Enhancing Autonomous Vehicle Security with ML-Based IDS

This presentation explores MLIDS-AV, a cybersecurity framework for autonomous vehicles (AVs), emphasizing enhanced threat detection in AV networks. It addresses vulnerabilities in protocols like CAN bus, leveraging GANs, LSTM networks, and Explainable AI for real-time detection and optimization. Practical applications, including synthetic data use and compliance with transparency standards, are highlighted, alongside validation in automotive contexts. The conclusion reflects on MLIDS-AV’s...