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 1611–1620 of 1808 papers

TitleStatusHype
Covariate Balancing Methods for Randomized Controlled Trials Are Not Adversarially Robust—0
COVER: A Heuristic Greedy Adversarial Attack on Prompt-based Learning in Language Models—0
Critical Checkpoints for Evaluating Defence Models Against Adversarial Attack and Robustness—0
Universal Adversarial Attack on Aligned Multimodal LLMs—0
Cross-Modality Attack Boosted by Gradient-Evolutionary Multiform Optimization—0
Cross-Task Attack: A Self-Supervision Generative Framework Based on Attention Shift—0
SIGL: Securing Software Installations Through Deep Graph Learning—0
CuDA2: An approach for Incorporating Traitor Agents into Cooperative Multi-Agent Systems—0
Signal Adversarial Examples Generation for Signal Detection Network via White-Box Attack—0
Curvature Dynamic Black-box Attack: revisiting adversarial robustness via dynamic curvature estimation—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