车载自组网中多重干扰攻击者数量估计

Liang Pang, Pengze Guo, Xiao Chen, Jiabin Li, Zhi Xue
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引用次数: 7

摘要

在车载自组织网络(VANET)中,由于无线介质的开放性和城市范围的应用范围,无线通信容易受到恶意的多重干扰攻击。这种干扰攻击会严重破坏VANET的预设功能。为了消除攻击者,最近提出了干扰机定位方法。但是,当有多个攻击者时,它将失效。为了解决这个问题,我们提出了一种新的方法来确定攻击者数量并对相应的数据集进行分类。该方法首先以车辆的运动特征和干扰器的空间特征为基础,将数据集划分为若干个点集。然后,该方法利用无卡点分布对点集进行分组。通过这一过程得到了相应的结果。仿真结果表明,与传统方法相比,本文提出的方法是有效的,具有许多优点。
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Estimating the number of multiple jamming attackers in Vehicular Ad Hoc Network
In Vehicular Ad Hoc Network (VANET), due to the openness of wireless medium and the city-wide applied region, wireless communications are vulnerable to malicious multiple jamming attackers. Such jamming attack can seriously disable the preset functions of VANET. Jammer localization method is proposed to eliminate the attacker recently. However, it becomes invalid when there are multiple attackers. To address this issue, we propose a novel method to determine the attacker number and classify the corresponding data set. Our proposed method first uses the moving features of vehicles and spatial features of jammers as basis to divide the data set into several point sets. Then, the method uses the distribution of no-jammed points to group the point sets. And the result is accordingly obtained through this process. The simulation results show that our proposed method is effective and has many advantages compared to the traditional method.
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