Adversarial Robustness

Adversarial Robustness evaluates the vulnerabilities of machine learning models under various types of adversarial attacks.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 351–375 of 1746 papers

Title	Date	Tasks	Status	Hype
Cauchy-Schwarz Divergence Information Bottleneck for Regression	Apr 27, 2024	Adversarial RobustnessInformation Plane	CodeCode Available	1
A Comparative Analysis of Adversarial Robustness for Quantum and Classical Machine Learning Models	Apr 24, 2024	Adversarial RobustnessQuantum Machine Learning	—Unverified	0
Adversarial Robustness of Deep Learning-Based Malware Detectors via (De)Randomized Smoothing	Apr 22, 2024	Adversarial Robustness	CodeCode Available	0
Fermi-Bose Machine achieves both generalization and adversarial robustness	Apr 21, 2024	Adversarial RobustnessContrastive Learning	—Unverified	0
GenFighter: A Generative and Evolutive Textual Attack Removal	Apr 17, 2024	Adversarial RobustnessTransfer Learning	—Unverified	0
Efficient Generation of Targeted and Transferable Adversarial Examples for Vision-Language Models Via Diffusion Models	Apr 16, 2024	Adversarial DefenseAdversarial Robustness	CodeCode Available	1
SpamDam: Towards Privacy-Preserving and Adversary-Resistant SMS Spam Detection	Apr 15, 2024	Adversarial RobustnessBackdoor Attack	CodeCode Available	0
Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies	Apr 14, 2024	Adversarial Robustness	CodeCode Available	1
A Survey of Neural Network Robustness Assessment in Image Recognition	Apr 12, 2024	Adversarial Robustnessimage-classification	—Unverified	0
Struggle with Adversarial Defense? Try Diffusion	Apr 12, 2024	Adversarial DefenseAdversarial Robustness	—Unverified	0
Adversarial Robustness of Distilled and Pruned Deep Learning-based Wireless Classifiers	Apr 11, 2024	Adversarial RobustnessKnowledge Distillation	—Unverified	0
Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization	Apr 11, 2024	Adversarial Robustness	CodeCode Available	1
Logit Calibration and Feature Contrast for Robust Federated Learning on Non-IID Data	Apr 10, 2024	Adversarial RobustnessFederated Learning	—Unverified	0
On adversarial training and the 1 Nearest Neighbor classifier	Apr 9, 2024	Adversarial Robustnessimage-classification	CodeCode Available	0
Out-of-Distribution Data: An Acquaintance of Adversarial Examples -- A Survey	Apr 8, 2024	Adversarial RobustnessAnomaly Detection	—Unverified	0
Investigating the Impact of Quantization on Adversarial Robustness	Apr 8, 2024	Adversarial RobustnessQuantization	—Unverified	0
ALERT: A Comprehensive Benchmark for Assessing Large Language Models' Safety through Red Teaming	Apr 6, 2024	Adversarial RobustnessDialogue Safety Prediction	CodeCode Available	2
DiffuseMix: Label-Preserving Data Augmentation with Diffusion Models	Apr 5, 2024	Adversarial RobustnessData Augmentation	—Unverified	0
Evaluating Adversarial Robustness: A Comparison Of FGSM, Carlini-Wagner Attacks, And The Role of Distillation as Defense Mechanism	Apr 5, 2024	Adversarial Robustnessimage-classification	—Unverified	0
On Extending the Automatic Test Markup Language (ATML) for Machine Learning	Apr 4, 2024	Adversarial RobustnessDrift Detection	—Unverified	0
Meta Invariance Defense Towards Generalizable Robustness to Unknown Adversarial Attacks	Apr 4, 2024	Adversarial DefenseAdversarial Robustness	—Unverified	0
BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression Tasks	Apr 1, 2024	Adversarial RobustnessAutonomous Driving	CodeCode Available	1
On Inherent Adversarial Robustness of Active Vision Systems	Mar 29, 2024	Adversarial RobustnessFoveation	—Unverified	0
Towards Sustainable SecureML: Quantifying Carbon Footprint of Adversarial Machine Learning	Mar 27, 2024	Adversarial Robustness	—Unverified	0
Scalable Lipschitz Estimation for CNNs	Mar 27, 2024	Adversarial Robustness	—Unverified	0

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All datasets AdvGLUE CIFAR-10 ImageNet ImageNet-A ImageNet-C Stylized ImageNet CIFAR-100

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	DeBERTa (single model)	Accuracy	0.61	—	Unverified
2	ALBERT (single model)	Accuracy	0.59	—	Unverified
3	T5 (single model)	Accuracy	0.57	—	Unverified
4	SMART_RoBERTa (single model)	Accuracy	0.54	—	Unverified
5	FreeLB (single model)	Accuracy	0.5	—	Unverified
6	RoBERTa (single model)	Accuracy	0.5	—	Unverified
7	InfoBERT (single model)	Accuracy	0.46	—	Unverified
8	ELECTRA (single model)	Accuracy	0.42	—	Unverified
9	BERT (single model)	Accuracy	0.34	—	Unverified
10	SMART_BERT (single model)	Accuracy	0.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Mixed classifier	Accuracy	95.23	—	Unverified
2	Stochastic-LWTA/PGD/WideResNet-34-10	Accuracy	92.26	—	Unverified
3	Stochastic-LWTA/PGD/WideResNet-34-5	Accuracy	91.88	—	Unverified
4	GLOT-DR	Accuracy	84.13	—	Unverified
5	TRADES-ANCRA/ResNet18	Accuracy	81.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResNet-50 (SGD, Cosine)	Accuracy	77.4	—	Unverified
2	ResNet-50 (SGD, Step)	Accuracy	76.9	—	Unverified
3	DeiT-S (AdamW, Cosine)	Accuracy	76.8	—	Unverified
4	ResNet-50 (AdamW, Cosine)	Accuracy	76.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DeiT-S (AdamW, Cosine)	Accuracy	12.2	—	Unverified
2	ResNet-50 (SGD, Cosine)	Accuracy	3.3	—	Unverified
3	ResNet-50 (SGD, Step)	Accuracy	3.2	—	Unverified
4	ResNet-50 (AdamW, Cosine)	Accuracy	3.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResNet-50 (AdamW, Cosine)	mean Corruption Error (mCE)	59.3	—	Unverified
2	ResNet-50 (SGD, Step)	mean Corruption Error (mCE)	57.9	—	Unverified
3	ResNet-50 (SGD, Cosine)	mean Corruption Error (mCE)	56.9	—	Unverified
4	DeiT-S (AdamW, Cosine)	mean Corruption Error (mCE)	48	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DeiT-S (AdamW, Cosine)	Accuracy	13	—	Unverified
2	ResNet-50 (SGD, Cosine)	Accuracy	8.4	—	Unverified
3	ResNet-50 (SGD, Step)	Accuracy	8.3	—	Unverified
4	ResNet-50 (AdamW, Cosine)	Accuracy	8.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Mixed Classifier	Clean Accuracy	85.21	—	Unverified
2	ResNet18/MART-ANCRA	Clean Accuracy	60.1	—	Unverified