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 451–475 of 1808 papers

Title	Date	Tasks	Status	Score
Adversarial Attack and Defense for Non-Parametric Two-Sample Tests	Feb 7, 2022	Adversarial AttackVocal Bursts Valence Prediction	CodeCode Available	5
Learning Transferable Adversarial Examples via Ghost Networks	Dec 9, 2018	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
Leveraging Information Consistency in Frequency and Spatial Domain for Adversarial Attacks	Aug 22, 2024	Adversarial Attack	CodeCode Available	5
From Flexibility to Manipulation: The Slippery Slope of XAI Evaluation	Dec 7, 2024	Adversarial AttackExplainable artificial intelligence	CodeCode Available	5
FDA: Feature Disruptive Attack	Sep 10, 2019	Adversarial Attackimage-classification	CodeCode Available	5
A Theoretical View of Linear Backpropagation and Its Convergence	Dec 21, 2021	Adversarial Attack	CodeCode Available	5
Fast Inference of Removal-Based Node Influence	Mar 13, 2024	Adversarial Attackcounterfactual	CodeCode Available	5
Boosting Adversarial Attacks with Momentum	Oct 17, 2017	Adversarial Attack	CodeCode Available	5
Enhancing Adversarial Attacks: The Similar Target Method	Aug 21, 2023	Adversarial Attack	CodeCode Available	5
Logits are predictive of network type	Nov 4, 2022	Adversarial AttackVocal Bursts Type Prediction	CodeCode Available	5
Look Closer to Your Enemy: Learning to Attack via Teacher-Student Mimicking	Jul 27, 2022	Adversarial AttackDomain Adaptation	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
A Targeted Universal Attack on Graph Convolutional Network	Nov 29, 2020	Adversarial AttackGraph Neural Network	CodeCode Available	5
Fashion-Guided Adversarial Attack on Person Segmentation	Apr 17, 2021	Adversarial AttackHuman Instance Segmentation	CodeCode Available	5
Feature Space Perturbations Yield More Transferable Adversarial Examples	Jun 1, 2019	Adversarial Attack	CodeCode Available	5
Exploiting vulnerabilities of deep neural networks for privacy protection	Jul 19, 2020	Adversarial AttackQuantization	CodeCode Available	5
Boosting Black-box Attack to Deep Neural Networks with Conditional Diffusion Models	Oct 11, 2023	Adversarial AttackDenoising	CodeCode Available	5
Explaining Adversarial Robustness of Neural Networks from Clustering Effect Perspective	Jan 1, 2023	Adversarial AttackAdversarial Robustness	CodeCode Available	5
Hidden Activations Are Not Enough: A General Approach to Neural Network Predictions	Sep 20, 2024	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
Expanding Scope: Adapting English Adversarial Attacks to Chinese	Jun 8, 2023	Adversarial AttackAdversarial Robustness	CodeCode Available	5
Adversarial Images for Variational Autoencoders	Dec 1, 2016	Adversarial Attack	CodeCode Available	5
Explainable and Safe Reinforcement Learning for Autonomous Air Mobility	Nov 24, 2022	Adversarial AttackDeep Reinforcement Learning	CodeCode Available	5
Exact Adversarial Attack to Image Captioning via Structured Output Learning with Latent Variables	May 10, 2019	Adversarial AttackImage Captioning	CodeCode Available	5

Show:10 25 50

← PrevPage 19 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