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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 51–65 of 65 papers

TitleStatusHype
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
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
Rapid Plug-in Defenders—0
Carefully Blending Adversarial Training, Purification, and Aggregation Improves Adversarial RobustnessCode0
Adversarial Purification with the Manifold Hypothesis—0
Towards Adversarial Purification using Denoising AutoEncoders—0
Guided Diffusion Model for Adversarial Purification from Random Noise—0
Text Adversarial Purification as Defense against Adversarial Attacks—0
Adversarial Purification through Representation Disentanglement—0
Online Adversarial Purification based on Self-Supervision—0
Online Adversarial Purification based on Self-supervised Learning—0
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