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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 451–460 of 1808 papers

Title	Date	Tasks	Status	Hype
Black-box Adversarial ML Attack on Modulation Classification	Aug 1, 2019	Adversarial AttackBIG-bench Machine Learning	—Unverified	0
Black-Box Decision based Adversarial Attack with Symmetric α-stable Distribution	Apr 11, 2019	Adversarial Attack	—Unverified	0
Black-Box Sparse Adversarial Attack via Multi-Objective Optimisation	Jan 1, 2023	Adversarial Attack	—Unverified	0
Black-box Targeted Adversarial Attack on Segment Anything (SAM)	Oct 16, 2023	Adversarial Attack	—Unverified	0
AutoAdversary: A Pixel Pruning Method for Sparse Adversarial Attack	Mar 18, 2022	Adversarial AttackNetwork Pruning	—Unverified	0
Blind Pre-Processing: A Robust Defense Method Against Adversarial Examples	Feb 5, 2018	Adversarial Attack	—Unverified	0
Adaptive Meta-learning-based Adversarial Training for Robust Automatic Modulation Classification	Jan 3, 2025	Adversarial AttackMeta-Learning	—Unverified	0
Blurring Fools the Network -- Adversarial Attacks by Feature Peak Suppression and Gaussian Blurring	Dec 21, 2020	Adversarial Attack	—Unverified	0
Adversarial Attacks and Defenses in Machine Learning-Powered Networks: A Contemporary Survey	Mar 11, 2023	Adversarial AttackAdversarial Defense	—Unverified	0
Adaptive Local Adversarial Attacks on 3D Point Clouds for Augmented Reality	Mar 12, 2023	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