Explaining Away Attacks Against Neural Networks

Sean Saito; Jin Wang

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arXiv · 2003.05748

Explaining Away Attacks Against Neural Networks

Sean Saito·Jin Wang

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Abstract

We investigate the problem of identifying adversarial attacks on image-based neural networks. We present intriguing experimental results showing significant discrepancies between the explanations generated for the predictions of a model on clean and adversarial data. Utilizing this intuition, we propose a framework which can identify whether a given input is adversarial based on the explanations given by the model. Code for our experiments can be found here: https://github.com/seansaito/Explaining-Away-Attacks-Against-Neural-Networks.

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cs.LG cs.CR cs.CV stat.ML

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Sean Saito, Jin Wang. 2020-03-06. Explaining Away Attacks Against Neural Networks. https://arxiv.org/abs/2003.05748

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