Towards Verifying Robustness of Neural Networks Against Semantic Perturbations

19 Dec 2019Jeet MohapatraTsui-WeiWengPin-Yu ChenSijia LiuLuca Daniel

Verifying robustness of neural networks given a specified threat model is a fundamental yet challenging task. While current verification methods mainly focus on the $\ell_p$-norm threat model of the input instances, robustness verification against semantic adversarial attacks inducing large $\ell_p$-norm perturbations, such as color shifting and lighting adjustment, are beyond their capacity... (read more)

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