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首页> 外文期刊>Wireless Communications Letters, IEEE >A Malicious Node Detection Strategy Based on Fuzzy Trust Model and the ABC Algorithm in Wireless Sensor Network
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A Malicious Node Detection Strategy Based on Fuzzy Trust Model and the ABC Algorithm in Wireless Sensor Network

机译:一种基于模糊信任模型的恶意节点检测策略和无线传感器网络中的ABC算法

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摘要

Wireless sensor network (WSN) nodes owing to their openness, are susceptible to several threats, one of which is dishonest recommendation attacks providing false trust values that favor the attacker. In this letter, a malicious node detection strategy is proposed based on a fuzzy trust model and artificial bee colony algorithm (ABC) (FTM-ABC). The fuzzy trust model (FTM) is introduced to calculate the indirect trust, and the ABC algorithm is applied to optimize the trust model for detecting dishonest recommendation attacks. Besides, fitness function includes recommended deviation and interaction index deviation to enhance the effectiveness. Simulation results reveal the improved FTM-ABC maintains a high recognition rate and a low false-positive rate, even if the number of dishonest nodes reaches 50%.
机译:由于其开放性的无线传感器网络(WSN)节点易受若干威胁的影响,其中一个是不诚实的推荐攻击,提供有利于攻击者的虚假信任值。 在这封信中,基于模糊信任模型和人造群菌落算法(ABC)(FTM-ABC)提出了一种恶意节点检测策略。 引入模糊信任模型(FTM)以计算间接信任,ABC算法应用于优化检测不诚实推荐攻击的信任模型。 此外,健身功能包括推荐的偏差和相互作用指数偏差,以提高效率。 仿真结果揭示了改进的FTM-ABC保持高识别率和低误率,即使不诚实节点的数量达到50%。

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