Construct · 1 fields · 1 citations

Carlini-Wagner attack: a standalone construct

One name. One construct. A landmark on the map.

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Adversarial machine learning

an optimization-based attack that finds minimal adversarial perturbations under several distance metrics, used to test whether defenses really work.

In adversarial machine learning, Carlini-Wagner attack refers to an optimization-based attack that finds minimal adversarial perturbations under several distance metrics, used to test whether defenses really work. This meaning comes from Carlini (2017) in 2017 IEEE Symposium on Security and Privacy (SP).[1]

Unit
Recovery means
Measured by

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Nearby constructs

attack4 fields · 10 citationsjingle · one word, four constructs learning6 fields · 14 citationsjingle · one name, six constructs privacy3 fields · 3 citationsjingle · one word, three carriers

References

Carlini, N., & Wagner, D. (2017). Towards Evaluating the Robustness of Neural Networks. 2017 IEEE Symposium on Security and Privacy (SP). https://doi.org/10.1109/sp.2017.49

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