Zero-day Vulnerability Inspired Hazard Assessment for Autonomous Driving Vehicles

Zhonglin Hou, Hong Liu, Yan Zhang
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引用次数: 2

Abstract

Safety of the intended functionality (SOTIF) is expected to be the third type of road vehicle auto-driving safety in addition to information security and functional safety. SOTIF which is unknown and uncertain is caused by non-system failure or personnel misoperation. Advanced driver assistance systems (ADAS) that SOTIF cannot be accepted will be dangerous. The unknown triggering events triggered suddenly or exploited by a malicious hacker will pose a threat to vehicle safety. In the field of traditional network security, there have been many pieces of research on vulnerability assessment. This paper establishes hazard graph for SOTIF and triggering event models and proposes a safety assessment method for unknown triggering events of SOTIF and a method to enhances SOTIF inspired by the zero-day vulnerability assessment in the traditional cybersecurity field. The AEB system is used as an example to apply the proposed algorithm, and Petri net accessibility testing is used as a verification of the correctness of the algorithm in this paper.
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基于零日漏洞的自动驾驶汽车危险评估
预期功能安全(SOTIF)有望成为继信息安全和功能安全之后,道路车辆自动驾驶安全的第三种类型。未知和不确定的SOTIF是由非系统故障或人员误操作引起的。不能接受SOTIF的高级驾驶辅助系统(ADAS)将是危险的。突然触发或被恶意黑客利用的未知触发事件将对车辆安全构成威胁。在传统的网络安全领域中,对漏洞评估进行了大量的研究。本文建立了SOTIF的危害图和触发事件模型,并在传统网络安全领域的零日漏洞评估的启发下,提出了SOTIF未知触发事件的安全性评估方法和增强SOTIF的方法。以AEB系统为例,对本文提出的算法进行了应用,并通过Petri网可达性测试验证了算法的正确性。
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