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Towards Optimal Randomized Strategies in Adversarial Example Game. (arXiv:2306.16738v1 [cs.LG])
cs.CR updates on arXiv.org arxiv.org
The vulnerability of deep neural network models to adversarial example
attacks is a practical challenge in many artificial intelligence applications.
A recent line of work shows that the use of randomization in adversarial
training is the key to find optimal strategies against adversarial example
attacks. However, in a fully randomized setting where both the defender and the
attacker can use randomized strategies, there are no efficient algorithm for
finding such an optimal strategy. To fill the gap, we propose the …
adversarial applications artificial artificial intelligence attacks challenge find game intelligence key network neural network randomization the key training vulnerability work