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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 961–970 of 1808 papers

Title	Date	Tasks	Status	Hype	Score
Information Importance-Aware Defense against Adversarial Attack for Automatic Modulation Classification:An XAI-Based Approach	Oct 15, 2024	Adversarial AttackClassification	—Unverified	0	0
AdvDO: Realistic Adversarial Attacks for Trajectory Prediction	Sep 19, 2022	Adversarial AttackAdversarial Robustness	—Unverified	0	0
Inline Detection of DGA Domains Using Side Information	Mar 12, 2020	Adversarial Attack	—Unverified	0	0
Input Hessian Regularization of Neural Networks	Sep 14, 2020	Adversarial Attack	—Unverified	0	0
Input-Specific and Universal Adversarial Attack Generation for Spiking Neural Networks in the Spiking Domain	May 7, 2025	Adversarial AttackDecision Making	—Unverified	0	0
Input-specific Attention Subnetworks for Adversarial Detection	Nov 16, 2021	Adversarial Attack	—Unverified	0	0
Input-specific Attention Subnetworks for Adversarial Detection	Mar 23, 2022	Adversarial Attack	—Unverified	0	0
The Effect of Similarity Measures on Accurate Stability Estimates for Local Surrogate Models in Text-based Explainable AI	Jun 22, 2024	Adversarial Attack	—Unverified	0	0
Intermediate Level Adversarial Attack for Enhanced Transferability	Nov 20, 2018	Adversarial Attack	—Unverified	0	0
Intermediate Outputs Are More Sensitive Than You Think	Dec 1, 2024	Adversarial AttackSensitivity	—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