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 176–200 of 1808 papers

TitleStatusHype
R&R: Metric-guided Adversarial Sentence GenerationCode1
GE-AdvGAN: Improving the transferability of adversarial samples by gradient editing-based adversarial generative modelCode1
Adversarial Immunization for Certifiable Robustness on GraphsCode1
Attacking Recommender Systems with Augmented User ProfilesCode1
Generalizing Universal Adversarial Attacks Beyond Additive PerturbationsCode1
CausalAdv: Adversarial Robustness through the Lens of CausalityCode1
Adversarial Laser Beam: Effective Physical-World Attack to DNNs in a BlinkCode1
Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query AttacksCode1
Adversarial Learning for Robust Deep ClusteringCode1
Adversarial Attack on Community Detection by Hiding IndividualsCode1
Attacking Video Recognition Models with Bullet-Screen CommentsCode1
Audio Jailbreak Attacks: Exposing Vulnerabilities in SpeechGPT in a White-Box FrameworkCode1
Hard No-Box Adversarial Attack on Skeleton-Based Human Action Recognition with Skeleton-Motion-Informed GradientCode1
Adversarial Attack on Deep Learning-Based Splice LocalizationCode1
Augmented Lagrangian Adversarial AttacksCode1
Data-free Universal Adversarial Perturbation with Pseudo-semantic PriorCode1
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock PredictionCode1
Contextualized Perturbation for Textual Adversarial AttackCode1
On the Multi-modal Vulnerability of Diffusion ModelsCode1
Adversarial Attack on Graph Neural Networks as An Influence Maximization ProblemCode1
Adversarial Magnification to Deceive Deepfake Detection through Super ResolutionCode1
High Frequency Component Helps Explain the Generalization of Convolutional Neural NetworksCode1
Adversarial Mask: Real-World Universal Adversarial Attack on Face Recognition ModelCode1
Benchmarking Adversarial Robustness on Image ClassificationCode1
CMUA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating DeepfakesCode1
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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