安全汽车风险分析方法

J. Monteuuis, Aymen Boudguiga, Jun Zhang, H. Labiod, Alain Servel, P. Urien
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引用次数: 29

摘要

联网和自动驾驶汽车旨在提高驾驶员和乘客的舒适度和安全性。为此,汽车制造商不断改进实际的标准化方法,以确保客户的安全、隐私和车辆的安全。然而,这些方法不支持完全自动驾驶汽车、可链接性和混淆威胁。为了解决这些问题,我们提出了一个系统的威胁分析和风险评估框架SARA,该框架包括改进的威胁模型、新的攻击方法/资产图、攻击者在攻击树中的参与以及新的驾驶系统观察度量。最后,通过车辆跟踪和舒适紧急制动故障两个用例验证了该方法在风险评估中的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SARA: Security Automotive Risk Analysis Method
Connected and automated vehicles aim to improve the comfort and the safety of the driver and passengers. To this end, car manufacturers continually improve actual standardized methods to ensure their customers safety, privacy, and vehicles security. However, these methods do not support fully autonomous vehicles, linkability and confusion threats. To address such gaps, we propose a systematic threat analysis and risk assessment framework, SARA, which comprises an improved threat model, a new attack method/asset map, the involvement of the attacker in the attack tree, and a new driving system observation metric. Finally, we demonstrate its feasibility in assessing risk with two use cases: Vehicle Tracking and Comfortable Emergency Brake Failure.
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