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

Showing 9761000 of 1808 papers

TitleStatusHype
Discovering Failure Modes of Text-guided Diffusion Models via Adversarial Search0
The Efficacy of SHIELD under Different Threat Models0
MF-CLIP: Leveraging CLIP as Surrogate Models for No-box Adversarial Attacks0
Adversarial Attacks on Time-Series Intrusion Detection for Industrial Control Systems0
Exploring the Robustness of NMT Systems to Nonsensical Inputs0
Investigating Decision Boundaries of Trained Neural Networks0
The FEVER2.0 Shared Task0
Investigating Resistance of Deep Learning-based IDS against Adversaries using min-max Optimization0
Investigating the significance of adversarial attacks and their relation to interpretability for radar-based human activity recognition systems0
Investigating Vulnerability to Adversarial Examples on Multimodal Data Fusion in Deep Learning0
A Formalization of Robustness for Deep Neural Networks0
Utilizing Multimodal Feature Consistency to Detect Adversarial Examples on Clinical Summaries0
Affine Disentangled GAN for Interpretable and Robust AV Perception0
AEMIM: Adversarial Examples Meet Masked Image Modeling0
The Impacts of Unanswerable Questions on the Robustness of Machine Reading Comprehension Models0
I See Dead People: Gray-Box Adversarial Attack on Image-To-Text Models0
Learning Task-aware Robust Deep Learning Systems0
Is It Time to Redefine the Classification Task for Deep Learning Systems?0
Isolated and Ensemble Audio Preprocessing Methods for Detecting Adversarial Examples against Automatic Speech Recognition0
Variational Quantum Cloning: Improving Practicality for Quantum Cryptanalysis0
Iterative Adversarial Attack on Image-guided Story Ending Generation0
ITPatch: An Invisible and Triggered Physical Adversarial Patch against Traffic Sign Recognition0
Adversarial Rain Attack and Defensive Deraining for DNN Perception0
JailbreakHunter: A Visual Analytics Approach for Jailbreak Prompts Discovery from Large-Scale Human-LLM Conversational Datasets0
Jailbreaking GPT-4V via Self-Adversarial Attacks with System Prompts0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Xu et al.Attack: PGD2078.68Unverified
23-ensemble of multi-resolution self-ensemblesAttack: AutoAttack78.13Unverified
3TRADES-ANCRA/ResNet18Attack: AutoAttack59.7Unverified
4AdvTraining [madry2018]Attack: PGD2048.44Unverified
5TRADES [zhang2019b]Attack: PGD2045.9Unverified
6XU-NetRobust Accuracy1Unverified
#ModelMetricClaimedVerifiedStatus
13-ensemble of multi-resolution self-ensemblesAttack: AutoAttack51.28Unverified
2multi-resolution self-ensemblesAttack: AutoAttack47.85Unverified