Post-Accident Cyberattack Event Analysis for Connected and Automated Vehicles

Smart mobility is an imperative facet of smart cities, and the transition of conventional automotive systems to connected and automated vehicles (CAVs) is envisioned as one of the emerging technologies on urban roads. The existing AV mobility environment is perhaps centered around road users and inf...

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Bibliographic Details
Published in:IEEE access 2022, Vol.10, p.83176-83194
Main Authors: Girdhar, Mansi, You, Yongsik, Song, Tai-Jin, Ghosh, Subhadip, Hong, Junho
Format: Article
Language:English
Subjects:
Accident investigation
Accident investigations
Accidents
Anomalies
Automation
Automobiles
CAV-enabled transport mobility environment
Computer crime
Cyber-physical systems
cybersecurity
Decision making
Ecosystems
Forensic engineering
New technology
Power grids
STRIDE threat modeling
Threat evaluation
Threat models
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Summary:Smart mobility is an imperative facet of smart cities, and the transition of conventional automotive systems to connected and automated vehicles (CAVs) is envisioned as one of the emerging technologies on urban roads. The existing AV mobility environment is perhaps centered around road users and infrastructure, but it does not support future CAV implementation due to its proximity with distinct modules nested in the cyber layer. Therefore, this paper conceptualizes a more sustainable CAV-enabled mobility framework that accommodates all cyber-based entities. Further, the key to a thriving autonomous system relies on accurate decision making in real-time, but cyberattacks on these entities can disrupt decision-making capabilities, leading to complicated CAV accidents. Due to the incompetence of the existing accident investigation frameworks to comprehend and handle these accidents, this paper proposes a 5Ws and 1H-based investigation approach to deal with cyberattack-related accidents. Further, this paper develops STRIDE threat modeling to analyze potential threats endured by the cyber-physical system (CPS) of a CAV ecosystem. Also, a stochastic anomaly detection system is proposed to identify the anomalies, abnormal activities, and unusual operations of the automated driving system (ADS) functions during a crash analysis.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2022.3196346