Impact Evaluation of Falsified Data Attacks on Connected Vehicle Based Traffic Signal Control
Impact Evaluation of Falsified Data Attacks on Connected Vehicle Based Traffic Signal Control
复制标题
伪造数据攻击对基于车联网的交通信号控制的影响评估
DOI：
10.14722/autosec.2021.23005
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Henry X. Liu
中科院分区：
文献类型：
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作者：
S. Huang;W. Wong;Yiheng Feng;Qi Alfred Chen;Z. Morley Mao;Henry X. Liu
车联网（CV）技术实现了车辆与交通基础设施之间的数据交换，因此在改善当前交通信号控制系统方面具有巨大潜力。然而，这种连接也可能带来网络安全问题。作为研究基于cv的交通信号控制（CV-TSC）系统网络安全的第一步，需要识别潜在的网络威胁并评估其影响。在本文中，我们的目标是评估网络攻击对CV-TSC系统的影响，通过考虑一个现实的攻击场景，其中CV-TSC系统的控制逻辑对攻击者不可用。我们的威胁模型假定攻击者可以使用代理模型学习控制逻辑。基于代理模型，攻击者可以发起伪造数据攻击来影响信号控制决策。在案例研究中，我们实际评估了伪造数据攻击对现有CV-TSC系统（即I-SIG）的影响。
Connected vehicle (CV) technology enables data exchange between vehicles and transportation infrastructure and therefore has great potentials to improve current traffic signal control systems. However, this connectivity might also bring cyber security concerns. As the first step in investigating the cyber security of CV-based traffic signal control (CV-TSC) systems, potential cyber threats need to be identified and corresponding impact needs to be evaluated. In this paper, we aim to evaluate the impact of cyber attacks on CV-TSC systems by considering a realistic attack scenario in which the control logic of a CV-TSC system is unavailable to attackers. Our threat model presumes that an attacker may learn the control logic using a surrogate model. Based on the surrogate model, the attacker may launch falsified data attacks to influence signal control decisions. In the case study, we realistically evaluate the impact of falsified data attacks on an existing CV-TSC system (i.e., I-SIG).