Towards Explaining Adversarial Examples Phenomenon in Artificial Neural Networks

• URL: http://arxiv.org/abs/2107.10599v1
• Date: Thu, 22 Jul 2021 11:56:14 GMT
• Title: Towards Explaining Adversarial Examples Phenomenon in Artificial Neural Networks
• Authors: Ramin Barati, Reza Safabakhsh, Mohammad Rahmati
• Abstract summary: We study the adversarial examples existence and adversarial training from the standpoint of convergence. We provide evidence that pointwise convergence in ANNs can explain these observations.
• Score: 8.31483061185317
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper, we study the adversarial examples existence and adversarial training from the standpoint of convergence and provide evidence that pointwise convergence in ANNs can explain these observations. The main contribution of our proposal is that it relates the objective of the evasion attacks and adversarial training with concepts already defined in learning theory. Also, we extend and unify some of the other proposals in the literature and provide alternative explanations on the observations made in those proposals. Through different experiments, we demonstrate that the framework is valuable in the study of the phenomenon and is applicable to real-world problems.

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