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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 1211–1220 of 1808 papers

Title	Date	Tasks	Status	Hype	Score
Over-the-Air Adversarial Attacks on Deep Learning Based Modulation Classifier over Wireless Channels	Feb 5, 2020	Adversarial Attack	—Unverified	0	0
Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation	May 23, 2025	Adversarial Attackimage-classification	—Unverified	0	0
PAR-AdvGAN: Improving Adversarial Attack Capability with Progressive Auto-Regression AdvGAN	Feb 16, 2025	Adversarial Attackregression	—Unverified	0	0
Learn2Weight: Parameter Adaptation against Similar-domain Adversarial Attacks	May 15, 2022	Adversarial AttackDomain Adaptation	—Unverified	0	0
Mitigating the Impact of Noisy Edges on Graph-Based Algorithms via Adversarial Robustness Evaluation	Jan 28, 2024	Adversarial AttackAdversarial Robustness	—Unverified	0	0
Pareto Regret Analyses in Multi-objective Multi-armed Bandit	Dec 1, 2022	Adversarial Attack	—Unverified	0	0
Pasadena: Perceptually Aware and Stealthy Adversarial Denoise Attack	Jul 14, 2020	Adversarial AttackCommon Sense Reasoning	—Unverified	0	0
3D-VFD: A Victim-free Detector against 3D Adversarial Point Clouds	May 18, 2022	Adversarial AttackSteganalysis	—Unverified	0	0
Towards Robustness of Deep Neural Networks via Regularization	Jan 1, 2021	Adversarial AttackAdversarial Robustness	—Unverified	0	0
Adversarial Learning of Deepfakes in Accounting	Oct 9, 2019	Adversarial AttackERP	—Unverified	0	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