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 701–725 of 1808 papers

TitleStatusHype
Dynamic Adversarial Attacks on Autonomous Driving SystemsCode0
An adversarial attack approach for eXplainable AI evaluation on deepfake detection modelsCode0
OT-Attack: Enhancing Adversarial Transferability of Vision-Language Models via Optimal Transport Optimization—0
A Simple Framework to Enhance the Adversarial Robustness of Deep Learning-based Intrusion Detection System—0
Realistic Scatterer Based Adversarial Attacks on SAR Image Classifiers—0
ScAR: Scaling Adversarial Robustness for LiDAR Object DetectionCode0
InstructTA: Instruction-Tuned Targeted Attack for Large Vision-Language ModelsCode0
TranSegPGD: Improving Transferability of Adversarial Examples on Semantic Segmentation—0
NeRFTAP: Enhancing Transferability of Adversarial Patches on Face Recognition using Neural Radiance Fields—0
Vulnerability Analysis of Transformer-based Optical Character Recognition to Adversarial Attacks—0
RetouchUAA: Unconstrained Adversarial Attack via Image Retouching—0
Adversarial Purification of Information MaskingCode0
Trainwreck: A damaging adversarial attack on image classifiersCode0
When Side-Channel Attacks Break the Black-Box Property of Embedded Artificial Intelligence—0
AdvGen: Physical Adversarial Attack on Face Presentation Attack Detection Systems—0
Generating Valid and Natural Adversarial Examples with Large Language Models—0
Jailbreaking GPT-4V via Self-Adversarial Attacks with System Prompts—0
DA^3: A Distribution-Aware Adversarial Attack against Language Models—0
Learning Globally Optimized Language Structure via Adversarial Training—0
Robust Text Classification: Analyzing Prototype-Based NetworksCode0
Robust Adversarial Attacks Detection for Deep Learning based Relative Pose Estimation for Space Rendezvous—0
Resilient and constrained consensus against adversarial attacks: A distributed MPC framework—0
Transferability Bound Theory: Exploring Relationship between Adversarial Transferability and FlatnessCode0
ABIGX: A Unified Framework for eXplainable Fault Detection and Classification—0
Army of Thieves: Enhancing Black-Box Model Extraction via Ensemble based sample selectionCode0
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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