IoT-enabled Adaptive Intrusion Detection Systems for Autonomous Vehicle Cybersecurity

Authors

  • Dr. Gül Büke Öztürk Associate Professor of Electrical and Electronics Engineering, Istanbul Technical University, Turkey Author

Keywords:

Motivation, Active Learning Intrusion Detection Systems

Abstract

Autonomous vehicles (AVs) are the future of the transportation industry. However, their reliance on Internet of Things (IoT) technologies introduces several cybersecurity threats. The ability to extend the Adaptive or the Active Learning Intrusion Detection Systems (AD-IDS/AL-IDS) to be able to explain their detections in real time is a critical missing piece in ensuring the safety and security of AVs. We implement SHapley Additive Explanation (SHAP) in the AL-IDS and the AD-IDS to develop two Explainable AI (XAI) models. We provide the steps, experiences, and lessons learned to simulate real-time detection in AVs with the StarCraft II, an open-source space game with different attack scenarios similar to those encountered by AVs. The real-time detection mechanism implemented provides transparency into decisions made by the IDS, which is a significant contribution regarding the wide application of AI models in domains where safety and trust are critical.

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References

A. K. Sahu, A. Tiwari, and S. K. Jena, "A Survey on Intrusion Detection Systems in IoT-Based Networks," in IEEE Access, vol. 9, pp. 58383-58400, 2021.

L. R. Medeiros, J. V. Pimentel, and J. J. P. C. Rodrigues, "Intrusion Detection Systems in Vehicular Networks: A Comprehensive Review," in IEEE Communications Surveys & Tutorials, vol. 22, no. 4, pp. 2500-2531, 2020.

D. Gunatilaka, D. Liyanage, M. Ylianttila, and A. Gurtov, "Intrusion Detection System for Vehicular Networks: A Survey," in IEEE Communications Surveys & Tutorials, vol. 21, no. 3, pp. 2130-2154, 2019.

Y. H. Lin, Y. X. Lin, C. F. Chen, and H. H. Chu, "Anomaly Intrusion Detection Systems in IoT Applications: A Review," in IEEE Internet of Things Journal, vol. 7, no. 1, pp. 41-52, 2020.

P. M. Bala, R. Kumar, and N. Ahuja, "Survey on Intrusion Detection Systems in Internet of Things," in IEEE Potentials, vol. 40, no. 2, pp. 26-32, 2021.

Tatineni, Sumanth. "Blockchain and Data Science Integration for Secure and Transparent Data Sharing." International Journal of Advanced Research in Engineering and Technology (IJARET) 10.3 (2019): 470-480.

Leeladhar Gudala, et al. “Leveraging Artificial Intelligence for Enhanced Threat Detection, Response, and Anomaly Identification in Resource-Constrained IoT Networks”. Distributed Learning and Broad Applications in Scientific Research, vol. 5, July 2019, pp. 23-54, https://dlabi.org/index.php/journal/article/view/4.

Vemori, Vamsi. "Towards Safe and Equitable Autonomous Mobility: A Multi-Layered Framework Integrating Advanced Safety Protocols, Data-Informed Road Infrastructure, and Explainable AI for Transparent Decision-Making in Self-Driving Vehicles." Human-Computer Interaction Perspectives 2.2 (2022): 10-41.

F. Salehi, M. Kahani, and M. M. Pedram, "Survey on Intrusion Detection Systems in Internet of Things," in IEEE Communications Surveys & Tutorials, vol. 22, no. 1, pp. 690-719, 2020.

X. Zhang, C. Tang, S. Zhou, and J. Sun, "A Survey of Intrusion Detection Systems in Internet of Things," in IEEE Internet of Things Journal, vol. 7, no. 1, pp. 487-498, 2020.

Z. Ullah, A. Gani, M. A. Khan, and A. Y. Zomaya, "Intrusion Detection Techniques in Cloud and Internet of Things: A Comprehensive Review," in IEEE Communications Surveys & Tutorials, vol. 20, no. 4, pp. 2693-2730, 2018.

R. Rajagopal, S. R. Biradar, and R. Bose, "A Review on Intrusion Detection Systems for Internet of Things," in IEEE Internet of Things Journal, vol. 7, no. 3, pp. 2294-2305, 2020.

K. S. Khawaja, M. Z. Shafiq, and M. Farooq, "A Survey of Intrusion Detection Systems in Internet of Things," in IEEE Internet of Things Journal, vol. 7, no. 10, pp. 9449-9469, 2020.

K. K. R. Choo and Y. Liu, "A Survey of Internet of Things (IoT) Forensics: Recent Advances, Challenges, and Opportunities," in IEEE Internet of Things Journal, vol. 6, no. 6, pp. 4682-4695, 2019.

D. B. Rawat, V. Kumar, and D. Yan, "A Survey on Software-Defined Networking," in IEEE Communications Surveys & Tutorials, vol. 17, no. 1, pp. 27-51, 2015.

H. Abbas, M. A. Ali, A. Gani, and S. U. Khan, "A Survey on Security and Privacy Issues in Internet of Things," in IEEE Communications Surveys & Tutorials, vol. 23, no. 1, pp. 762-785, 2021.

A. M. Aly, A. A. Ahmed, and M. M. Hadhoud, "A Survey on IoT Security and Privacy Using Machine Learning Approaches," in IEEE Access, vol. 9, pp. 41392-41417, 2021.

K. Kaur and A. Kumar, "A Review on Security Challenges in Internet of Things," in IEEE Potentials, vol. 40, no. 1, pp. 28-33, 2021.

N. Kumar, M. Singh, A. Verma, and S. Srivastava, "A Comprehensive Review on Security Challenges in Internet of Things," in IEEE Access, vol. 9, pp. 21121-21153, 2021.

R. Singh, R. Gupta, and S. Jain, "A Comprehensive Review on Internet of Things Security," in IEEE Communications Surveys & Tutorials, vol. 19, no. 4, pp. 2792-2830, 2017.

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Published

30-06-2023

How to Cite

[1]
Dr. Gül Büke Öztürk, “IoT-enabled Adaptive Intrusion Detection Systems for Autonomous Vehicle Cybersecurity”, J. of Artificial Int. Research and App., vol. 3, no. 1, pp. 1–24, Jun. 2023, Accessed: Nov. 24, 2024. [Online]. Available: https://aimlstudies.co.uk/index.php/jaira/article/view/86

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