Employing a Model of Computation for Testing and Verifying the
Security of Connected and Autonomous Vehicles 12-07-03-0020
This also appears in
SAE International Journal of Connected and Automated Vehicles-V133-12EJ
Testing and verifying the security of connected and autonomous vehicles (CAVs)
under cyber-physical attacks is a critical challenge for ensuring their safety
and reliability. Proposed in this article is a novel testing framework based on
a model of computation that generates scenarios and attacks in a closed-loop
manner, while measuring the safety of the unit under testing (UUT), using a
verification vector. The framework was applied for testing the performance of
two cooperative adaptive cruise control (CACC) controllers under false data
injection (FDI) attacks. Serving as the baseline controller is one of a
traditional design, while the proposed controller uses a resilient design that
combines a model and learning-based algorithm to detect and mitigate FDI attacks
in real-time. The simulation results show that the resilient controller
outperforms the traditional controller in terms of maintaining a safe distance,
staying below the speed limit, and the accuracy of the FDI estimation.
Citation: Alnaser, A., Holland, J., and Sargolzaei, A., "Employing a Model of Computation for Testing and Verifying the Security of Connected and Autonomous Vehicles," SAE Intl. J CAV 7(3):2024, https://doi.org/10.4271/12-07-03-0020. Download Citation
Author(s):
Ala Jamil Alnaser, James Holland, Arman Sargolzaei
Affiliated:
Florida Polytechnic University, Mathematics, USA, University of South Florida, Mechanical Engineering Department,
USA
Pages: 15
ISSN:
2574-0741
e-ISSN:
2574-075X
Related Topics:
Adaptive cruise control
Autonomous vehicles
Mathematical models
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