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We provide a complete characterisation of the phenomenon of adversarialexamples - inputs intentionally crafted to fool machine learning models. We aimto cover all the important concerns in this field of study: (1) the conjectureson the existence of adversarial examples, (2) the security, safety androbustness implications, (3) the methods used to generate and (4) protectagainst adversarial examples and (5) the ability of adversarial examples totransfer between different machine learning models. We provide ample backgroundinformation in an effort to make this document self-contained. Therefore, thisdocument can be used as survey, tutorial or as a catalog of attacks anddefences using adversarial examples.

Adversarial Examples - A Complete Characterisation of the Phenomenon