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Sybil attack detection based on signature vectors in VANETs

机译：VANET中基于特征向量的Sybil攻击检测

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摘要

Sybil attack is one of the serious threats in vehicular ad hoc networks (VANETs) because drivers may receive wrong information, which could lead to injury the lives of the drivers and passengers, when they are under Sybil attack. This paper, therefore, presents a novel solution named Sybil attack detection based on signature vectors (SADSIV) in VANETs. Each node gathers the digital signatures in their moving; then our algorithm detects Sybil attack by analysing and comparing vehicle nodes' signature vectors independently under the condition of inadequate infrastructures. We improve the feasibility of our approach through the limited infrastructures at the early deployment stages of VANETs. In addition, the independency and feasibility of our algorithm are more robust than the existing solutions which rely on collaboration of neighbouring nodes. Simulation results show that our method outperforms the existing detection schemes in terms of robustness, detection rate and lower system requirements.
机译：Sybil攻击是车辆自组织网络（VANET）的严重威胁之一，因为驾驶员可能会收到错误的信息，这可能会导致驾驶员和乘客在受到Sybil攻击时丧生。因此，本文提出了一种基于VANET中基于特征向量（SADSIV）的Sybil攻击检测新解决方案。每个节点在移动时都会收集数字签名。然后我们的算法通过在基础设施不足的情况下独立分析和比较车辆节点的特征向量来检测Sybil攻击。在VANET的早期部署阶段，我们通过有限的基础结构来提高我们方法的可行性。另外，我们的算法的独立性和可行性比依赖于相邻节点协作的现有解决方案更加健壮。仿真结果表明，该方法在鲁棒性，检测率和较低的系统要求方面均优于现有的检测方案。

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