Adaptive Threat Response Mechanisms for Cybersecurity in Autonomous Vehicle Networks
Keywords:
Autonomous vehicle technologyAbstract
To address the dynamic, sophisticated, and undetectable cyberattacks the solution to stabilize the CAV platoons can be mainly divided into two mitigation directions. The first mitigation direction is to construct a new research method to suppress the control effect of cyberattack. This direction is usually based on designing a robust and resilient control strategy for the active vehicle. [1] The second mitigation direction is to detect and remove the threats from the platoon structure to secure and stabilize the following teammates. It is naturally considered as the design problem of the monitoring sensor for the individual vehicle. Both the first and second mitigation methods aim to secure the number of relatively stable and beautifully-preceding and following teammates in the CAV platoon.
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M. B Jedh, J. Kai Lee, and L. ben Othmane, "Evaluation of the Architecture Alternatives for Real-time Intrusion Detection Systems for Connected Vehicles," 2022. [PDF]
T. Wang, M. Tu, H. Lyu, Y. Li et al., "Impact Evaluation of Cyberattacks on Connected and Automated Vehicles in Mixed Traffic Flow and Its Resilient and Robust Control Strategy," 2022. ncbi.nlm.nih.gov
S. Ali Siddiqui, A. Mahmood, Q. Z. Sheng, H. Suzuki et al., "Towards a Machine Learning Driven Trust Management Heuristic for the Internet of Vehicles," 2023. ncbi.nlm.nih.gov
V. Kumar Kukkala, S. Vignesh Thiruloga, and S. Pasricha, "Roadmap for Cybersecurity in Autonomous Vehicles," 2022. [PDF]
S. M Mostaq Hossain, S. Banik, T. Banik, and A. Md Shibli, "Survey on Security Attacks in Connected and Autonomous Vehicular Systems," 2023. [PDF]
K. M. Ali Alheeti, M. Shaban Al-ani, and K. McDonald-Maier, "A hierarchical detection method in external communication for self-driving vehicles based on TDMA," 2018. ncbi.nlm.nih.gov
S. Park and J. Y. Choi, "Hierarchical Anomaly Detection Model for In-Vehicle Networks Using Machine Learning Algorithms," 2020. ncbi.nlm.nih.gov
Tatineni, Sumanth. "Compliance and Audit Challenges in DevOps: A Security Perspective." International Research Journal of Modernization in Engineering Technology and Science 5.10 (2023): 1306-1316.
Vemori, Vamsi. "From Tactile Buttons to Digital Orchestration: A Paradigm Shift in Vehicle Control with Smartphone Integration and Smart UI–Unveiling Cybersecurity Vulnerabilities and Fortifying Autonomous Vehicles with Adaptive Learning Intrusion Detection Systems." African Journal of Artificial Intelligence and Sustainable Development3.1 (2023): 54-91.
Mahammad Shaik. “Rethinking Federated Identity Management: A Blockchain-Enabled Framework for Enhanced Security, Interoperability, and User Sovereignty”. Blockchain Technology and Distributed Systems, vol. 2, no. 1, June 2022, pp. 21-45, https://thesciencebrigade.com/btds/article/view/223.
S. A. Abdel Hakeem, H. H. Hussein, and H. W. Kim, "Security Requirements and Challenges of 6G Technologies and Applications," 2022. ncbi.nlm.nih.gov
S. Paiva, M. Abdul Ahad, G. Tripathi, N. Feroz et al., "Enabling Technologies for Urban Smart Mobility: Recent Trends, Opportunities and Challenges," 2021. ncbi.nlm.nih.gov
S. Lee, Y. Cho, and B. C. Min, "Attack-Aware Multi-Sensor Integration Algorithm for Autonomous Vehicle Navigation Systems," 2017. [PDF]
R. Changalvala, B. Fedoruk, and H. Malik, "Radar Data Integrity Verification Using 2D QIM-Based Data Hiding," 2020. ncbi.nlm.nih.gov
S. N. Saadatmand, "Finding the ground states of symmetric infinite-dimensional Hamiltonians: explicit constrained optimizations of tensor networks," 2019. [PDF]
Y. Mei, "First-order coherent quantum Zeno dynamics and its appearance in tight-binding chains," 2023. [PDF]
M. Hamad, A. Finkenzeller, M. Kühr, A. Roberts et al., "REACT: Autonomous Intrusion Response System for Intelligent Vehicles," 2024. [PDF]
Y. Wang, A. Smahi, H. Zhang, and H. Li, "Towards Double Defense Network Security Based on Multi-Identifier Network Architecture," 2022. ncbi.nlm.nih.gov
C. Oham, R. Jurdak, and S. Jha, "Risk Analysis Study of Fully Autonomous Vehicle," 2019. [PDF]
M. Hamad and S. Steinhorst, "Security Challenges in Autonomous Systems Design," 2023. [PDF]
A. Jafar Md Muzahid, S. Fauzi Kamarulzaman, M. Arafatur Rahman, S. Akbar Murad et al., "Multiple vehicle cooperation and collision avoidance in automated vehicles: survey and an AI-enabled conceptual framework," 2023. ncbi.nlm.nih.gov
D. H. Lee, C. M. Kim, H. S. Song, Y. H. Lee et al., "Simulation-Based Cybersecurity Testing and Evaluation Method for Connected Car V2X Application Using Virtual Machine," 2023. ncbi.nlm.nih.gov
M. Dibaei, X. Zheng, K. Jiang, S. Maric et al., "An Overview of Attacks and Defences on Intelligent Connected Vehicles," 2019. [PDF]
V. Zieglmeier, S. Kacianka, T. Hutzelmann, and A. Pretschner, "A Real-Time Remote IDS Testbed for Connected Vehicles," 2018. [PDF]
P. Meyer, T. Häckel, T. Lübeck, F. Korf et al., "A Framework for the Systematic Assessment of Anomaly Detectors in Time-Sensitive Automotive Networks," 2024. [PDF]
S. Boddupalli, A. Someshwar Rao, and S. Ray, "Resilient Cooperative Adaptive Cruise Control for Autonomous Vehicles Using Machine Learning," 2021. [PDF]
N. Chinpattanakarn and C. Amornbunchornvej, "Framework for Variable-lag Motif Following Relation Inference In Time Series using Matrix Profile analysis," 2024. [PDF]
S. Bagchi, V. Aggarwal, S. Chaterji, F. Douglis et al., "Grand Challenges in Resilience: Autonomous System Resilience through Design and Runtime Measures," 2019. [PDF]
D. Haileselassie Hagos and D. B. Rawat, "Recent Advances in Artificial Intelligence and Tactical Autonomy: Current Status, Challenges, and Perspectives," 2022. ncbi.nlm.nih.gov
W. Payre, J. Perelló-March, and S. Birrell, "Under pressure: Effect of a ransomware and a screen failure on trust and driving performance in an automated car simulation," 2023. ncbi.nlm.nih.gov
P. Marcillo, D. Tamayo-Urgilés, Ángel Leonardo Valdivieso Caraguay, and M. Hernández-Álvarez, "Security in V2I Communications: A Systematic Literature Review," 2022. ncbi.nlm.nih.gov
