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    A Survey on Adversarial Examples in Deep Learning

    Kai Chen1,*, Haoqi Zhu2, Leiming Yan1, Jinwei Wang1

    Journal on Big Data, Vol.2, No.2, pp. 71-84, 2020, DOI:10.32604/jbd.2020.012294

    Abstract Adversarial examples are hot topics in the field of security in deep learning. The feature, generation methods, attack and defense methods of the adversarial examples are focuses of the current research on adversarial examples. This article explains the key technologies and theories of adversarial examples from the concept of adversarial examples, the occurrences of the adversarial examples, the attacking methods of adversarial examples. This article lists the possible reasons for the adversarial examples. This article also analyzes several typical generation methods of adversarial examples in detail: Limited-memory BFGS (L-BFGS), Fast Gradient Sign Method (FGSM), Basic Iterative Method (BIM), Iterative Least-likely… More >

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