Yifan Jiang

The rapid development of intelligent connected vehicles has increased the attack surface of vehicles and made the complexity of vehicle systems unprecedented. Original equipment manufacturers (OEMs) need to accurately represent and identify threats and match corresponding security requirements. Meanwhile, the fast iteration cycle of modern vehicles requires development engineers to quickly obtain cybersecurity requirements for new features in their developed systems in order to develop system code that meets cybersecurity requirements. However, existing threat identification and cybersecurity requirement methods in the automotive domain cannot accurately describe and identify threats for a new feature while also quickly matching appropriate cybersecurity requirements. This article proposes a cybersecurity requirements management system (CRMS) framework to assist OEM security experts in conducting comprehensive automated threat analysis and risk assessment and to help development engineers identify security requirements prior to software development. The proposed CRMS framework enables development engineers to quickly model their systems using the UML-based (i.e., capable of describing systems using UML) Eclipse Modeling Framework and security experts to integrate their security experience into a threat library and security requirement library expressed in Alloy formal language. In order to ensure accurate matching between the two, a middleware communication framework called the component channel messaging and interface (CCMI) framework, specifically designed for the automotive domain, is proposed. The CCMI communication framework enables the fast model of development engineers to match with the formal model of security experts for threat and security requirement matching, achieving accurate and automated threat and risk identification and security requirement matching. To validate our work, we conducted experiments on the proposed framework and compared the results with the HEAVENS approach. The results showed that the proposed framework is superior in terms of threat detection rates and coverage rates of security requirements. Moreover, it also saves analysis time for large and complex systems, and the cost-saving effect becomes more pronounced with increasing system complexity.

Modern vehicles are more complex and interconnected than ever before, which also means that attack surfaces for vehicles have increased significantly. Malicious cyberattacks will not only exploit personal privacy and property, but also affect the functional safety of electrical/electronic (E/E) safety-critical systems by controlling the driving functionality, which is life-threatening. Therefore, it is necessary to conduct cybersecurity testing on vehicles to reveal and address relevant security threats and vulnerabilities. Cybersecurity standards and regulations issued in recent years, such as ISO/SAE 21434 and UNECE WP.29 regulations (R155 and R156), also emphasize the indispensability of cybersecurity verification and validation in the development lifecycle but lack specific technical details. Thus, this paper conducts a systematic and comprehensive review of the research and practice in the field of automotive cybersecurity testing, which can provide reference and advice for automotive security researchers and testers. We classify and discuss the security testing methods and testbeds in automotive engineering. Furthermore, we identify gaps and limitations in existing research and point out future challenges.

With the development of intelligent and connected vehicles, onboard Ethernet will play an important role in the next generation of vehicle network architectures. It is well established that accurate timing and guaranteed data delivery are critical in the automotive environment. The time-sensitive network (TSN) protocol can precisely guarantee the time certainty of the key signals of automotive Ethernet. With the time-sensitive network based on automotive Ethernet being standardized by the TSN working group, the TSN has already entered the vision of the automotive network. However, the security mechanism of the TSN protocol is rarely discussed. First, the security of the TSN automotive Ethernet as a backbone E/E (electrical/electronic) architecture is analyzed in this paper through the Microsoft STRIDE threat model, and possible countermeasures for the security of automotive TSNs are listed, including the security protocol defined in the TSN, so that the TSN security protocol and the traditional protection technology can form a complete automotive Ethernet protection system. Then, the security mechanism per-stream filtering and policing (PSFP) defined in IEEE 802.1Qci is analyzed in detail, and an anomaly detection system based on PSFP is proposed in this paper. Finally, OMNeT++ is used to simulate a real TSN topology to evaluate the performance of the proposed anomaly detection system (ADS). As a result, the protection strategy based on 802.1Qci not only ensures the real-time performance of the TSN but can also isolate individuals with abnormal behavior and block DoS (denial of service) attacks, thus attaining the security protection of the TSN vehicle-based network.

With the rapid development of connected vehicles, people can get a better driving experience. However, the interconnection with the external network may bring growing accidents caused by cybersecurity vulnerabilities. As a result, automakers are paying more attention to cybersecurity and spending more cost on developing cybersecurity defense mechanisms. Threat analysis and risk assessment (TARA) is an efficient method to ensure the defense effect and greatly save costs in the early stage of vehicle development. It analyzes the threat of vehicle systems and determines the hierarchical defense and corresponding mitigations according to the potential threat to the system. This paper gives an overview of threat analysis and risk assessment in the automotive field. First, a novel classification of different TARA methods has been proposed. The existing methods have been analyzed and compared. Then, we have found some commonly used tools applied to TARA and compared their performance. After that, a concept named attack-defense mapping is proposed to figure out how to map the already found threats and vulnerabilities of the system to the appropriate mitigations. At last, the future development directions of TARA in the automotive domain have been discussed.