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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 581–590 of 1808 papers

Title	Date	Tasks	Status	Hype
Dynamic backdoor attacks against federated learning	Nov 15, 2020	Adversarial AttackBIG-bench Machine Learning	—Unverified	0
A Relaxed Optimization Approach for Adversarial Attacks against Neural Machine Translation Models	Jun 14, 2023	Adversarial AttackMachine Translation	—Unverified	0
Adversarial Attack by Limited Point Cloud Surface Modifications	Oct 7, 2021	Adversarial AttackPoint Cloud Classification	—Unverified	0
Architecture Selection via the Trade-off Between Accuracy and Robustness	Jun 4, 2019	Adversarial Attack	—Unverified	0
A Prompting-based Approach for Adversarial Example Generation and Robustness Enhancement	Mar 21, 2022	Adversarial Attack	—Unverified	0
Adversarial Attack Based on Prediction-Correction	Jun 2, 2023	Adversarial AttackPrediction	—Unverified	0
Adversarial Examples in Deep Learning: Characterization and Divergence	Jun 29, 2018	Adversarial AttackDeep Learning	—Unverified	0
Improving VAEs' Robustness to Adversarial Attack	Jun 1, 2019	Adversarial Attack	—Unverified	0
A Practical and Stealthy Adversarial Attack for Cyber-Physical Applications	Nov 22, 2021	Adversarial Attack	—Unverified	0
A Practical Adversarial Attack on Contingency Detection of Smart Energy Systems	Sep 13, 2021	Adversarial AttackDeep Reinforcement Learning	—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