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 1081–1090 of 1808 papers

TitleStatusHype
Targeted Attacks on Timeseries Forecasting—0
Target Model Agnostic Adversarial Attacks with Query Budgets on Language Understanding Models—0
TASA: Twin Answer Sentences Attack for Adversarial Context Generation in Question Answering—0
TEAM: Temporal Adversarial Examples Attack Model against Network Intrusion Detection System Applied to RNN—0
Temporal Sparse Adversarial Attack on Sequence-based Gait Recognition—0
TenAd: A Tensor-based Low-rank Black Box Adversarial Attack for Video Classification—0
TESSER: Transfer-Enhancing Adversarial Attacks from Vision Transformers via Spectral and Semantic Regularization—0
TETRIS: Towards Exploring the Robustness of Interactive Segmentation—0
TextAttack: Lessons learned in designing Python frameworks for NLP—0
TextDefense: Adversarial Text Detection based on Word Importance Entropy—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