Adversarial Examples are Misaligned in Diffusion Model Manifolds
Fuente:
arXiv
Saved in:
| Main Authors: | Lorenz, Peter, Durall, Ricard, Keuper, Janis |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial Detection
by: Lorenz, Peter, et al.
Published: (2022)
by: Lorenz, Peter, et al.
Published: (2022)
Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness?
by: Lorenz, Peter, et al.
Published: (2021)
by: Lorenz, Peter, et al.
Published: (2021)
Detecting AutoAttack Perturbations in the Frequency Domain
by: Lorenz, Peter, et al.
Published: (2021)
by: Lorenz, Peter, et al.
Published: (2021)
DiffProtect: Generate Adversarial Examples with Diffusion Models for Facial Privacy Protection
by: Liu, Jiang, et al.
Published: (2023)
by: Liu, Jiang, et al.
Published: (2023)
Transcending Adversarial Perturbations: Manifold-Aided Adversarial Examples with Legitimate Semantics
by: Li, Shuai, et al.
Published: (2024)
by: Li, Shuai, et al.
Published: (2024)
Deciphering the Definition of Adversarial Robustness for post-hoc OOD Detectors
by: Lorenz, Peter, et al.
Published: (2024)
by: Lorenz, Peter, et al.
Published: (2024)
Defensive Adversarial CAPTCHA: A Semantics-Driven Framework for Natural Adversarial Example Generation
by: Du, Xia, et al.
Published: (2025)
by: Du, Xia, et al.
Published: (2025)
Time Traveling to Defend Against Adversarial Example Attacks in Image Classification
by: Etim, Anthony, et al.
Published: (2024)
by: Etim, Anthony, et al.
Published: (2024)
A Random Ensemble of Encrypted models for Enhancing Robustness against Adversarial Examples
by: Iijima, Ryota, et al.
Published: (2024)
by: Iijima, Ryota, et al.
Published: (2024)
ViTGuard: Attention-aware Detection against Adversarial Examples for Vision Transformer
by: Sun, Shihua, et al.
Published: (2024)
by: Sun, Shihua, et al.
Published: (2024)
Signal Adversarial Examples Generation for Signal Detection Network via White-Box Attack
by: Li, Dongyang, et al.
Published: (2024)
by: Li, Dongyang, et al.
Published: (2024)
Enhancing Adversarial Example Detection Through Model Explanation
by: Ma, Qian, et al.
Published: (2025)
by: Ma, Qian, et al.
Published: (2025)
Rethinking Robust Adversarial Concept Erasure in Diffusion Models
by: Yin, Qinghong, et al.
Published: (2025)
by: Yin, Qinghong, et al.
Published: (2025)
Transferable Adversarial Examples with Bayes Approach
by: Fan, Mingyuan, et al.
Published: (2022)
by: Fan, Mingyuan, et al.
Published: (2022)
Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models
by: Zhang, Yimeng, et al.
Published: (2024)
by: Zhang, Yimeng, et al.
Published: (2024)
Struggle with Adversarial Defense? Try Diffusion
by: Li, Yujie, et al.
Published: (2024)
by: Li, Yujie, et al.
Published: (2024)
Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation
by: Yu, Yi, et al.
Published: (2025)
by: Yu, Yi, et al.
Published: (2025)
Adversarial Sparse Teacher: Defense Against Distillation-Based Model Stealing Attacks Using Adversarial Examples
by: Yilmaz, Eda, et al.
Published: (2024)
by: Yilmaz, Eda, et al.
Published: (2024)
LightPure: Realtime Adversarial Image Purification for Mobile Devices Using Diffusion Models
by: Khalili, Hossein, et al.
Published: (2024)
by: Khalili, Hossein, et al.
Published: (2024)
Improving Transferability of Adversarial Examples via Bayesian Attacks
by: Li, Qizhang, et al.
Published: (2023)
by: Li, Qizhang, et al.
Published: (2023)
SAP-DIFF: Semantic Adversarial Patch Generation for Black-Box Face Recognition Models via Diffusion Models
by: Wang, Mingsi, et al.
Published: (2025)
by: Wang, Mingsi, et al.
Published: (2025)
Controllable Adversarial Makeup for Privacy via Text-Guided Diffusion
by: Kwon, Youngjin, et al.
