Emerging Regulatory Countermeasures for Sensor Spoofing in Autonomous Vehicles
Abstract views: 1
/ 
PDF downloads: 0
DOI:
https://doi.org/10.59022/ujldp.375Keywords:
Sensor Spoofing, Autonomous Vehicles, Cybersecurity, Regulation, Accountability, Liability, Governance, PolicyAbstract
This research explores how regulators and policymakers address the rising threat of sensor spoofing in autonomous vehicles. It highlights the growing importance of cybersecurity and accountability in the safe deployment of self-driving technologies. The study aims to examine existing legal and regulatory frameworks, identify gaps in current governance, and propose practical approaches for improvement. Using a qualitative research method based on doctrinal and document analysis, the study reviewed official laws, international standards, and peer-reviewed literature. The results show that current policies emphasize general cybersecurity but lack specific rules for spoofing, creating inconsistencies across countries. The analysis suggests that stronger coordination, clearer liability frameworks, and proactive legal design are needed to ensure safety and trust in autonomous systems. The study concludes by recommending global harmonization of standards and further research on the ethical and legal implications of emerging vehicle technologies.
References
Alelyani, T. (2024). Establishing trust in artificial intelligence-driven autonomous healthcare systems: an expert-guided framework. Frontiers in Digital Health, 6. https://doi.org/10.3389/fdgth.2024.1474692
Ali, S., Wang, J., & Leung, V. C. M. (2025). AI-driven fusion with cybersecurity: Exploring current trends, advanced techniques, future directions, and policy implications for evolving paradigms– A comprehensive review. Information Fusion, 118, 102922. https://doi.org/10.1016/j.inffus.2024.102922
Al-Na’amneh, Q., Aljawarneh, M., Hazaymih, R., & Al Mamlook, R. E. (2025). Ethical Issues in Cyber-Security for Autonomous Vehicles (AV) and Automated Driving (pp. 173–196). https://doi.org/10.4018/979-8-3693-9919-4.ch010
Benyahya, M., Collen, A., & Nijdam, N. A. (2023). Analyses on standards and regulations for connected and automated vehicles: Identifying the certifications roadmap. Transportation Engineering, 14, 100205. https://doi.org/10.1016/j.treng.2023.100205
Burbank, J., Greene, T., & Kaabouch, N. (2024). Detecting and Mitigating Attacks on GPS Devices. Sensors, 24(17), 5529. https://doi.org/10.3390/s24175529
Elendu, C., Omeludike, E. K., Oloyede, P. O., Obidigbo, B. T., & Omeludike, J. C. (2024). Legal implications for clinicians in cybersecurity incidents: A review. Medicine, 103(39), e39887. https://doi.org/10.1097/MD.0000000000039887
El-Rewini, Z., Sadatsharan, K., Selvaraj, D. F., Plathottam, S. J., & Ranganathan, P. (2020). Cybersecurity challenges in vehicular communications. Vehicular Communications, 23, 100214. https://doi.org/10.1016/j.vehcom.2019.100214
Giannaros, A., Karras, A., Theodorakopoulos, L., Karras, C., Kranias, P., Schizas, N., Kalogeratos, G., & Tsolis, D. (2023). Autonomous Vehicles: Sophisticated Attacks, Safety Issues, Challenges, Open Topics, Blockchain, and Future Directions. Journal of Cybersecurity and Privacy, 3(3), 493–543. https://doi.org/10.3390/jcp3030025
Hu, X., Liu, T., Shu, T., & Nguyen, D. (2024). Spoofing Detection for LiDAR in Autonomous Vehicles: A Physical-Layer Approach. IEEE Internet of Things Journal, 11(11), 20673–20689. https://doi.org/10.1109/JIOT.2024.3371378
Huszár, V. D., & Adhikarla, V. K. (2021). Live Spoofing Detection for Automatic Human Activity Recognition Applications. Sensors, 21(21), 7339. https://doi.org/10.3390/s21217339
Jakobsen, S., Knudsen, K., & Andersen, B. (2023). Analysis of Sensor Attacks Against Autonomous Vehicles. Proceedings of the 8th International Conference on Internet of Things, Big Data and Security, 131–139. https://doi.org/10.5220/0011841800003482
