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Detection and Mitigation of Smart Blackhole and Gray Hole Attacks in VANET Using Dynamic Time Warping

机译:基于动态时间扭曲的VANET智能黑洞和灰洞攻击的检测和缓解

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摘要

VANET topology is highly dynamic, wherein the vehicles frequently move across locations. Due to the continually changing topology and lack of security infrastructure, routing protocols in VANET are vulnerable to several attacks. In this paper, we focus on the black hole and the gray hole attacks due to its severity. In black hole and gray hole attacks, the attacker gains access to the wireless network and drops the received packets fully/selectively that impacts on the safety applications of VANET. This paper presents a novel security approach called Smart Blackhole and Gray hole Mitigation (SBGM) to detect and mitigate both black hole and gray hole nodes in VANET using a time series analysis of the dropped packets of each node. The computation of the packet drop distance threshold based on Dynamic Time Warping improves the detection accuracy in SBGM. We assess the performance of SBGM using AODV and OLSR routing protocols under low-dense and high-dense traffic scenarios in terms of Packet Delivery Ratio, Throughput, Average End-to-End Delay, and Packet Drop percentage. From the experimental results, it is evident that the proposed SBGM outperforms the existing techniques in detecting the black and gray hole attacks. The proposed SBGM achieves a detection rate of 99.87 in highway scenarios and 99.68 in urban scenarios.
机译:VANET拓扑结构是高度动态的,其中车辆经常在不同位置之间移动。由于拓扑结构的不断变化和缺乏安全基础设施,VANET中的路由协议容易受到多种攻击。在本文中,我们重点关注黑洞和灰洞攻击的严重性。在黑洞和灰洞攻击中,攻击者获得对无线网络的访问权,并完全/选择性地丢弃接收到的数据包,从而影响VANET的安全应用。本文提出了一种称为智能黑洞和灰洞缓解(SBGM)的新安全方法,通过对每个节点丢弃的数据包进行时间序列分析来检测和缓解VANET中的黑洞和灰洞节点。基于动态时间扭曲的丢包距离阈值计算提高了SBGM的检测精度。我们评估了使用 AODV 和 OLSR 路由协议的 SBGM 在低密度和高密度流量场景下的性能,包括数据包传递率、吞吐量、平均端到端延迟和丢包百分比。从实验结果可以看出,所提出的SBGM在黑洞和灰洞攻击检测方面优于现有技术。所提出的SBGM在高速公路场景下的检测率为99.87%,在城市场景下的检测率为99.68%。

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