Human-Centric Authentication Systems for Secure Access Control in Autonomous Vehicles

Authors

  • Dr. Min Chen Professor of Mechanical Engineering, Tsinghua University, China Author

Keywords:

minor integrations

Abstract

In the present work, the experts focus on requirements and challenges to be considered at: a) conceptual design phase, b) up to minor integration results, that have been possibly achieved, and c) potential issues faced with major integration [1]. In this context, the situation of achieving temporal approval for minor integrations, respectively the situation of potentially occurring liabilities on manufacturers’ side, not only poses an enormous challenge, but also not only in the context of anti-tampering and manipulability security features. Moreover, during system integration and operation, the recognition unit has to be robust against hazardous system manipulation by attackers.

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References

Tatineni, S., and A. Katari. “Advanced AI-Driven Techniques for Integrating DevOps and MLOps: Enhancing Continuous Integration, Deployment, and Monitoring in Machine Learning Projects”. Journal of Science & Technology, vol. 2, no. 2, July 2021, pp. 68-98, https://thesciencebrigade.com/jst/article/view/243.

Prabhod, Kummaragunta Joel. "Advanced Techniques in Reinforcement Learning and Deep Learning for Autonomous Vehicle Navigation: Integrating Large Language Models for Real-Time Decision Making." Journal of AI-Assisted Scientific Discovery 3.1 (2023): 1-20.

Tatineni, Sumanth, and Sandeep Chinamanagonda. “Leveraging Artificial Intelligence for Predictive Analytics in DevOps: Enhancing Continuous Integration and Continuous Deployment Pipelines for Optimal Performance”. Journal of Artificial Intelligence Research and Applications, vol. 1, no. 1, Feb. 2021, pp. 103-38, https://aimlstudies.co.uk/index.php/jaira/article/view/104.

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Published

30-12-2023

How to Cite

[1]
Dr. Min Chen, “Human-Centric Authentication Systems for Secure Access Control in Autonomous Vehicles”, J. of Artificial Int. Research and App., vol. 3, no. 2, pp. 325–352, Dec. 2023, Accessed: Nov. 07, 2024. [Online]. Available: https://aimlstudies.co.uk/index.php/jaira/article/view/116