Imagen de Portada

DIFFender: Diffusion-Based Adversarial Defense against Patch Attacks

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Kang, Caixin, Dong, Yinpeng, Wang, Zhengyi, Ruan, Shouwei, Chen, Yubo, Su, Hang, Wei, Xingxing
Formato:	Preprint
Publicado:	2023
Materias:	Computer Vision and Pattern Recognition Artificial Intelligence Cryptography and Security Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Real-world Adversarial Defense against Patch Attacks based on Diffusion Model
por: Wei, Xingxing, et al.
Publicado: (2024)

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations
por: Kang, Caixin, et al.
Publicado: (2024)

MMCert: Provable Defense against Adversarial Attacks to Multi-modal Models
por: Wang, Yanting, et al.
Publicado: (2024)

BSPA: Exploring Black-box Stealthy Prompt Attacks against Image Generators
por: Tian, Yu, et al.
Publicado: (2024)

Robust Classification via a Single Diffusion Model
por: Chen, Huanran, et al.
Publicado: (2023)

Anomaly Unveiled: Securing Image Classification against Adversarial Patch Attacks
por: Chattopadhyay, Nandish, et al.
Publicado: (2024)

Robust Image Classification: Defensive Strategies against FGSM and PGD Adversarial Attacks
por: Waghela, Hetvi, et al.
Publicado: (2024)

Towards Transferable Targeted 3D Adversarial Attack in the Physical World
por: Huang, Yao, et al.
Publicado: (2023)

Autoencoder-based Denoising Defense against Adversarial Attacks on Object Detection
por: Song, Min Geun, et al.
Publicado: (2025)

ODDR: Outlier Detection & Dimension Reduction Based Defense Against Adversarial Patches
por: Chattopadhyay, Nandish, et al.
Publicado: (2023)

PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation Efficiency of Adversarial Patch Defenses
por: Xiang, Chong, et al.
Publicado: (2023)

Exploring Adversarial Attacks against Latent Diffusion Model from the Perspective of Adversarial Transferability
por: Chen, Junxi, et al.
Publicado: (2024)

Robustness Analysis against Adversarial Patch Attacks in Fully Unmanned Stores
por: Na, Hyunsik, et al.
Publicado: (2025)

Struggle with Adversarial Defense? Try Diffusion
por: Li, Yujie, et al.
Publicado: (2024)

Membership Inference on Text-to-Image Diffusion Models via Conditional Likelihood Discrepancy
por: Zhai, Shengfang, et al.
Publicado: (2024)

Vulnerabilities in AI-generated Image Detection: The Challenge of Adversarial Attacks
por: Diao, Yunfeng, et al.
Publicado: (2024)

Adversarial Attacks and Defenses on Text-to-Image Diffusion Models: A Survey
por: Zhang, Chenyu, et al.
Publicado: (2024)

Adversarial Training against Location-Optimized Adversarial Patches
por: Rao, Sukrut, et al.
Publicado: (2020)

Towards Physically Realizable Adversarial Attenuation Patch against SAR Object Detection
por: Zhang, Yiming, et al.
Publicado: (2026)

Revisiting Adversarial Patch Defenses on Object Detectors: Unified Evaluation, Large-Scale Dataset, and New Insights
por: Zheng, Junhao, et al.
Publicado: (2025)

Attacking Transformers with Feature Diversity Adversarial Perturbation
por: Gao, Chenxing, et al.
Publicado: (2024)

AdvDreamer Unveils: Are Vision-Language Models Truly Ready for Real-World 3D Variations?
por: Ruan, Shouwei, et al.
Publicado: (2024)

Bounding-box Watermarking: Defense against Model Extraction Attacks on Object Detectors
por: Koda, Satoru, et al.
Publicado: (2024)

Nearest is Not Dearest: Towards Practical Defense against Quantization-conditioned Backdoor Attacks
por: Li, Boheng, et al.
Publicado: (2024)

CAPAA: Classifier-Agnostic Projector-Based Adversarial Attack
por: Li, Zhan, et al.
Publicado: (2025)

MVPatch: More Vivid Patch for Adversarial Camouflaged Attacks on Object Detectors in the Physical World
por: Zhou, Zheng, et al.
Publicado: (2023)

Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models
por: Zhang, Yimeng, et al.
Publicado: (2024)

Training-Free Color-Aware Adversarial Diffusion Sanitization for Diffusion Stegomalware Defense at Security Gateways
por: Frants, Vladimir, et al.
Publicado: (2025)

Mitigating Backdoor Attack by Injecting Proactive Defensive Backdoor
por: Wei, Shaokui, et al.
Publicado: (2024)

Adversarial Sparse Teacher: Defense Against Distillation-Based Model Stealing Attacks Using Adversarial Examples
por: Yilmaz, Eda, et al.
Publicado: (2024)

CAAP: Capture-Aware Adversarial Patch Attacks on Palmprint Recognition Models
por: Liu, Renyang, et al.
Publicado: (2026)

BB-Patch: BlackBox Adversarial Patch-Attack using Zeroth-Order Optimization
por: Kumar, Satyadwyoom, et al.
Publicado: (2024)

Toward Availability Attacks in 3D Point Clouds
por: Zhu, Yifan, et al.
Publicado: (2024)

ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches
por: Pintor, Maura, et al.
Publicado: (2022)

A Survey of Trojan Attacks and Defenses to Deep Neural Networks
por: Jin, Lingxin, et al.
Publicado: (2024)

Survey on Adversarial Attack and Defense for Medical Image Analysis: Methods and Challenges
por: Dong, Junhao, et al.
Publicado: (2023)

Adversarial Defenses via Vector Quantization
por: Dong, Zhiyi, et al.
Publicado: (2023)

Defensive Adversarial CAPTCHA: A Semantics-Driven Framework for Natural Adversarial Example Generation
por: Du, Xia, et al.
Publicado: (2025)

Physical 3D Adversarial Attacks against Monocular Depth Estimation in Autonomous Driving
por: Zheng, Junhao, et al.
Publicado: (2024)

TPatch: A Triggered Physical Adversarial Patch
por: Zhu, Wenjun, et al.
Publicado: (2023)