Transport Layer Scanning for Attack Surface Detection in Vehicular Networks

Weiss, Nils; Renner, Sebastian; Mottok, Jürgen; Matoušek, Václav

doi:10.1145/3385958.3430476

Cited by 2 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The information obtained from the previous UDS topology discovery and service scanning can facilitate subsequent penetration testing and fuzzing. Weiss et al [ 25 ] also designed a security scanning tool for the CAN transport layer to help assess the attack surface of the system. Table 6 compares various vulnerability scanning methods by time, cost, test scope and limitation.…”

Section: Automotive Cybersecurity Testing Methodsmentioning

confidence: 99%

Cybersecurity Testing for Automotive Domain: A Survey

Luo

Zhang

Yang

et al. 2022

Sensors

View full text Add to dashboard Cite

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.

show abstract

Section: Automotive Cybersecurity Testing Methodsmentioning

confidence: 99%