Kidmose, B. (2025). A review of smart vehicles in smart cities: Dangers, impacts, and the threat landscape. Vehicular Communications, 51, 100871. https://doi.org/10.1016/j.vehcom.2024.100871
Kifor, C. V., & Popescu, A. (2024). Automotive Cybersecurity: A Survey on Frameworks, Standards, and Testing and Monitoring Technologies. Sensors, 24(18), 6139. https://doi.org/10.3390/s24186139
Kollarova, M., Granak, T., Strelcova, S., & Ristvej, J. (2023). Conceptual Model of Key Aspects of Security and Privacy Protection in a Smart City in Slovakia. Sustainability, 15(8), 6926. https://doi.org/10.3390/su15086926
Lin, X., Lee, C.-Y., & Fan, C. K. (2025). Exploring the Impacts of Autonomous Vehicles on the Insurance Industry and Strategies for Adaptation. World Electric Vehicle Journal, 16(3), 119. https://doi.org/10.3390/wevj16030119
Lingras, S., & Basu, A. (2025). The Security of Autonomous Vehicle Software and its National Security Implications. European Journal of Applied Science, Engineering and Technology, 3(1), 180–188. https://doi.org/10.59324/ejaset.2025.3(1).16
López González, A., Moreno, M., Moreno Román, A. C., Hadfeg Fernández, Y., & Cepero Pérez, N. (2024). Ethics in Artificial Intelligence: an Approach to Cybersecurity. Inteligencia Artificial, 27(73), 38–54. https://doi.org/10.4114/intartif.vol27iss73pp38-54
Margaret, I., Schoubben, F., & Verwaal, E. (2024). When do investors see value in international environmental management certification of multinational corporations? A study of ISO 14001 certification after the Paris Agreement. Global Strategy Journal, 14(1), 25–55. https://doi.org/10.1002/gsj.1490
Matos, F., Bernardino, J., Durães, J., & Cunha, J. (2024). A Survey on Sensor Failures in Autonomous Vehicles: Challenges and Solutions. Sensors, 24(16), 5108. https://doi.org/10.3390/s24165108
Meng, L., Yang, L., Yang, W., & Zhang, L. (2022). A Survey of GNSS Spoofing and Anti-Spoofing Technology. Remote Sensing, 14(19), 4826. https://doi.org/10.3390/rs14194826
Pande, D., & Taeihagh, A. (2023). Navigating the governance challenges of disruptive technologies: insights from regulation of autonomous systems in Singapore. Journal of Economic Policy Reform, 26(3), 298–319. https://doi.org/10.1080/17487870.2023.2197599
Sakhai, M., Sithu, K., Oke, M. K. S., & Wielgosz, M. (2025). Cyberattack Resilience of Autonomous Vehicle Sensor Systems: Evaluating RGB vs. Dynamic Vision Sensors in CARLA. Applied Sciences, 15(13), 7493. https://doi.org/10.3390/app15137493
Schellekens, M. (2016). Car hacking: Navigating the regulatory landscape. Computer Law & Security Review, 32(2), 307–315. https://doi.org/10.1016/j.clsr.2015.12.019
Schepis, D., Purchase, S., Olaru, D., Smith, B., & Ellis, N. (2023). How governments influence autonomous vehicle (AV) innovation. Transportation Research Part A: Policy and Practice, 178, 103874. https://doi.org/10.1016/j.tra.2023.103874
Taeihagh, A., & Lim, H. S. M. (2019). Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks. Transport Reviews, 39(1), 103–128. https://doi.org/10.1080/01441647.2018.1494640
Tzoannos, Z.-R., Kosmanos, D., Xenakis, A., & Chaikalis, C. (2024). The Impact of Spoofing Attacks in Connected Autonomous Vehicles under Traffic Congestion Conditions. Telecom, 5(3), 747–759. https://doi.org/10.3390/telecom5030037
Verma, P., Newe, T., O’Mahony, G. D., Brennan, D., & O’Shea, D. (2025). Toward a Unified Understanding of Cyber Resilience: Concepts, Strategies, and Future Directions. IEEE Access, 13, 49945–49965. https://doi.org/10.1109/ACCESS.2025.3551887
Wang, J., Li, F., Zhang, X., & Sun, H. (2024). Adversarial Obstacle Generation Against LiDAR-Based 3D Object Detection. IEEE Transactions on Multimedia, 26, 2686–2699. https://doi.org/10.1109/TMM.2023.3302018
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Uzbek Journal of Law and Digital Policy
This work is licensed under a Creative Commons Attribution 4.0 International License.
