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

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Showing 301–350 of 1808 papers

TitleStatusHype
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-LearningCode1
On Improving Adversarial Transferability of Vision TransformersCode1
Character-level White-Box Adversarial Attacks against Transformers via Attachable Subwords SubstitutionCode1
CgAT: Center-Guided Adversarial Training for Deep Hashing-Based RetrievalCode1
An Analysis of Recent Advances in Deepfake Image Detection in an Evolving Threat LandscapeCode1
An Efficient Adversarial Attack for Tree EnsemblesCode1
Adversarial Attack and Defense in Deep RankingCode1
On the Multi-modal Vulnerability of Diffusion ModelsCode1
Order-Disorder: Imitation Adversarial Attacks for Black-box Neural Ranking ModelsCode1
OUTFOX: LLM-Generated Essay Detection Through In-Context Learning with Adversarially Generated ExamplesCode1
Adversarial Attack and Defense of Structured Prediction ModelsCode1
Combining GANs and AutoEncoders for Efficient Anomaly DetectionCode1
Composite Adversarial AttacksCode1
An Extensive Study on Adversarial Attack against Pre-trained Models of CodeCode1
Adversarial Attack and Defense of YOLO Detectors in Autonomous Driving ScenariosCode1
Contextualized Perturbation for Textual Adversarial AttackCode1
An integrated Auto Encoder-Block Switching defense approach to prevent adversarial attacksCode1
Controlling Whisper: Universal Acoustic Adversarial Attacks to Control Speech Foundation ModelsCode1
Guardians of Image Quality: Benchmarking Defenses Against Adversarial Attacks on Image Quality MetricsCode1
CyberLLMInstruct: A New Dataset for Analysing Safety of Fine-Tuned LLMs Using Cyber Security DataCode1
Rob-GAN: Generator, Discriminator, and Adversarial AttackerCode0
From Adversarial Arms Race to Model-centric Evaluation: Motivating a Unified Automatic Robustness Evaluation FrameworkCode0
From Flexibility to Manipulation: The Slippery Slope of XAI EvaluationCode0
Accelerated Stochastic Gradient-free and Projection-free MethodsCode0
Forging and Removing Latent-Noise Diffusion Watermarks Using a Single ImageCode0
Transferability Bound Theory: Exploring Relationship between Adversarial Transferability and FlatnessCode0
AdvPC: Transferable Adversarial Perturbations on 3D Point CloudsCode0
FenceBox: A Platform for Defeating Adversarial Examples with Data Augmentation TechniquesCode0
FireBERT: Hardening BERT-based classifiers against adversarial attackCode0
FMM-Attack: A Flow-based Multi-modal Adversarial Attack on Video-based LLMsCode0
AdvHat: Real-world adversarial attack on ArcFace Face ID systemCode0
Feature Space Perturbations Yield More Transferable Adversarial ExamplesCode0
AdvGPS: Adversarial GPS for Multi-Agent Perception AttackCode0
AccelAT: A Framework for Accelerating the Adversarial Training of Deep Neural Networks through Accuracy GradientCode0
FDA: Feature Disruptive AttackCode0
Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate GradientsCode0
Foiling Explanations in Deep Neural NetworksCode0
GenAttack: Practical Black-box Attacks with Gradient-Free OptimizationCode0
advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorchCode0
Advancing Adversarial Robustness in GNeRFs: The IL2-NeRF AttackCode0
Fast Inference of Removal-Based Node InfluenceCode0
Fast Adversarial CNN-based Perturbation Attack of No-Reference Image Quality MetricsCode0
Fashion-Guided Adversarial Attack on Person SegmentationCode0
Exploiting vulnerabilities of deep neural networks for privacy protectionCode0
Adversarial Training for Physics-Informed Neural NetworksCode0
Exploring the Vulnerability of Natural Language Processing Models via Universal Adversarial TextsCode0
Explainable and Safe Reinforcement Learning for Autonomous Air MobilityCode0
Adversarial Attack and Defense for Non-Parametric Two-Sample TestsCode0
Explainable Graph Neural Networks Under FireCode0
Adversarial Self-Defense for Cycle-Consistent GANsCode0
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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