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 1461–1470 of 1808 papers

TitleStatusHype
Secure Diagnostics: Adversarial Robustness Meets Clinical Interpretability—0
Attacking the Spike: On the Transferability and Security of Spiking Neural Networks to Adversarial Examples—0
Security Analysis and Enhancement of Model Compressed Deep Learning Systems under Adversarial Attacks—0
Autonomous LLM-Enhanced Adversarial Attack for Text-to-Motion—0
AVTrustBench: Assessing and Enhancing Reliability and Robustness in Audio-Visual LLMs—0
A White-Box Adversarial Attack Against a Digital Twin—0
Security of Deep Learning based Lane Keeping System under Physical-World Adversarial Attack—0
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Meme Stock Prediction—0
Automated Trustworthiness Oracle Generation for Machine Learning Text Classifiers—0
Automated Decision-based 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