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Identifying fake feedback in cloud trust management systems using feedback evaluation component and Bayesian game model

机译:使用反馈评估组件和贝叶斯博弈模型识别云信任管理系统中的虚假反馈

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摘要

Cloud computing trust management has become an important subject in recent years. Trust management is a difficult and complicated work in cloud computing due to features such as distributed, dynamic and non-transparent environment. Since most trust management frameworks predict trust values based on received feedbacks, the validation and authenticity of feedback are highly necessary. In this paper, two new methods are presented to identify fake feedbacks. One is feedback evaluation component and the other is Bayesian game model. The feedback evaluation component is used to examine the received feedback and identify its probable fake identity. Our results reveal that the feedback evaluation component can correctly identify and rectify fake feedbacks. Bayesian game model is presented to detect malicious users and prevent their feedbacks. Simulation results coincided well with analytical results, indicating that our Bayesian game model can correctly recognize malicious user. Received feedbacks from malicious user are identified as fake feedbacks. Eventually, two new methods were compared.
机译:近年来,云计算信任管理已成为重要的课题。由于分布式,动态和非透明环境等功能,信任管理在云计算中是一项艰巨而复杂的工作。由于大多数信任管理框架都是根据收到的反馈来预测信任值的,因此反馈的验证和可靠性非常必要。本文提出了两种识别伪造反馈的新方法。一个是反馈评估组件,另一个是贝叶斯博弈模型。反馈评估组件用于检查收到的反馈并识别其可能的假身份。我们的结果表明,反馈评估组件可以正确识别和纠正虚假反馈。提出了贝叶斯博弈模型以检测恶意用户并防止其反馈。仿真结果与分析结果非常吻合,表明我们的贝叶斯游戏模型可以正确识别恶意用户。从恶意用户收到的反馈被标识为伪造反馈。最终,比较了两种新方法。

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