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 1401–1425 of 1808 papers

Title	Date	Tasks	Status
Controversial stimuli: pitting neural networks against each other as models of human recognition	Nov 21, 2019	Adversarial Attack	CodeCode Available
Exploring the Vulnerability of Natural Language Processing Models via Universal Adversarial Texts	Dec 1, 2021	Adversarial Attacktext-classification	CodeCode Available
FMM-Attack: A Flow-based Multi-modal Adversarial Attack on Video-based LLMs	Mar 20, 2024	Adversarial Attack	CodeCode Available
Foiling Explanations in Deep Neural Networks	Nov 27, 2022	Adversarial AttackExplainable artificial intelligence	CodeCode Available
Exploiting vulnerabilities of deep neural networks for privacy protection	Jul 19, 2020	Adversarial AttackQuantization	CodeCode Available
Explaining Adversarial Robustness of Neural Networks from Clustering Effect Perspective	Jan 1, 2023	Adversarial AttackAdversarial Robustness	CodeCode Available
Combining Generators of Adversarial Malware Examples to Increase Evasion Rate	Apr 14, 2023	Adversarial Attack	CodeCode Available
ColorFool: Semantic Adversarial Colorization	Nov 25, 2019	Adversarial AttackColorization	CodeCode Available
Explainable Graph Neural Networks Under Fire	Jun 10, 2024	Adversarial Attack	CodeCode Available
Explainable and Safe Reinforcement Learning for Autonomous Air Mobility	Nov 24, 2022	Adversarial AttackDeep Reinforcement Learning	CodeCode Available
Pay Attention to the Robustness of Chinese Minority Language Models! Syllable-level Textual Adversarial Attack on Tibetan Script	Dec 3, 2024	Adversarial Attack	CodeCode Available
Where and How to Attack? A Causality-Inspired Recipe for Generating Counterfactual Adversarial Examples	Dec 21, 2023	Adversarial Attackcounterfactual	CodeCode Available
Forging and Removing Latent-Noise Diffusion Watermarks Using a Single Image	Apr 27, 2025	Adversarial Attack	CodeCode Available
PDPGD: Primal-Dual Proximal Gradient Descent Adversarial Attack	Jun 3, 2021	Adversarial AttackAdversarial Robustness	CodeCode Available
VIP: Visual Information Protection through Adversarial Attacks on Vision-Language Models	Jul 11, 2025	Adversarial Attack	CodeCode Available
The UCR Time Series Archive	Oct 17, 2018	Adversarial AttackTime Series	CodeCode Available
Expanding Scope: Adapting English Adversarial Attacks to Chinese	Jun 8, 2023	Adversarial AttackAdversarial Robustness	CodeCode Available
Excess Capacity and Backdoor Poisoning	Sep 2, 2021	Adversarial AttackBackdoor Attack	CodeCode Available
Exact Adversarial Attack to Image Captioning via Structured Output Learning with Latent Variables	May 10, 2019	Adversarial AttackImage Captioning	CodeCode Available
A principled approach for generating adversarial images under non-smooth dissimilarity metrics	Aug 5, 2019	Adversarial Attack	CodeCode Available
From Adversarial Arms Race to Model-centric Evaluation: Motivating a Unified Automatic Robustness Evaluation Framework	May 29, 2023	Adversarial Attack	CodeCode Available
Rob-GAN: Generator, Discriminator, and Adversarial Attacker	Jul 27, 2018	Adversarial AttackGenerative Adversarial Network	CodeCode Available
Adversarial Examples on Graph Data: Deep Insights into Attack and Defense	Mar 5, 2019	Adversarial AttackAdversarial Defense	CodeCode Available
From Flexibility to Manipulation: The Slippery Slope of XAI Evaluation	Dec 7, 2024	Adversarial AttackExplainable artificial intelligence	CodeCode Available
Class-Conditioned Transformation for Enhanced Robust Image Classification	Mar 27, 2023	Adversarial AttackClassification	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