SOTAVerified

Adversarial Defense

Competitions with currently unpublished results:

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 351–400 of 403 papers

TitleStatusHype
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
Adversarial Defense Framework for Graph Neural Network—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
Towards Black-box Adversarial Example Detection: A Data Reconstruction-based Method—0
Training Robust Deep Neural Networks via Adversarial Noise Propagation—0
Towards Model-Agnostic Adversarial Defenses using Adversarially Trained Autoencoders—0
TREATED:Towards Universal Defense against Textual Adversarial Attacks—0
Tricking Adversarial Attacks To Fail—0
Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness—0
Universal Learning Approach for Adversarial Defense—0
Show:102550
← PrevPage 8 of 9Next →
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