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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 1111–1120 of 1808 papers

Title	Date	Tasks	Status	Hype
Towards Adversarially Robust Deep Image Denoising	Jan 12, 2022	Adversarial AttackAdversarial Robustness	—Unverified	0
Similarity-based Gray-box Adversarial Attack Against Deep Face Recognition	Jan 11, 2022	Adversarial AttackFace Recognition	CodeCode Available	0
ROOM: Adversarial Machine Learning Attacks Under Real-Time Constraints	Jan 5, 2022	Adversarial AttackBIG-bench Machine Learning	—Unverified	0
Adversarial Attack via Dual-Stage Network Erosion	Jan 1, 2022	Adversarial Attack	CodeCode Available	0
Bounded Adversarial Attack on Deep Content Features	Jan 1, 2022	Adversarial Attack	CodeCode Available	0
360-Attack: Distortion-Aware Perturbations From Perspective-Views	Jan 1, 2022	Adversarial Attack	—Unverified	0
A General Framework for Evaluating Robustness of Combinatorial Optimization Solvers on Graphs	Dec 28, 2021	Adversarial AttackCombinatorial Optimization	—Unverified	0
Adversarial Attack for Asynchronous Event-based Data	Dec 27, 2021	Adversarial AttackAutonomous Driving	—Unverified	0
Task and Model Agnostic Adversarial Attack on Graph Neural Networks	Dec 25, 2021	Adversarial AttackQ-Learning	CodeCode Available	0
A Theoretical View of Linear Backpropagation and Its Convergence	Dec 21, 2021	Adversarial Attack	CodeCode Available	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