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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 1041–1050 of 1808 papers

Title	Date	Tasks	Status	Hype	Score
To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models	May 6, 2024	Adversarial AttackMemorization	—Unverified	0	0
Light Lies: Optical Adversarial Attack	Jun 18, 2021	Adversarial AttackClassification	—Unverified	0	0
BOSH: An Efficient Meta Algorithm for Decision-based Attacks	Sep 10, 2019	Adversarial AttackBayesian Optimization	—Unverified	0	0
OTAD: An Optimal Transport-Induced Robust Model for Agnostic Adversarial Attack	Aug 1, 2024	Adversarial AttackAdversarial Defense	—Unverified	0	0
Limited Budget Adversarial Attack Against Online Image Stream	Jun 18, 2021	Adversarial Attack	—Unverified	0	0
Linear Backpropagation Leads to Faster Convergence	Sep 29, 2021	Adversarial Attack	—Unverified	0	0
Linear system security -- detection and correction of adversarial attacks in the noise-free case	Nov 15, 2017	Adversarial Attack	—Unverified	0	0
LLMs Can Defend Themselves Against Jailbreaking in a Practical Manner: A Vision Paper	Feb 24, 2024	Adversarial AttackSafety Alignment	—Unverified	0	0
Towards Accuracy-Fairness Paradox: Adversarial Example-based Data Augmentation for Visual Debiasing	Jul 27, 2020	Adversarial AttackAttribute	—Unverified	0	0
Local Competition and Stochasticity for Adversarial Robustness in Deep Learning	Jan 4, 2021	Adversarial AttackAdversarial Robustness	—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