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ExploreADV: Towards exploratory attack for Neural Networks. (arXiv:2301.01223v1 [cs.CR])
cs.CR updates on arXiv.org arxiv.org
Although deep learning has made remarkable progress in processing various
types of data such as images, text and speech, they are known to be susceptible
to adversarial perturbations: perturbations specifically designed and added to
the input to make the target model produce erroneous output. Most of the
existing studies on generating adversarial perturbations attempt to perturb the
entire input indiscriminately. In this paper, we propose ExploreADV, a general
and flexible adversarial attack system that is capable of modeling regional and …
adversarial attack data deep learning images input networks neural networks progress speech studies target text types