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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 1121–1130 of 1808 papers

Title	Date	Tasks	Status	Hype	Score
Mutual-modality Adversarial Attack with Semantic Perturbation	Dec 20, 2023	Adversarial Attack	—Unverified	0	0
NATTACK: A STRONG AND UNIVERSAL GAUSSIAN BLACK-BOX ADVERSARIAL ATTACK	May 1, 2019	Adversarial Attack	—Unverified	0	0
Towards Certified Defense for Unrestricted Adversarial Attacks	Sep 25, 2019	Adversarial Attack	—Unverified	0	0
Adversarial Robustness in Deep Learning: Attacks on Fragile Neurons	Jan 31, 2022	Adversarial AttackAdversarial Robustness	—Unverified	0	0
Adversarial Robustness for Machine Learning Cyber Defenses Using Log Data	Jul 29, 2020	Adversarial AttackAdversarial Robustness	—Unverified	0	0
Towards Characterizing Adversarial Defects of Deep Learning Software from the Lens of Uncertainty	Apr 24, 2020	Adversarial Attack	—Unverified	0	0
Near Optimal Adversarial Attacks on Stochastic Bandits and Defenses with Smoothed Responses	Aug 21, 2020	Adversarial AttackThompson Sampling	—Unverified	0	0
NeRFTAP: Enhancing Transferability of Adversarial Patches on Face Recognition using Neural Radiance Fields	Nov 29, 2023	Adversarial AttackFace Recognition	—Unverified	0	0
Adversarial Robustness for Deep Learning-based Wildfire Prediction Models	Dec 28, 2024	Adversarial AttackAdversarial Robustness	—Unverified	0	0
ADMM based Distributed State Observer Design under Sparse Sensor Attacks	Sep 13, 2022	Adversarial Attack	—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