Don't Watch Me: A Spatio-Temporal Trojan Attack on Deep-Reinforcement-Learning-Augment Autonomous Driving. (arXiv:2211.14440v1 [cs.CR])

Deep reinforcement learning (DRL) is one of the most popular algorithms to
realize an autonomous driving (AD) system. The key success factor of DRL is
that it embraces the perception capability of deep neural networks which,
however, have been proven vulnerable to Trojan attacks. Trojan attacks have
been widely explored in supervised learning (SL) tasks (e.g., image
classification), but rarely in sequential decision-making tasks solved by DRL.
Hence, in this paper, we explore Trojan attacks on DRL for AD tasks. …

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