ABSTRACT

Advanced Technologies are transforming the Automotive industry and the pace of innovation is accelerating at a breakneck speed. Autonomous Vehicles (AVs) incorporate many different systems and technologies and their increased computer functionality and connectivity lead to enormous cybersecurity risk. The aim of this research is to explore the significant factors that influence cyber threats on AVs and to examine their level of importance.

Partial Least Squares path modeling was preferred for research studies for its flexible modeling and identifying key drivers. The data analysis was carried out using ADANCO 2.0.1 to develop and evaluate the structural model and the causal relationships between the variables.

Correlation of in-vehicular network vulnerabilities with trust and the correlation between the “workload of the driverless system” with cyber-attacks and cyber threats to AVs are two relations but have not been touched upon in previous studies. In this research, a modified framework is proposed based on the Cyber Cycle and integrated model of Diamond Model of Intrusion Analysis with the Active Cyber Defense Cycle.

摘要

先进技术正在改变汽车行业，创新步伐以惊人的速度加速。自动驾驶汽车（AV）融合了许多不同的系统和技术，其增加的计算机功能和连接性导致巨大的网络安全风险。这项研究的目的是探究影响AV上网络威胁的重要因素，并研究其重要性。

偏最小二乘路径建模因其灵活的建模和识别关键驱动因素而被首选用于研究。使用ADANCO 2.0.1进行数据分析，以开发和评估结构模型以及变量之间的因果关系。

车载网络漏洞与信任的关联以及“无人驾驶系统的工作量”与网络攻击和对AV的网络威胁之间的关联是两个关系，但是在先前的研究中并未涉及。在这项研究中，提出了一种基于网络周期和具有主动网络防御周期的入侵分析的钻石模型集成模型的改进框架。