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 1601–1625 of 1808 papers

Title	Date	Tasks	Status
Residue-Based Natural Language Adversarial Attack Detection	Apr 17, 2022	Adversarial AttackAdversarial Attack Detection	CodeCode Available
Resilience of Named Entity Recognition Models under Adversarial Attack	Jul 1, 2022	Adversarial Attacknamed-entity-recognition	CodeCode Available
KGPA: Robustness Evaluation for Large Language Models via Cross-Domain Knowledge Graphs	Jun 16, 2024	Adversarial AttackAdversarial Robustness	CodeCode Available
KNOW How to Make Up Your Mind! Adversarially Detecting and Alleviating Inconsistencies in Natural Language Explanations	Jun 5, 2023	Adversarial Attack	CodeCode Available
Knowledge Distillation with Adversarial Samples Supporting Decision Boundary	May 15, 2018	Adversarial AttackKnowledge Distillation	CodeCode Available
Adversarial and Clean Data Are Not Twins	Apr 17, 2017	Adversarial Attack	CodeCode Available
Adversarial Training for Physics-Informed Neural Networks	Oct 18, 2023	Adversarial Attack	CodeCode Available
Accelerated Stochastic Gradient-free and Projection-free Methods	Jul 16, 2020	Adversarial Attack	CodeCode Available
Resisting Deep Learning Models Against Adversarial Attack Transferability via Feature Randomization	Sep 11, 2022	Adversarial AttackAutonomous Navigation	CodeCode Available
XSS Adversarial Attacks Based on Deep Reinforcement Learning: A Replication and Extension Study	Feb 26, 2025	Adversarial AttackDeep Reinforcement Learning	CodeCode Available
DVS-Attacks: Adversarial Attacks on Dynamic Vision Sensors for Spiking Neural Networks	Jul 1, 2021	Adversarial Attack	CodeCode Available
Disttack: Graph Adversarial Attacks Toward Distributed GNN Training	May 10, 2024	Adversarial AttackGraph Learning	CodeCode Available
Adversarial Self-Defense for Cycle-Consistent GANs	Aug 5, 2019	Adversarial AttackImage-to-Image Translation	CodeCode Available
Who is Real Bob? Adversarial Attacks on Speaker Recognition Systems	Nov 3, 2019	Adversarial AttackSpeaker Recognition	CodeCode Available
Adversarial Self-Attack Defense and Spatial-Temporal Relation Mining for Visible-Infrared Video Person Re-Identification	Jul 8, 2023	Adversarial AttackPerson Re-Identification	CodeCode Available
TextHacker: Learning based Hybrid Local Search Algorithm for Text Hard-label Adversarial Attack	Jan 20, 2022	Adversarial AttackHard-label Attack	CodeCode Available
Learning Black-Box Attackers with Transferable Priors and Query Feedback	Oct 21, 2020	Adversarial Attack	CodeCode Available
Advancing Adversarial Robustness in GNeRFs: The IL2-NeRF Attack	Jan 1, 2025	3D ReconstructionAdversarial Attack	CodeCode Available
BitAbuse: A Dataset of Visually Perturbed Texts for Defending Phishing Attacks	Feb 6, 2025	Adversarial Attack	CodeCode Available
Deep k-NN Defense against Clean-label Data Poisoning Attacks	Sep 29, 2019	Adversarial AttackData Poisoning	CodeCode Available
Task-generalizable Adversarial Attack based on Perceptual Metric	Nov 22, 2018	Adversarial Attackobject-detection	CodeCode Available
Learning to Accelerate Approximate Methods for Solving Integer Programming via Early Fixing	Jul 5, 2022	Adversarial AttackImitation Learning	CodeCode Available
Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies	Feb 20, 2024	Adversarial AttackMuJoCo	CodeCode Available
Rethinking Independent Cross-Entropy Loss For Graph-Structured Data	May 24, 2024	Adversarial AttackNode Classification	CodeCode Available
Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent	Feb 18, 2020	Adversarial Attackimage-classification	CodeCode Available

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All datasets CIFAR-10 CIFAR-100

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ResNet20	Test Accuracy	89.95	89.95(1)	Community Verified
2	Xu et al.	Attack: PGD20	78.68	—	Unverified
3	3-ensemble of multi-resolution self-ensembles	Attack: AutoAttack	78.13	—	Unverified
4	TRADES-ANCRA/ResNet18	Attack: AutoAttack	59.7	—	Unverified
5	AdvTraining [madry2018]	Attack: PGD20	48.44	—	Unverified
6	TRADES [zhang2019b]	Attack: PGD20	45.9	—	Unverified
7	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