Vol. 4 No. 1 (2024): African Journal of Artificial Intelligence and Sustainable Development
Articles

Artificial Intelligence for Predictive Change Management in Information Systems Projects: Cognitive Authentication Mechanisms for User Verification in Autonomous Vehicles

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  • Dr. Mohamed Azzouzi
Dr. Mohamed Azzouzi
Associate Professor of Computer Science, Cadi Ayyad University, Morocco
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Published 05-04-2024

Keywords

  • emulation,
  • cloning
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Dr. Mohamed Azzouzi, “Artificial Intelligence for Predictive Change Management in Information Systems Projects: Cognitive Authentication Mechanisms for User Verification in Autonomous Vehicles”, African J. of Artificial Int. and Sust. Dev., vol. 4, no. 1, pp. 106–129, Apr. 2024, Accessed: Dec. 22, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/122

Abstract

The development of secure authentication mechanisms in autonomous vehicles is critical to preventing impersonation attacks, particularly in the context of AI-driven Predictive Change Management frameworks. This paper presents a comprehensive analysis of cognitive authentication mechanisms designed for user verification, addressing the vulnerabilities posed by adversarial attacks on secure Driver Authentication Frameworks (DAF). Our research highlights the lack of standardized methodologies for testing behavior-based defense systems and introduces a novel evaluation framework. By employing both static and dynamic security evaluations, we demonstrate how adversarial simulations can expose security weaknesses in vehicular systems. Furthermore, we propose the use of this framework in adaptive change environments, considering users with cognitive impairments or voice issues, offering a path toward more resilient and user-centered security solutions in project management for autonomous vehicle architectures.

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