SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 821–830 of 1808 papers

TitleStatusHype
A Brief Survey on Deep Learning Based Data Hiding—0
Boosting Adversarial Transferability for Hyperspectral Image Classification Using 3D Structure-invariant Transformation and Intermediate Feature Distance—0
Adversarial Attack for Asynchronous Event-based Data—0
Black-Box Adversarial Attacks on Graph Neural Networks as An Influence Maximization Problem—0
Black-box Adversarial Attacks on Commercial Speech Platforms with Minimal Information—0
Black-box Adversarial Attacks against Dense Retrieval Models: A Multi-view Contrastive Learning Method—0
Black-Box Adversarial Attack on Vision Language Models for Autonomous Driving—0
Adversarial Sampling for Fairness Testing in Deep Neural Network—0
Biologically inspired protection of deep networks from adversarial attacks—0
Bio-Inspired Adversarial Attack Against Deep Neural Networks—0
Show:102550
← PrevPage 83 of 181Next →
All datasetsCIFAR-10CIFAR-100

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Xu et al.Attack: PGD2078.68—Unverified
23-ensemble of multi-resolution self-ensemblesAttack: AutoAttack78.13—Unverified
3TRADES-ANCRA/ResNet18Attack: AutoAttack59.7—Unverified
4AdvTraining [madry2018]Attack: PGD2048.44—Unverified
5TRADES [zhang2019b]Attack: PGD2045.9—Unverified
6XU-NetRobust Accuracy1—Unverified
#ModelMetricClaimedVerifiedStatus
13-ensemble of multi-resolution self-ensemblesAttack: AutoAttack51.28—Unverified
2multi-resolution self-ensemblesAttack: AutoAttack47.85—Unverified