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 326–350 of 1808 papers

Title	Date	Tasks	Status	Score
Transferability Bound Theory: Exploring Relationship between Adversarial Transferability and Flatness	Nov 10, 2023	Adversarial AttackDiversity	CodeCode Available	5
AdvPC: Transferable Adversarial Perturbations on 3D Point Clouds	Dec 1, 2019	Adversarial AttackClassify 3D Point Clouds	CodeCode Available	5
FenceBox: A Platform for Defeating Adversarial Examples with Data Augmentation Techniques	Dec 3, 2020	Adversarial AttackData Augmentation	CodeCode Available	5
FireBERT: Hardening BERT-based classifiers against adversarial attack	Aug 10, 2020	Adversarial Attack	CodeCode Available	5
FMM-Attack: A Flow-based Multi-modal Adversarial Attack on Video-based LLMs	Mar 20, 2024	Adversarial Attack	CodeCode Available	5
AdvHat: Real-world adversarial attack on ArcFace Face ID system	Aug 23, 2019	Adversarial AttackReal-World Adversarial Attack	CodeCode Available	5
Feature Space Perturbations Yield More Transferable Adversarial Examples	Jun 1, 2019	Adversarial Attack	CodeCode Available	5
AdvGPS: Adversarial GPS for Multi-Agent Perception Attack	Jan 30, 2024	Adversarial Attackobject-detection	CodeCode Available	5
AccelAT: A Framework for Accelerating the Adversarial Training of Deep Neural Networks through Accuracy Gradient	Oct 13, 2022	Adversarial Attack	CodeCode Available	5
FDA: Feature Disruptive Attack	Sep 10, 2019	Adversarial Attackimage-classification	CodeCode Available	5
Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients	Aug 8, 2023	Adversarial AttackFederated Learning	CodeCode Available	5
Foiling Explanations in Deep Neural Networks	Nov 27, 2022	Adversarial AttackExplainable artificial intelligence	CodeCode Available	5
GenAttack: Practical Black-box Attacks with Gradient-Free Optimization	May 28, 2018	Adversarial AttackAdversarial Robustness	CodeCode Available	5
advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch	Feb 20, 2019	Adversarial AttackAdversarial Defense	CodeCode Available	5
Advancing Adversarial Robustness in GNeRFs: The IL2-NeRF Attack	Jan 1, 2025	3D ReconstructionAdversarial Attack	CodeCode Available	5
Fast Inference of Removal-Based Node Influence	Mar 13, 2024	Adversarial Attackcounterfactual	CodeCode Available	5
Fast Adversarial CNN-based Perturbation Attack of No-Reference Image Quality Metrics	Apr 11, 2023	Adversarial AttackNo-Reference Image Quality Assessment	CodeCode Available	5
Fashion-Guided Adversarial Attack on Person Segmentation	Apr 17, 2021	Adversarial AttackHuman Instance Segmentation	CodeCode Available	5
Exploiting vulnerabilities of deep neural networks for privacy protection	Jul 19, 2020	Adversarial AttackQuantization	CodeCode Available	5
Adversarial Training for Physics-Informed Neural Networks	Oct 18, 2023	Adversarial Attack	CodeCode Available	5
Exploring the Vulnerability of Natural Language Processing Models via Universal Adversarial Texts	Dec 1, 2021	Adversarial Attacktext-classification	CodeCode Available	5
Explainable and Safe Reinforcement Learning for Autonomous Air Mobility	Nov 24, 2022	Adversarial AttackDeep Reinforcement Learning	CodeCode Available	5
Adversarial Attack and Defense for Non-Parametric Two-Sample Tests	Feb 7, 2022	Adversarial AttackVocal Bursts Valence Prediction	CodeCode Available	5
Explainable Graph Neural Networks Under Fire	Jun 10, 2024	Adversarial Attack	CodeCode Available	5
Adversarial Self-Defense for Cycle-Consistent GANs	Aug 5, 2019	Adversarial AttackImage-to-Image Translation	CodeCode Available	5

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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