Autonomous Driving Security: A Comprehensive Threat Model of Attacks and Mitigation Strategies
Autonomous Driving Security: A Comprehensive Threat Model of Attacks and Mitigation Strategies
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DOI：
10.1109/wf-iot54382.2022.10152219
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发表时间：
2022-10
期刊：
影响因子：
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通讯作者：
Mohammad Aminul Hoque;Ragib Hasan
中科院分区：
文献类型：
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作者：
Mohammad Aminul Hoque;Ragib Hasan
自动驾驶汽车(AVs)被认为是为了提高道路上的安全和效率，提高生产率，并对城市交通系统产生积极影响。由于自动驾驶(AD)技术的最新发展，自动驾驶已经开始在道路上行驶。然而，这项前景看好的技术面临着许多独特的安全挑战，有可能导致交通事故。尽管一些研究人员已经利用和解决了AD中的特定安全问题，但缺乏使用全面威胁模型来设计安全解决方案的系统方法。威胁模型分析并识别潜在的威胁和漏洞。它还识别攻击者模型，并根据已知的安全解决方案提出缓解策略。作为一种新兴的网络物理系统，AD系统需要一个设计良好的威胁模型来理解安全威胁并设计解决方案。本文探讨了AD系统中的安全问题，并使用STRIDE威胁建模过程对威胁模型进行了分析。我们假设，我们基于威胁模型的分析将有助于提高AVs的安全性，并指导研究人员开发安全的AVs。
Autonomous vehicles (AVs) are envisioned to enhance safety and efficiency on the road, increase productivity, and positively impact the urban transportation system. Due to recent developments in autonomous driving (AD) technology, AVs have started moving on the road. However, this promising technology has many unique security challenges that have the potential to cause traffic accidents. Though some researchers have exploited and addressed specific security issues in AD, there is a lack of a systematic approach to designing security solutions using a comprehensive threat model. A threat model analyzes and identifies potential threats and vulnerabilities. It also identifies the attacker model and proposes mitigation strategies based on known security solutions. As an emerging cyber-physical system, the AD system requires a well-designed threat model to understand the security threats and design solutions. This paper explores security issues in the AD system and analyzes the threat model using the STRIDE threat modeling process. We posit that our threat model-based analysis will help improve AVs' security and guide researchers toward developing secure AVs.