Mitigating Replay Attacks in Autonomous Vehicle Networks
Abstract
Vehicular Ad Hoc Networks (VANETs) play a crucial role in autonomous vehicle (AV) systems; however, they are vulnerable to cyberattacks such as replay attacks. In this study, the VEINS simulation framework is used to demonstrate how an attacker can manipulate roadside units (RSUs) to broadcast outdated traffic information and cause vehicles to reroute. To mitigate this, a timestamp-based packet validation system that rejects delayed messages is proposed, as well as a packet rate threshold to identify and filter out suspicious traffic. Results suggest that these methods can effectively reduce the impact of replay attacks, ensuring more reliable and safe communication in AV networks.
Mitigating Replay Attacks in Autonomous Vehicle Networks
ONU McIntosh Center; Dean's Heritage Room
Vehicular Ad Hoc Networks (VANETs) play a crucial role in autonomous vehicle (AV) systems; however, they are vulnerable to cyberattacks such as replay attacks. In this study, the VEINS simulation framework is used to demonstrate how an attacker can manipulate roadside units (RSUs) to broadcast outdated traffic information and cause vehicles to reroute. To mitigate this, a timestamp-based packet validation system that rejects delayed messages is proposed, as well as a packet rate threshold to identify and filter out suspicious traffic. Results suggest that these methods can effectively reduce the impact of replay attacks, ensuring more reliable and safe communication in AV networks.