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 1221–1230 of 1808 papers

TitleStatusHype
Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain—0
Adversarial Interaction Attacks: Fooling AI to Misinterpret Human Intentions—0
Towards Robust Neural Image Compression: Adversarial Attack and Model Finetuning—0
PB-UAP: Hybrid Universal Adversarial Attack For Image Segmentation—0
Towards Robust Speech-to-Text Adversarial Attack—0
PEARL: Preprocessing Enhanced Adversarial Robust Learning of Image Deraining for Semantic Segmentation—0
Pelta: Shielding Transformers to Mitigate Evasion Attacks in Federated Learning—0
Perception-Aware Attack: Creating Adversarial Music via Reverse-Engineering Human Perception—0
Perception Improvement for Free: Exploring Imperceptible Black-box Adversarial Attacks on Image Classification—0
Adversarial Interaction Attack: Fooling AI to Misinterpret Human Intentions—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