SOTAVerified

Adversarial Defense

Competitions with currently unpublished results:

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–250 of 403 papers

TitleStatusHype
MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense—0
MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking—0
MirrorCheck: Efficient Adversarial Defense for Vision-Language Models—0
Modeling Adversarial Noise for Adversarial Defense—0
Multi-head Uncertainty Inference for Adversarial Attack Detection—0
On the Susceptibility and Robustness of Time Series Models through Adversarial Attack and Defense—0
Bridging Optimal Transport and Jacobian Regularization by Optimal Trajectory for Enhanced Adversarial Defense—0
Perceptual Adversarial Robustness: Generalizable Defenses Against Unforeseen Threat Models—0
Perseus: Leveraging Common Data Patterns with Curriculum Learning for More Robust Graph Neural Networks—0
Physically Realizable Adversarial Examples for LiDAR Object Detection—0
Pixel Redrawn For A Robust Adversarial Defense—0
Privacy-preserving Universal Adversarial Defense for Black-box Models—0
Proactive Adversarial Defense: Harnessing Prompt Tuning in Vision-Language Models to Detect Unseen Backdoored Images—0
PuVAE: A Variational Autoencoder to Purify Adversarial Examples—0
RAILS: A Robust Adversarial Immune-inspired Learning System—0
The Best Defense is Attack: Repairing Semantics in Textual Adversarial Examples—0
Rebuild and Ensemble: Exploring Defense Against Text Adversaries—0
Text Adversarial Purification as Defense against Adversarial Attacks—0
Releasing Inequality Phenomena in L_-Adversarial Training via Input Gradient Distillation—0
Revisiting and Advancing Adversarial Training Through A Simple Baseline—0
Rethinking Invariance Regularization in Adversarial Training to Improve Robustness-Accuracy Trade-off—0
Rethinking Textual Adversarial Defense for Pre-trained Language Models—0
Revisiting Role of Autoencoders in Adversarial Settings—0
Robust Adversarial Defense by Tensor Factorization—0
Robust Android Malware Detection System against Adversarial Attacks using Q-Learning—0
Robust Boosting Forests with Richer Deep Feature Hierarchy—0
Robust Deep Reinforcement Learning in Robotics via Adaptive Gradient-Masked Adversarial Attacks—0
Robust Image Classification: Defensive Strategies against FGSM and PGD Adversarial Attacks—0
RobustPdM: Designing Robust Predictive Maintenance against Adversarial Attacks—0
SAD: Saliency Adversarial Defense without Adversarial Training—0
Scale-Invariant Adversarial Attack for Evaluating and Enhancing Adversarial Defenses—0
A^3D: A Platform of Searching for Robust Neural Architectures and Efficient Adversarial Attacks—0
Secure Video Quality Assessment Resisting Adversarial Attacks—0
Self-Gradient Networks—0
NCIS: Neural Contextual Iterative Smoothing for Purifying Adversarial Perturbations—0
ShieldLearner: A New Paradigm for Jailbreak Attack Defense in LLMs—0
Simple and Effective Stochastic Neural Networks—0
Stochastic-Shield: A Probabilistic Approach Towards Training-Free Adversarial Defense in Quantized CNNs—0
Struggle with Adversarial Defense? Try Diffusion—0
Subspace Defense: Discarding Adversarial Perturbations by Learning a Subspace for Clean Signals—0
Sustainable Self-evolution Adversarial Training—0
Sylva: Tailoring Personalized Adversarial Defense in Pre-trained Models via Collaborative Fine-tuning—0
Target Training: Tricking Adversarial Attacks to Fail—0
TART: Boosting Clean Accuracy Through Tangent Direction Guided Adversarial Training—0
Test-time Adversarial Defense with Opposite Adversarial Path and High Attack Time Cost—0
The Good, the Bad and the Ugly: Watermarks, Transferable Attacks and Adversarial Defenses—0
The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing—0
Towards Achieving Adversarial Robustness Beyond Perceptual Limits—0
Towards a constructive framework for control theory—0
Towards Adversarial-Resilient Deep Neural Networks for False Data Injection Attack Detection in Power Grids—0
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All datasetsCIFAR-10ImageNet (non-targeted PGD, max perturbation=4)ImageNetImageNet (targeted PGD, max perturbation=16)MNISTCAAD 2018miniImageNet

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1WRN-28-10Accuracy90.03—Unverified
2Diffusion ClassifierAccuracy89.85—Unverified
3Stochastic-LWTA/PGD/WideResNet-34-10Accuracy84.3—Unverified
4Ours (Stochastic-LWTA/PGD/WideResNet-34-5)Accuracy83.4—Unverified
5Ours (Stochastic-LWTA/PGD/WideResNet-34-1)Accuracy81.87—Unverified
6ResNet18 (TRADES-ANCRA/PGD-40)Accuracy81.7—Unverified
7Stochastic-LWTA/PGD/WideResNet-34-5Attack: AutoAttack81.22—Unverified
8PCL (against PGD, white box)Accuracy46.7—Unverified
#ModelMetricClaimedVerifiedStatus
1SAT-EfficientNet-L1Accuracy58.6—Unverified
2LLR-ResNet-152Accuracy47—Unverified
3ResNet-152 free-m=4Accuracy36—Unverified
4ResNet-101 free-m=4Accuracy34.3—Unverified
5ResNet-50 free-m=4Accuracy31.8—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet101Accuracy99.8—Unverified
2InceptionV3Accuracy98.6—Unverified
3Feature DenoisingAccuracy49.5—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet-152 DenoiseAccuracy42.8—Unverified
2ResNeXt-101 DenoiseAllAccuracy40.4—Unverified
3ResNet-152Accuracy39—Unverified
#ModelMetricClaimedVerifiedStatus
1Defense GANAccuracy0.85—Unverified
2PuVAEAccuracy0.81—Unverified
#ModelMetricClaimedVerifiedStatus
1Feature DenoisingAccuracy50.6—Unverified
#ModelMetricClaimedVerifiedStatus
1Auto Encoder-Block Switching defense with GradCAMAccuracy 88.54—Unverified