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Detecting Injection Attacks on Cooperative Adaptive Cruise Control

机译:在合作自适应巡航控制系统上检测喷射攻击

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Although vehicle platooning promises to improve transportation efficiency and safety by leveraging communication between convoy members, preliminary results in previous work suggest that cyber-attacks could deceive many Cooperative Adaptive Cruise Control algorithms, hence endangering the safety of every participant. This paper deeply analyzes the case of injection attacks. First, we introduce an extensive security analysis carried out through realistic simulations, to demonstrate how even slight and smooth falsification attacks do succeed in fooling the CACC controllers and cause numerous vehicle crashes. Second, we present a novel misbehavior detection technique. It leverages the correlation between multiple motion parameters concerning both single and consecutive vehicles to evaluate the plausibility of the information received from the other members. Extensive validation confirms the effectiveness of the technique proposed: overall, it succeeds to detect all the attacks simulated and prevents the occurrence of safety-critical situations.
机译:尽管车辆排行有望通过利用车队成员之间的通信来提高运输效率和安全性,但先前工作的初步结果表明,网络攻击可能会欺骗许多协作式自适应巡航控制算法,从而危及每个参与者的安全。本文对注入攻击的案例进行了深入分析。首先,我们通过真实的仿真进行了广泛的安全性分析,以证明即使是轻微,平稳的伪造攻击也能成功骗过CACC控制器并导致大量车辆坠毁。其次,我们提出了一种新颖的不良行为检测技术。它利用与单个和连续车辆有关的多个运动参数之间的相关性来评估从其他成员接收到的信息的合理性。广泛的验证证实了所提出技术的有效性:总体而言,它成功地检测了所有模拟的攻击并防止了对安全至关重要的情况的发生。

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