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车联网中的中间人攻击:评估攻击者策略的影响。

Man-In-The-Middle Attacks in Vehicular Ad-Hoc Networks: Evaluating the Impact of Attackers' Strategies.

机构信息

Cyber Security Research Group, College of Engineering and Technology, University of Derby, Derby DE22 3AW, UK.

Department of Computer Science, Loughborough University, Loughborough LE11 3TU, UK.

出版信息

Sensors (Basel). 2018 Nov 20;18(11):4040. doi: 10.3390/s18114040.

Abstract

Vehicular Ad-Hoc Network (VANET), a vital component of Intelligent Transportation Systems (ITS) technology, relies on communication between dynamically connected vehicles and static Road Side Units (RSU) to offer various applications (e.g., collision avoidance alerts, steep-curve warnings and infotainment). VANET has a massive potential to improve traffic efficiency, and road safety by exchanging critical information between nodes (vehicles and RSU), thus reducing the likelihood of traffic accidents. However, this communication between nodes is subject to a variety of attacks, such as Man-In-The-Middle (MITM) attacks which represent a major risk in VANET. It happens when a malicious node intercepts or tampers with messages exchanged between legitimate nodes. In this paper, we studied the impact on network performance of different strategies which attackers can adopt to launch MITM attacks in VANET, such as fleet or random strategies. In particular, we focus on three goals of MITM attacks-message delayed, message dropped and message tampered. The simulation results indicate that these attacks have a severe influence on the legitimate nodes in VANET as the network experience high number of compromised messages, high end-to-end delays and preeminent packet losses.

摘要

车联网(VANET)是智能交通系统(ITS)技术的重要组成部分,依靠动态连接的车辆与静态路边单元(RSU)之间的通信来提供各种应用(例如,碰撞避免警报、急弯警告和信息娱乐)。VANET 具有通过节点(车辆和 RSU)之间交换关键信息来提高交通效率和道路安全的巨大潜力,从而降低交通事故的可能性。然而,节点之间的这种通信易受到各种攻击,例如中间人(MITM)攻击,这在 VANET 中是一个主要风险。当恶意节点截获或篡改合法节点之间交换的消息时,就会发生这种攻击。在本文中,我们研究了攻击者在 VANET 中采用不同策略发起 MITM 攻击对网络性能的影响,例如车队或随机策略。特别关注 MITM 攻击的三个目标——消息延迟、消息丢失和消息篡改。仿真结果表明,这些攻击对 VANET 中的合法节点造成了严重影响,因为网络会遇到大量受损消息、高端到端延迟和明显的分组丢失。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b7/6263439/e1ede7cd6823/sensors-18-04040-g001.jpg

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