页码:1098-1106
  • 语言:中文
  • 分类:TP393.01[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
  • 作者机构:[1]中国科学院计算技术研究所,北京100190, [2]中国科学院研究生院,北京100049
  • 相关基金:国家自然科学基金项目(60803138)
  • 相关项目:网络路由策略一致性验证方法研究
中文摘要:

基于荣誉的信任机制是对P2P网络节点行为进行评价的重要手段,用来保证P2P网络应用的健康进行.信任机制在对一个节点进行评价时需要获得其他节点的局部信任值信息.目前局部信任值的计算由于不考虑策略节点和人类评价误差两种重要因素的影响,难以准确反映网络节点的特征.提出了一种P2P网络中邻居行为的评价模型PeerStrategy,该模型使用确定的有限状态机(DFA)对邻居连续行为的状态变化进行刻画.通过关注邻居在任意连续行为中引起负面评价的概率,既能够较为准确地发现网络中的策略节点,又能够容忍一定程度的人类评价误差.仿真实验表明,该模型显著提高了局部信任值的准确度,并降低了对全局信任值估计误差影响,明显优于当前的其他局部信任值计算方法.

英文摘要:

Reputation based trust mechanism has been identified as an effective method to evaluate peers' behavior and which is employed to secure the applications in P2P network. Trust mechanism is such a mechanism that relies on other peers' reports, which are also called local trust, to evaluate a designated peer. However, the existence of strategic peers and human judgment error is a big challenge, which makes the local trust hard to reflect peers' type. Furthermore, it increases the estimation error of global trust. The authors propose a new model, called PeerStrategy, to evaluate neighbor's behavior in P2P network. This model explores deterministic finite automaton (DFA) to describe the variance of neighbor's consecutive behaviors. The DFA consists of seven states and it transits between states by neighbor's performance in the interactions. By examining the probability of negative behaviors in any consecutive ones, the model can not only detect strategic peers accurately but also tolerate human judgment error. As a result, this model improves the accuracy of local trust, and what's more, it decreases the estimation error of global trust. The simulation shows that this model improves the accuracy of local trust considerately and also diminishes the influence on the estimation error of global trust, and it performs the best compared with other current methods.

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