Towards Secure and Robust Autonomy Software in Autonomous Driving and Smart Transportation

Abstract

Autonomous Driving (AD) technology has always been an international pursuit due to its significant benefit in driving safety, efficiency, and mobility. Over 15 years after the first DARPA Grand Challenge, its development and deployment are becoming increasingly mature and practical, with some AD vehicles already providing services on public roads (e.g., Google Waymo One in Phoenix and Baidu Apollo Go in China). In AD technology, the autonomy software stack, or the AD software, is highly security critical: it is in charge of safety-critical driving decisions such as collision avoidance and lane keeping, and thus any security problems in it can directly impact road safety. In this talk, I will describe my recent research that initiates the first systematic effort towards understanding and addressing the security problems in production AD software. I will be focusing on two critical modules: perception and localization, and talk about how we are able to discover novel and practical sensor/physical-world attacks that can cause end-to-end safety impacts such as crashing into obstacles or driving off road. Besides AD software, I will also briefly talk about my recent research on autonomy software security in smart transportation in general, especially those enabled by Connected Vehicle (CV) technology. I will conclude with a discussion on defense and future research directions.