Sensor Security

Deterministic perception of surrounding environment is both crucial and a challenging task for autonomous vehicle. A wide-range of sensors including LiDAR, RADAR, cameras, and so on, are used to build the perception layer of an autonomous vehicle. Many interfaces such as, OBD-II, Wi-Fi, Buletooth, cellular network, etc. have been introduced in the autonomous vehicle to control various functionalities including V2X communications, over-the-air update, security, remote vehicle health monitoring, and so on. These interfaces are introducing new attack surfaces that can be exploited via external as well as internal attacks. Attackers have successfully demonstrated how to exploit these attack surfaces by crafting attack vectors to launch both insider and external attacks. The sensor and sensor data are also vulnerable to both external and insider attacks. Developing safeguards against these attacks is a steppingstone in the design and development of a reliable autonomous vehicle. For instance, failure to detect and localize sensor data tampering can result in erroneous perception of environment could lead to wrong path planning and control decisions.

This research effort aims mitigate growing threat vectors for sensor data by developing robust and reliable countermeasures for real-time sensor data integrity verification and tamper detection and localization.