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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 81–90 of 1808 papers

Title	Date	Tasks	Status	Hype	Score
Adversarial Attack and Defense Strategies for Deep Speaker Recognition Systems	Aug 18, 2020	Adversarial AttackAdversarial Robustness	CodeCode Available	1	5
An Extensive Study on Adversarial Attack against Pre-trained Models of Code	Nov 13, 2023	Adversarial Attack	CodeCode Available	1	5
3D Gaussian Splat Vulnerabilities	May 30, 2025	3DGSAdversarial Attack	CodeCode Available	1	5
Adversarial Attacks on ML Defense Models Competition	Oct 15, 2021	Adversarial AttackAdversarial Robustness	CodeCode Available	1	5
Ad2Attack: Adaptive Adversarial Attack on Real-Time UAV Tracking	Mar 3, 2022	Adversarial AttackObject Tracking	CodeCode Available	1	5
A Perturbation-Constrained Adversarial Attack for Evaluating the Robustness of Optical Flow	Mar 24, 2022	Adversarial AttackAdversarial Robustness	CodeCode Available	1	5
An Adaptive Model Ensemble Adversarial Attack for Boosting Adversarial Transferability	Aug 5, 2023	Adversarial Attack	CodeCode Available	1	5
Are AlphaZero-like Agents Robust to Adversarial Perturbations?	Nov 7, 2022	Adversarial AttackBoard Games	CodeCode Available	1	5
A Survey On Universal Adversarial Attack	Mar 2, 2021	Adversarial AttackSurvey	CodeCode Available	1	5
Adversarial Vulnerability of Randomized Ensembles	Jun 14, 2022	Adversarial AttackAdversarial Robustness	CodeCode Available	1	5

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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