MULDEF: Multi-model-based Defense Against Adversarial Examples for Neural Networks

31 Aug 2018 Siwakorn Srisakaokul Yuhao Zhang Zexuan Zhong Wei Yang Tao Xie Bo Li

Despite being popularly used in many applications, neural network models have been found to be vulnerable to adversarial examples, i.e., carefully crafted examples aiming to mislead machine learning models. Adversarial examples can pose potential risks on safety and security critical applications... (read more)

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