AI-Enhanced Cybersecurity for Autonomous Vehicles

Author(s)	Mr. Yojit Mittal
Country	India
Abstract	As autonomous vehicles transition from prototypes to widespread use, their dependence on artificial intelligence, sensor networks, and constant connectivity exposes them to critical cybersecurity risks. This paper examines major attack vectors, including adversarial manipulation of AI models, GPS spoofing, sensor tampering, and compromised V2X communication, and explores AI-driven defenses such as intrusion detection, anomaly recognition, federated learning, and secure-by-design architectures. It also addresses challenges in data privacy, legal accountability, and ethical decision-making, alongside emerging solutions like quantum-resistant cryptography and blockchain integration. By identifying current gaps and future research priorities, the study underscores that robust, adaptive, and transparent cybersecurity is essential to the safety, reliability, and public trust of autonomous transportation.
Keywords	Autonomous Vehicles, Cybersecurity, Artificial Intelligence, Intrusion Detection, Anomaly Detection, V2X Communication, Adversarial Attacks, Security by Design, Federated Learning, Quantum Cryptography, AI in Transportation
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 4, July-August 2025
Published On	2025-08-23
DOI	https://doi.org/10.36948/ijfmr.2025.v07i04.53783

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