Published: (2025)
by: Kwon, Youngjin, et al.
Published: (2025)
Universal Adversarial Purification with DDIM Metric Loss for Stable Diffusion
by: Zheng, Li, et al.
Published: (2026)
by: Zheng, Li, 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)
by: Frants, Vladimir, et al.
Published: (2025)
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples
by: Cinà, Antonio Emanuele, et al.
Published: (2024)
by: Cinà, Antonio Emanuele, et al.
Published: (2024)
AED-PADA:Improving Generalizability of Adversarial Example Detection via Principal Adversarial Domain Adaptation
by: Peng, Heqi, et al.
Published: (2024)
by: Peng, Heqi, et al.
Published: (2024)
LoyalDiffusion: A Diffusion Model Guarding Against Data Replication
by: Li, Chenghao, et al.
Published: (2024)
by: Li, Chenghao, et al.
Published: (2024)
Unlearnable Examples Detection via Iterative Filtering
by: Yu, Yi, et al.
Published: (2024)
by: Yu, Yi, et al.
Published: (2024)
Semantic Deep Hiding for Robust Unlearnable Examples
by: Meng, Ruohan, et al.
Published: (2024)
by: Meng, Ruohan, et al.
Published: (2024)
DataCook: Crafting Anti-Adversarial Examples for Healthcare Data Copyright Protection
by: Shang, Sihan, et al.
Published: (2024)
by: Shang, Sihan, et al.
Published: (2024)
Improving Integrated Gradient-based Transferable Adversarial Examples by Refining the Integration Path
by: Ren, Yuchen, et al.
Published: (2024)
by: Ren, Yuchen, et al.
Published: (2024)
$σ$-zero: Gradient-based Optimization of $\ell_0$-norm Adversarial Examples
by: Cinà, Antonio Emanuele, et al.
Published: (2024)
by: Cinà, Antonio Emanuele, et al.
Published: (2024)
Generating Image Adversarial Examples by Embedding Digital Watermarks
by: Xiang, Yuexin, et al.
Published: (2020)
by: Xiang, Yuexin, et al.
Published: (2020)
Exploring Adversarial Attacks against Latent Diffusion Model from the Perspective of Adversarial Transferability
by: Chen, Junxi, et al.
Published: (2024)
by: Chen, Junxi, et al.
Published: (2024)
Boosting Adversarial Transferability with Spatial Adversarial Alignment
by: Chen, Zhaoyu, et al.
Published: (2025)
by: Chen, Zhaoyu, et al.
Published: (2025)
Mitigate Replication and Copying in Diffusion Models with Generalized Caption and Dual Fusion Enhancement
by: Li, Chenghao, et al.
Published: (2023)
by: Li, Chenghao, et al.
Published: (2023)
Security Risk of Misalignment between Text and Image in Multi-modal Model
by: Wang, Xiaosen, et al.
Published: (2025)
by: Wang, Xiaosen, et al.
Published: (2025)
ROBIN: Robust and Invisible Watermarks for Diffusion Models with Adversarial Optimization
by: Huang, Huayang, et al.
Published: (2024)
by: Huang, Huayang, et al.
Published: (2024)
MMA-Diffusion: MultiModal Attack on Diffusion Models
by: Yang, Yijun, et al.
Published: (2023)
by: Yang, Yijun, et al.
Published: (2023)
Jailbreak Vision Language Models via Bi-Modal Adversarial Prompt
by: Ying, Zonghao, et al.
Published: (2024)
by: Ying, Zonghao, et al.
Published: (2024)
Similar Items
-
Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial Detection
by: Lorenz, Peter, et al.
Published: (2022) -
Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness?
by: Lorenz, Peter, et al.
Published: (2021) -
Detecting AutoAttack Perturbations in the Frequency Domain
by: Lorenz, Peter, et al.
Published: (2021) -
DiffProtect: Generate Adversarial Examples with Diffusion Models for Facial Privacy Protection
by: Liu, Jiang, et al.
Published: (2023) -
Transcending Adversarial Perturbations: Manifold-Aided Adversarial Examples with Legitimate Semantics
by: Li, Shuai, et al.
Published: (2024)