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With the wide bandwidths in millimeter wave (mmWave) frequency band thatresults in unprecedented accuracy, mmWave sensing has become vital for manyapplications, especially in autonomous vehicles (AVs). In addition, mmWavesensing has superior reliability compared to other sensing counterparts such ascamera and LiDAR, which is essential for safety-critical driving. Therefore, itis critical to understand the security vulnerabilities and improve the securityand reliability of mmWave sensing in AVs. To this end, we perform theend-to-end security analysis of a mmWave-based sensing system in AVs, bydesigning and implementing practical physical layer attack and defensestrategies in a state-of-the-art mmWave testbed and an AV testbed in real-worldsettings. Various strategies are developed to take control of the victim AV byspoofing its mmWave sensing module, including adding fake obstacles atarbitrary locations and faking the locations of existing obstacles. Fivereal-world attack scenarios are constructed to spoof the victim AV and force itto make dangerous driving decisions leading to a fatal crash. Field experimentsare conducted to study the impact of the various attack scenarios using aLincoln MKZ-based AV testbed, which validate that the attacker can indeedassume control of the victim AV to compromise its security and safety. Todefend the attacks, we design and implement a challenge-response authenticationscheme and a RF fingerprinting scheme to reliably detect aforementionedspoofing attacks.

Who is in Control? Practical Physical Layer Attack and Defense for mmWave based Sensing in Autonomous Vehicles