Cover Image

Real-world Adversarial Defense against Patch Attacks based on Diffusion Model

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wei, Xingxing, Kang, Caixin, Dong, Yinpeng, Wang, Zhengyi, Ruan, Shouwei, Chen, Yubo, Su, Hang
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence Cryptography and Security Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DIFFender: Diffusion-Based Adversarial Defense against Patch Attacks
by: Kang, Caixin, et al.
Published: (2023)

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

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

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

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

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

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

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

Breaking the Ceiling: Exploring the Potential of Jailbreak Attacks through Expanding Strategy Space
by: Huang, Yao, et al.
Published: (2025)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Adversarial Defenses via Vector Quantization
by: Dong, Zhiyi, et al.
Published: (2023)

Efficient Backdoor Attacks for Deep Neural Networks in Real-world Scenarios
by: Li, Ziqiang, et al.
Published: (2023)

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

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

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

Enhancing Remote Adversarial Patch Attacks on Face Detectors with Tiling and Scaling
by: Okano, Masora, et al.
Published: (2024)