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Robust Physical-World Attacks on Deep Learning Visual ...

This paper appears at CVPR 2018 Robust Physical-World Attacks on Deep Learning Visual ClassificationKevin Eykholt 1, Ivan Evtimov*2, Earlence Fernandes2, Bo Li3,Amir Rahmati4, Chaowei Xiao1, Atul Prakash1, Tadayoshi Kohno2, and Dawn Song31 University of Michigan, Ann Arbor2 University of Washington3 University of California, Berkeley4 Samsung Research America and Stony Brook UniversityAbstractRecent studies show that the state-of-the-art deep neuralnetworks (DNNs) are vulnerable to adversarial examples,resulting from small-magnitude perturbations added to theinput.

quences for autonomous driving systems, without arousing suspicion in human operators. Given the lack of a standardized method for evaluating Figure 2: RP 2 pipeline overview. The input is the target Stop sign. RP 2 samples from a distribution that models physical dynamics (in …

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