Security Challenges in Autonomous Systems: A Zero-Trust Approach
DOI:
https://doi.org/10.56472/ICCSAIML25-107Keywords:
Autonomous systems, cyber security, zero-trust, AI security, penetration testing, machine learning attacks, API security, micro-segmentationAbstract
By improving efficiency, scalability & their intelligence, autonomous systems including self-driving cars, drones & AI-powered robotics are transforming their sectors. The security issues these systems run across likewise become more serious as per their complexity rises. Cyberattacks targeting autonomous technologies have become more common as attackers take advantage of flaws in their systems integrations, AI models & the communication networks. Dependent on perimeter defenses, conventional security approaches are inadequate against modern threats that fast adapt and could originate from both outside and inside sources. The Zero-Trust security model is investigated in this paper as a paradigm for improving autonomous system defenses. Zero Trust guarantees that every access request is always verified, tracked & validated, unlike conventional security methods that follow the idea of "never trust, always verify." Reducing attack surfaces & hence preventing possible breaches depends on the fundamental security concepts such least privilege access, constant verification, micro-segmentation, adaptive authentication & AI-driven threat detection. By using Zero-Trust architecture, companies can increase their robustness of autonomous systems against data breaches, insider threats & their cyberattacks. This work reviews real case studies, assesses common weaknesses & provides sensible approaches for Zero-Trust implementation in the autonomous systems. The outcomes highlight the need of a proactive security approach including continuous surveillance & the threat identification improved by AI to safeguard critical operations. Using a Zero-Trust strategy for security is absolutely essential as autonomous technologies merge into present day life. For academics, cybersecurity analysts & the industry leaders trying to create strong, future-oriented security solutions for intelligent autonomous ecosystems, this article provides important latest perspectives
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References
[1] Annabi, M., Zeroual, A., & Messai, N. (2024). Towards zero trust security in connected vehicles: A comprehensive survey. Computers & Security, 104018.
[2] Joshi, H. (2024). Emerging Technologies Driving Zero Trust Maturity Across Industries. IEEE Open Journal of the Computer Society.
[3] Tiwari, S., Sarma, W., & Srivastava, A. (2022). Integrating Artificial Intelligence with Zero Trust Architecture: Enhancing Adaptive Security in Modern Cyber Threat Landscape. INTERNATIONAL JOURNAL OF RESEARCH AND ANALYTICAL REVIEWS, 9, 712-728.
[4] Nahar, N., Andersson, K., Schelén, O., & Saguna, S. (2024). A Survey on Zero Trust Architecture: Applications and Challenges of 6G Networks. IEEE Access.
[5] Syed, N. F., Shah, S. W., Shaghaghi, A., Anwar, A., Baig, Z., & Doss, R. (2022). Zero trust architecture (zta): A comprehensive survey. IEEE access, 10, 57143-57179.
[6] He, Y., Huang, D., Chen, L., Ni, Y., & Ma, X. (2022). A survey on zero trust architecture: Challenges and future trends. Wireless Communications and Mobile Computing, 2022(1), 6476274.
[7] Shoaib Hashim, M. I. (2023). Zero Trust Meets AI: Redefining Security in the Age of Advanced Cyber Threats.
[8] Kim, Y., Sohn, S. G., Jeon, H. S., Lee, S. M., Lee, Y., & Kim, J. (2024). Exploring Effective Zero Trust Architecture for Defense Cybersecurity: A Study. KSII Transactions on Internet and Information Systems (TIIS), 18(9), 2665-2691.
[9] Van Bossuyt, D. L., Hale, B., Arlitt, R., & Papakonstantinou, N. (2023). Zero-trust for the system design lifecycle. Journal of Computing and Information Science in Engineering, 23(6).
[10] Chitimoju, S. (2024). The Impact of AI in Zero-Trust Security Architectures: Challenges and Innovations. International Journal of Digital Innovation, 5(1).
[11] Nair, S. S., & Lakshmikanthan, G. (2024). Digital Identity Architecture for Autonomous Mobility: A Blockchain and Federation Approach. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 5(2), 25-36. https://doi.org/10.63282/49s0p265
[12] Cao, Y., Pokhrel, S. R., Zhu, Y., Doss, R., & Li, G. (2024). Automation and orchestration of zero trust architecture: Potential solutions and challenges. Machine Intelligence Research, 21(2), 294-317.
[13] Weinberg, A. I., & Cohen, K. (2024). Zero Trust Implementation in the Emerging Technologies Era: Survey. arXiv preprint arXiv:2401.09575.
[14] Chokkanathan, K., Karpagavalli, S. M., Priyanka, G., Vanitha, K., Anitha, K., & Shenbagavalli, P. (2024, November). AI-Driven Zero Trust Architecture: Enhancing Cyber-Security Resilience. In 2024 8th International Conference on Computational System and Information Technology for Sustainable Solutions (CSITSS) (pp. 1-6). IEEE.
[15] Alquwayzani, A. A., & Albuali, A. A. (2024). A Systematic Literature Review of Zero Trust Architecture for Military UAV Security Systems. IEEE Access.
[16] Arunkumar Paramasivan. (2022). AI and Blockchain: Enhancing Data Security and Patient Privacy in Healthcare Systems. International Journal on Science and Technology, 13(4), 1–18. https://doi.org/10.5281/zenodo.14551599
[17] Sarkar, S., Choudhary, G., Shandilya, S. K., Hussain, A., & Kim, H. (2022). Security of zero trust networks in cloud computing: A comparative review. Sustainability, 14(18), 11213.