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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 1501–1510 of 1808 papers

Title	Date	Tasks	Status	Hype
A Thorough Comparison Study on Adversarial Attacks and Defenses for Common Thorax Disease Classification in Chest X-rays	Mar 31, 2020	Adversarial AttackGeneral Classification	—Unverified	0
Adversarial Imitation Attack	Mar 28, 2020	Adversarial Attack	—Unverified	0
Challenging the adversarial robustness of DNNs based on error-correcting output codes	Mar 26, 2020	Adversarial AttackAdversarial Robustness	—Unverified	0
Solving Non-Convex Non-Differentiable Min-Max Games using Proximal Gradient Method	Mar 18, 2020	Adversarial Attack	—Unverified	0
Inline Detection of DGA Domains Using Side Information	Mar 12, 2020	Adversarial Attack	—Unverified	0
Frequency-Tuned Universal Adversarial Attacks	Mar 11, 2020	Adversarial Attack	—Unverified	0
Using an ensemble color space model to tackle adversarial examples	Mar 10, 2020	Adversarial AttackAutonomous Driving	—Unverified	0
SAD: Saliency-based Defenses Against Adversarial Examples	Mar 10, 2020	Adversarial AttackMusic Genre Recognition	—Unverified	0
Gradient-based adversarial attacks on categorical sequence models via traversing an embedded world	Mar 9, 2020	Adversarial AttackDiversity	—Unverified	0
No Surprises: Training Robust Lung Nodule Detection for Low-Dose CT Scans by Augmenting with Adversarial Attacks	Mar 8, 2020	Adversarial AttackLung Nodule Detection	—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