 PixelDefend: Leveraging Generative Models to Understand and Defend
against Adversarial ExamplesInternational Conference on Learning Representations (ICLR), 2017 |
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 Generating Adversarial Malware Examples for Black-Box Attacks Based on
GANInternational Conference on Data Mining and Big Data (ICDMBD), 2017 |
 Dense Associative Memory is Robust to Adversarial InputsNeural Computation (Neural Comput.), 2017 |
 Adversarial Examples Detection in Deep Networks with Convolutional
Filter StatisticsIEEE International Conference on Computer Vision (ICCV), 2016 |
 Adversary Resistant Deep Neural Networks with an Application to Malware
DetectionKnowledge Discovery and Data Mining (KDD), 2016 |
 Towards Evaluating the Robustness of Neural NetworksIEEE Symposium on Security and Privacy (IEEE S&P), 2016 |
