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Collusion Based Realization of Trust and Reputation Models in Extreme Fraudulent Environment over Static and Dynamic Wireless Sensor Networks

机译:基于串谋的静态和动态无线传感器网络上极端欺诈环境下信任和信誉模型的实现

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We derive a new representation for the collusive sensor nodes when the underlying fraudulent correlated environment has strong influence on wireless sensor networks performance. We have evaluated collusion effect with respect to static (SW) and dynamic (DW) wireless sensor networks to derive the joint resultant. Moreover accuracy, path length, and energy consumption of sensor node operations are also evaluated. Additionally, we emphasized over the satisfaction evaluation for linguistic fuzzy trust and reputation (LFTM) models in the deployed WSN framework. Finally, simulation analysis has been carried out to prove the validity of our proposal. However, collusion for wireless sensor networks seems intractable with the static and dynamic WSNs when varied with specified number of fraudulent nodes in the scenario.
机译:当潜在的欺诈性关联环境对无线传感器网络性能产生重大影响时,我们为共谋传感器节点派生了新的表示形式。我们评估了相对于静态(SW)和动态(DW)无线传感器网络的串通效应,以得出联合结果。此外,还评估了传感器节点操作的准确性,路径长度和能耗。此外,我们重点介绍了已部署的WSN框架中语言模糊信任和信誉(LFTM)模型的满意度评估。最后,通过仿真分析证明了该方案的有效性。但是,当场景中指定的欺诈节点数量不同时,静态和动态WSN对无线传感器网络的合谋似乎很难解决。

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