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 571–580 of 1808 papers

TitleStatusHype
Adversarial Attack for Explanation Robustness of Rationalization Models—0
Art-Attack: Black-Box Adversarial Attack via Evolutionary Art—0
A Robust Likelihood Model for Novelty Detection—0
Domain Adaptive Transfer Attack (DATA)-based Segmentation Networks for Building Extraction from Aerial Images—0
Adversarial Fine-tune with Dynamically Regulated Adversary—0
AR-GAN: Generative Adversarial Network-Based Defense Method Against Adversarial Attacks on the Traffic Sign Classification System of Autonomous Vehicles—0
Adversarial Attack Driven Data Augmentation for Accurate And Robust Medical Image Segmentation—0
Adversarial Exposure Attack on Diabetic Retinopathy Imagery Grading—0
Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts?—0
DoPa: A Comprehensive CNN Detection Methodology against Physical Adversarial Attacks—0
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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