Year: 2019
Type: preprint
Abstract: We propose a generative model for adversarial attack. The model generates subtle but predictive patterns from the input. To perform an attack, it replaces the patterns of the input with those generated based on examples from some other class. We demonstrate our model by attacking CNN on MNIST.
Source: arXiv (Cornell University)
Authors: Dong, Ziang, Mao, Liang, Sun, Shiliang
Institution: East China Normal University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2989929865