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Adversarial Purification

A class of adversarial defense methods that remove adversarial perturbations using a generative model.

Papers

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Showing 26–50 of 65 papers

TitleStatusHype
ADBM: Adversarial diffusion bridge model for reliable adversarial purification—0
Diffusion-based Adversarial Purification for Intrusion DetectionCode0
ZeroPur: Succinct Training-Free Adversarial PurificationCode0
Large Language Model Sentinel: LLM Agent for Adversarial Purification—0
Towards Understanding the Robustness of Diffusion-Based Purification: A Stochastic Perspective—0
Adversarial purification for no-reference image-quality metrics: applicability study and new methods—0
Robust Diffusion Models for Adversarial Purification—0
Robust Overfitting Does Matter: Test-Time Adversarial Purification With FGSMCode0
PCLD: Point Cloud Layerwise Diffusion for Adversarial PurificationCode0
Adversarial Purification and Fine-tuning for Robust UDC Image Restoration—0
Adversarial Text Purification: A Large Language Model Approach for Defense—0
Adversarial Training on Purification (AToP): Advancing Both Robustness and GeneralizationCode1
PuriDefense: Randomized Local Implicit Adversarial Purification for Defending Black-box Query-based Attacks—0
MalPurifier: Enhancing Android Malware Detection with Adversarial Purification against Evasion AttacksCode1
MimicDiffusion: Purifying Adversarial Perturbation via Mimicking Clean Diffusion Model—0
Adversarial Purification of Information MaskingCode0
Diffusion models meet image counter-forensicsCode1
Adversarial Purification for Data-Driven Power System Event Classifiers with Diffusion Models—0
Purify++: Improving Diffusion-Purification with Advanced Diffusion Models and Control of Randomness—0
DiffAttack: Evasion Attacks Against Diffusion-Based Adversarial PurificationCode1
Diffusion-Based Adversarial Purification for Speaker Verification—0
Language Guided Adversarial PurificationCode0
Advancing Adversarial Robustness Through Adversarial Logit Update—0
DiffSmooth: Certifiably Robust Learning via Diffusion Models and Local SmoothingCode0
Universal Adversarial Defense in Remote Sensing Based on Pre-trained Denoising Diffusion ModelsCode1
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