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引用次数: 0
摘要
摘要 拒绝服务(DoS)攻击威胁着车载无线网络(VANET)关键组件的可用性。为了确保 VANET 免受 DoS 攻击,人们提出了各种基于信任的集中式和分散式方法。集中式方法的效率较低,因为对中央信任管理器的攻击会导致整体服务失效。相比之下,基于集群的分散式方法由于车辆的高速行驶而导致集群成员的频繁变化,因此面临着开销问题。因此,我们提出了一种基于集群的抗拒绝服务信任模型(DoSRT)。它利用基于速度偏差的聚类改进了分散式信任管理,并根据发送信息的频率检测 DoS 攻击。通过性能评估,我们发现在存在 30% DoS 攻击者的情况下,DoSRT 的精确度、召回率、准确度和 F-Score 分别提高了约 19%、16%、20% 和 17%。
DoSRT: A Denial-of-Service Resistant Trust Model for VANET
Abstract The Denial of Service (DoS) attack threatens the availability of key components of Vehicular Ad-hoc Network (VANET). Various centralized and decentralized trust-based approaches have been proposed to secure the VANET from DoS attack. The centralized approach is less efficient because the attack on the central trust manager leads to the overall failure of services. In comparison, the cluster-based decentralized approach faces overhead because of frequent changes in cluster members due to the high speed of the vehicles. Therefore, we have proposed a cluster-based Denial-of-Service Resistant Trust model (DoSRT). It improves decentralized trust management using speed deviation-based clustering and detects DoS attack based on the frequency of messages sent. Through performance evaluation, we have found that DoSRT improves precision, recall, accuracy, and F-Score by around 19%, 16%, 20%, and 17% in the presence of 30% DoS attackers.