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Adversarial Examples for Cost-Sensitive Classifiers · Around

2019

Adversarial Examples for Cost-Sensitive Classifiers

Hartnett, Gavin S., Lohn, Andrew J., Sedlack, Alexander P.

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Motivated by safety-critical classification problems, we investigate adversarial attacks against cost-sensitive classifiers.

We use current state-of-the-art adversarially-resistant neural network classifiers [1] as the underlying models.
Cost-sensitive predictions are then achieved via a final processing step in the feed-forward evaluation of the network.
We evaluate the effectiveness of cost-sensitive classifiers against a variety of attacks and we introduce a new cost-sensitive attack which performs better than targeted attacks in some cases.

Built on

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