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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 481–490 of 1808 papers

Title	Date	Tasks	Status	Hype
Adversarial Attacks and Dimensionality in Text Classifiers	Apr 3, 2024	Adversarial AttackAdversarial Defense	—Unverified	0
Brightness-Restricted Adversarial Attack Patch	Jul 1, 2023	Adversarial Attack	—Unverified	0
Making Corgis Important for Honeycomb Classification: Adversarial Attacks on Concept-based Explainability Tools	Oct 14, 2021	Adversarial AttackFairness	—Unverified	0
BruSLeAttack: A Query-Efficient Score-Based Black-Box Sparse Adversarial Attack	Apr 8, 2024	Adversarial Attack	—Unverified	0
Btech thesis report on adversarial attack detection and purification of adverserially attacked images	May 9, 2022	Adversarial AttackAdversarial Attack Detection	—Unverified	0
BufferSearch: Generating Black-Box Adversarial Texts With Lower Queries	Nov 16, 2021	Adversarial Attacktext-classification	—Unverified	0
Attribution-driven Causal Analysis for Detection of Adversarial Examples	Mar 14, 2019	Adversarial AttackBIG-bench Machine Learning	—Unverified	0
CAAD 2018: Iterative Ensemble Adversarial Attack	Nov 7, 2018	Adversarial Attack	—Unverified	0
CAG: A Real-time Low-cost Enhanced-robustness High-transferability Content-aware Adversarial Attack Generator	Dec 16, 2019	Adversarial Attack	—Unverified	0
Attribute-Guided Encryption with Facial Texture Masking	May 22, 2023	Adversarial AttackAttribute	—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