Intelligent cyber-attack detection in autonomous vehicles using residual network based deep learning model

Key Points

• The research aims to develop an effective method for detecting cyber-attacks in autonomous vehicles using deep learning techniques.
• Utilized a residual network deep learning model for detection tasks.
• Analyzed data from simulated autonomous vehicle environments.
• Implemented performance metrics to evaluate detection accuracy.
• Achieved significant improvements in detection rates of cyber-attacks.
• Demonstrated resilience against various types of attacks.
• Showcased the deep learning model's capability to learn and adapt over time.

Abstract