A review of cyber attacks on sensors and perception systems in autonomous vehicle

Abstract

Vehicle automation has been in the works for a long time now. Automatic brakes, cruise control, GPS satellite navigation, etc. are all common features seen in today's automobiles. Automation and artificial intelligence breakthroughs are likely to lead to an increase in the usage of automation technologies in cars. Because of this, mankind will be more reliant on computer-controlled equipment and car systems in our daily lives. All major corporations have begun investing in the development of self-driving cars because of the rapid advancement of advanced driver support technologies. However, the level of safety and trustworthiness is still questionable. Imagine what the assailants could do if they had access to a car. Control of braking, acceleration and even steering by an attacker can have disastrous results. Most of the assaults against autonomous vehicle software and hardware are covered in this study, along with their prospective consequences. This work explores an extended analysis of the security threat and cyber-attacks on different sensors and perception systems in autonomous vehicles. This work also showed machine learning-based possible defensive techniques to prevent the security threat. An overview of most of the conceivable assaults against autonomous vehicle software and hardware and their prospective consequences is presented in this study.

Keywords

• Autonomous vehicle
• Security threats
• Artificial intelligence
• Vulnerabilities
• Machine learning
• CAN