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Adversarial Attack

An Adversarial Attack is a technique to find a perturbation that changes the prediction of a machine learning model. The perturbation can be very small and imperceptible to human eyes.

Source: Recurrent Attention Model with Log-Polar Mapping is Robust against Adversarial Attacks

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1151–1160 of 1808 papers

Title	Date	Tasks	Status	Hype
Input-specific Attention Subnetworks for Adversarial Detection	Nov 16, 2021	Adversarial Attack	—Unverified	0
Towards Interpretability of Speech Pause in Dementia Detection using Adversarial Learning	Nov 14, 2021	Adversarial Attack	—Unverified	0
Defense Against Explanation Manipulation	Nov 8, 2021	Adversarial AttackBIG-bench Machine Learning	—Unverified	0
Adversarial Attack against Cross-lingual Knowledge Graph Alignment	Nov 1, 2021	Adversarial AttackEntity Alignment	—Unverified	0
An Actor-Critic Method for Simulation-Based Optimization	Oct 31, 2021	Adversarial AttackReinforcement Learning (RL)	—Unverified	0
AdvCodeMix: Adversarial Attack on Code-Mixed Data	Oct 30, 2021	Adversarial AttackSentence	—Unverified	0
Disrupting Deep Uncertainty Estimation Without Harming Accuracy	Oct 26, 2021	Adversarial Attack	CodeCode Available	0
Generating Watermarked Adversarial Texts	Oct 25, 2021	Adversarial AttackAdversarial Text	—Unverified	0
Covariate Balancing Methods for Randomized Controlled Trials Are Not Adversarially Robust	Oct 25, 2021	Adversarial Attack	—Unverified	0
Improving Robustness of Malware Classifiers using Adversarial Strings Generated from Perturbed Latent Representations	Oct 22, 2021	Adversarial Attack	—Unverified	0

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All datasets CIFAR-10 CIFAR-100

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Xu et al.	Attack: PGD20	78.68	—	Unverified
2	3-ensemble of multi-resolution self-ensembles	Attack: AutoAttack	78.13	—	Unverified
3	TRADES-ANCRA/ResNet18	Attack: AutoAttack	59.7	—	Unverified
4	AdvTraining [madry2018]	Attack: PGD20	48.44	—	Unverified
5	TRADES [zhang2019b]	Attack: PGD20	45.9	—	Unverified
6	XU-Net	Robust Accuracy	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	3-ensemble of multi-resolution self-ensembles	Attack: AutoAttack	51.28	—	Unverified
2	multi-resolution self-ensembles	Attack: AutoAttack	47.85	—	Unverified