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 301–325 of 1808 papers

Title	Date	Tasks	Status	Hype
Renofeation: A Simple Transfer Learning Method for Improved Adversarial Robustness	Feb 7, 2020	Adversarial AttackAdversarial Robustness	CodeCode Available	1
Adversarial Attack on Community Detection by Hiding Individuals	Jan 22, 2020	Adversarial AttackCommunity Detection	CodeCode Available	1
Fooling Detection Alone is Not Enough: Adversarial Attack against Multiple Object Tracking	Jan 1, 2020	Adversarial AttackAutonomous Driving	CodeCode Available	1
T3: Tree-Autoencoder Constrained Adversarial Text Generation for Targeted Attack	Dec 22, 2019	Adversarial AttackAdversarial Text	CodeCode Available	1
Square Attack: a query-efficient black-box adversarial attack via random search	Nov 29, 2019	Adversarial Attack	CodeCode Available	1
Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks	Aug 17, 2019	Adversarial Attack	CodeCode Available	1
Natural Adversarial Examples	Jul 16, 2019	Adversarial AttackData Augmentation	CodeCode Available	1
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers	Jun 9, 2019	Adversarial AttackAdversarial Defense	CodeCode Available	1
High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks	May 28, 2019	Adversarial AttackVocal Bursts Intensity Prediction	CodeCode Available	1
Fooling Detection Alone is Not Enough: First Adversarial Attack against Multiple Object Tracking	May 27, 2019	Adversarial AttackAutonomous Driving	CodeCode Available	1
Adversarial Training for Free!	Apr 29, 2019	Adversarial AttackAdversarial Defense	CodeCode Available	1
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations	Feb 21, 2019	Adversarial AttackAdversarial Defense	CodeCode Available	1
On Evaluating Adversarial Robustness	Feb 18, 2019	Adversarial AttackAdversarial Defense	CodeCode Available	1
Theoretically Principled Trade-off between Robustness and Accuracy	Jan 24, 2019	Adversarial AttackAdversarial Defense	CodeCode Available	1
Distributionally Adversarial Attack	Aug 16, 2018	Adversarial Attack	CodeCode Available	1
Local Gradients Smoothing: Defense against localized adversarial attacks	Jul 3, 2018	Adversarial Attack	CodeCode Available	1
Generalizable Data-free Objective for Crafting Universal Adversarial Perturbations	Jan 24, 2018	Adversarial AttackDepth Estimation	CodeCode Available	1
Towards Deep Learning Models Resistant to Adversarial Attacks	Jun 19, 2017	Adversarial AttackAdversarial Defense	CodeCode Available	1
Adversarial Examples for Semantic Segmentation and Object Detection	Mar 24, 2017	Adversarial Attackimage-classification	CodeCode Available	1
Deep Variational Information Bottleneck	Dec 1, 2016	Adversarial Attack	CodeCode Available	1
3DGAA: Realistic and Robust 3D Gaussian-based Adversarial Attack for Autonomous Driving	Jul 14, 2025	3DGSAdversarial Attack	—Unverified	0
VIP: Visual Information Protection through Adversarial Attacks on Vision-Language Models	Jul 11, 2025	Adversarial Attack	CodeCode Available	0
Identifying the Smallest Adversarial Load Perturbations that Render DC-OPF Infeasible	Jul 10, 2025	Adversarial AttackBenchmarking	CodeCode Available	0
3D Gaussian Splatting Driven Multi-View Robust Physical Adversarial Camouflage Generation	Jul 2, 2025	3DGSAdversarial Attack	CodeCode Available	0
Robustness of Misinformation Classification Systems to Adversarial Examples Through BeamAttack	Jun 30, 2025	Adversarial AttackMisinformation	CodeCode Available	0

Show:10 25 50

← PrevPage 13 of 73Next →

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