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Cyber Risk Assessment Approach in Connected Autonomous Vehicles
Book chapter

Cyber Risk Assessment Approach in Connected Autonomous Vehicles

Marcielo Bell, June Wei and Guillermo Francia
Human-Centered Design, Operation and Evaluation of Mobile Communications, pp.157-165
Lecture Notes in Computer Science, 14738, Springer Nature Switzerland
06/01/2024
DOI: https://doi.org/10.1007/978-3-031-60487-4_12
Web of Science ID: WOS:001283835100012

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Abstract

The rise of automated technologies due to recent advances in Intelligent Transportation systems (ITS) from autonomous delivery services to physical transportation is rapidly developing and public availability is imminent with the active deployment and testing of teleoperation models launching this reality. With the inaugural release of the National Roadway Safety Strategy in 2022, the U.S. National transportation industry initiative aims for a goal of zero roadway fatalities and part of the solution is in designing safer autonomous or self-driving vehicle systems as viable forms of transport [14]. This initiative is prompted by the fact that worldwide vehicle related accidents result in 1.3 million deaths annually [13]. Further, this ambitious commitment to deliver safety and reliability in automotive teleoperations is commendable and will require further intentional efforts to focus on mitigating existing cybersecurity vulnerability and threat concerns. Additionally, the automotive industry supports integration of cybersecurity risk assessment and management through enforcing the joint International Organization for Standardization and Society of Automobile Engineers (ISO/SAE) 21434 standard and governance on road vehicle systems design and development. This ongoing research aims to develop a comprehensive framework to aid in threat mitigation by providing a conceptual information exchange flow model on Connected Autonomous Vehicle (CAV) and utilizing existing knowledge of threats to general information system security. By identifying the information flow, threat analysis and risk assessment risk based on threat vectors may be combined hybrid model approach annotating a ranked list to display classify risk factors into three severity levels: high, medium, low. This is an integral part of an overarching research on the design and development of a set of methodologies supporting the automotive industry toward the prevention of connected automotive cybersecurity vulnerability exploitation and promoting risk mitigation.

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