1. DIFFender: Diffusion-Based Adversarial Defense against Patch Attacks in the Physical World
    Caixin Kang, Yinpeng Dong, Zhengyi Wang, Shouwei Ruan, Hang Su, Xingxing Wei
    arXiv 2023. Paper  
    2023-06-15
    2023-06-15
  2. An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization
    Fei Kong, Jinhao Duan, RuiPeng Ma, Hengtao Shen, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu
    arXiv 2023. Paper  
    2023-05-26
    2023-05-26
  3. Differentially Private Latent Diffusion Models
    Saiyue Lyu, Margarita Vinaroz, Michael F. Liu, Mijung Park
    arXiv 2023. Paper  
    2023-05-25
    2023-05-25
  4. Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability
    Haotian Xue, Alexandre Araujo, Bin Hu, Yongxin Chen
    arXiv 2023. Paper   Github  
    2023-05-25
    2023-05-25
  5. Latent Magic: An Investigation into Adversarial Examples Crafted in the Semantic Latent Space
    BoYang Zheng
    arXiv 2023. Paper  
    2023-05-22
    2023-05-22
  6. Mist: Towards Improved Adversarial Examples for Diffusion Models
    Chumeng Liang, Xiaoyu Wu
    arXiv 2023. Paper  
    2023-05-22
    2023-05-22
  7. Zero-Day Backdoor Attack against Text-to-Image Diffusion Models via Personalization
    Yihao Huang, Qing Guo, Felix Juefei-Xu
    arXiv 2023. Paper  
    2023-05-18
    2023-05-18
  8. Content-based Unrestricted Adversarial Attack
    Zhaoyu Chen, Bo Li, Shuang Wu, Kaixun Jiang, Shouhong Ding, Wenqiang Zhang
    arXiv 2023. Paper  
    2023-05-18
    2023-05-18
  9. Raising the Bar for Certified Adversarial Robustness with Diffusion Models
    Thomas Altstidl, David Dobre, Björn Eskofier, Gauthier Gidel, Leo Schwinn
    arXiv 2023. Paper  
    2023-05-17
    2023-05-17
  10. On enhancing the robustness of Vision Transformers: Defensive Diffusion
    Raza Imam, Muhammad Huzaifa, Mohammed El-Amine Azz
    arXiv 2023. Paper   Github  
    2023-05-14
    2023-05-14
  11. Diffusion Models for Imperceptible and Transferable Adversarial Attack
    Jianqi Chen, Hao Chen, Keyan Chen, Yilan Zhang, Zhengxia Zou, Zhenwei Shi
    arXiv 2023. Paper   Github  
    2023-05-14
    2023-05-14
  12. Generative Steganography Diffusion
    Ping Wei, Qing Zhou, Zichi Wang, Zhenxing Qian, Xinpeng Zhang, Sheng Li
    arXiv 2023. Paper  
    2023-05-05
    2023-05-05
  13. A Pilot Study of Query-Free Adversarial Attack against Stable Diffusion
    Haomin Zhuang, Yihua Zhang, Sijia Liu
    CVPR Workshop 2023. Paper  
    2023-04-03
    2023-04-03
  14. Black-box Backdoor Defense via Zero-shot Image Purification
    Yucheng Shi, Mengnan Du, Xuansheng Wu, Zihan Guan, Ninghao Liu
    arXiv 2023. Paper  
    2023-03-21
    2023-03-21
  15. Adversarial Counterfactual Visual Explanations
    Guillaume Jeanneret, Loïc Simon, Frédéric Jurie
    CVPR 2023. Paper   Github  
    2023-03-17
    2023-03-17
  16. Robust Evaluation of Diffusion-Based Adversarial Purification
    Minjong Lee, Dongwoo Kim
    ICLR 2023. Paper  
    2023-03-16
    2023-03-16
  17. The Devil's Advocate: Shattering the Illusion of Unexploitable Data using Diffusion Models
    Hadi M. Dolatabadi, Sarah Erfani, Christopher Leckie
    arXiv 2023. Paper  
    2023-03-15
    2023-03-15
  18. TrojDiff: Trojan Attacks on Diffusion Models with Diverse Targets
    Weixin Chen, Dawn Song, Bo Li
    CVPR 2023. Paper   Github  
    2023-03-10
    2023-03-10
  19. Generative Model-Based Attack on Learnable Image Encryption for Privacy-Preserving Deep Learning
    AprilPyone MaungMaung, Hitoshi Kiya
    arXiv 2023. Paper  
    2023-03-09
    2023-03-09
  20. Differentially Private Diffusion Models Generate Useful Synthetic Images
    Sahra Ghalebikesabi, Leonard Berrada, Sven Gowal, Ira Ktena, Robert Stanforth, Jamie Hayes, Soham De, Samuel L. Smith, Olivia Wiles, Borja Balle
    arXiv 2023. Paper  
    2023-02-27
    2023-02-27
  21. Data Forensics in Diffusion Models: A Systematic Analysis of Membership Privacy
    Derui Zhu, Dingfan Chen, Jens Grossklags, Mario Fritz
    arXiv 2023. Paper  
    2023-02-15
    2023-02-15
  22. Raising the Cost of Malicious AI-Powered Image Editing
    Hadi Salman, Alaa Khaddaj, Guillaume Leclerc, Andrew Ilyas, Aleksander Madry
    arXiv 2023. Paper   Github  
    2023-02-13
    2023-02-13
  23. Better Diffusion Models Further Improve Adversarial Training
    Zekai Wang, Tianyu Pang, Chao Du, Min Lin, Weiwei Liu, Shuicheng Yan
    arXiv 2023. Paper   Github  
    2023-02-09
    2023-02-09
  24. Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples
    Chumeng Liang, Xiaoyu Wu, Yang Hua, Jiaru Zhang, Yiming Xue, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan
    arXiv 2023. Paper  
    2023-02-09
    2023-02-09
  25. Membership Inference Attacks against Diffusion Models
    Tomoya Matsumoto, Takayuki Miura, Naoto Yanai
    arXiv 2023. Paper  
    2023-02-07
    2023-02-07
  26. MorDIFF: Recognition Vulnerability and Attack Detectability of Face Morphing Attacks Created by Diffusion Autoencoders
    Naser Damer, Meiling Fang, Patrick Siebke, Jan Niklas Kolf, Marco Huber, Fadi Boutros
    IWBF 2023. Paper   Github  
    2023-02-03
    2023-02-03
  27. Are Diffusion Models Vulnerable to Membership Inference Attacks?
    Jinhao Duan, Fei Kong, Shiqi Wang, Xiaoshuang Shi, Kaidi Xu
    arXiv 2023. Paper  
    2023-02-02
    2023-02-02
  28. Extracting Training Data from Diffusion Models
    Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, Eric Wallace
    arXiv 2023. Paper  
    2023-02-02
    2023-02-02
  29. Salient Conditional Diffusion for Defending Against Backdoor Attacks
    Brandon B. May, N. Joseph Tatro, Piyush Kumar, Nathan Shnidman
    ICLR Workshop 2023. Paper  
    2023-01-31
    2023-01-31
  30. Extracting Training Data from Diffusion Models
    Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, Eric Wallace
    arXiv 2023. Paper  
    2023-01-30
    2023-01-30
  31. Membership Inference of Diffusion Models
    Hailong Hu, Jun Pang
    arXiv 2023. Paper  
    2023-01-24
    2023-01-24
  32. Denoising Diffusion Probabilistic Models as a Defense against Adversarial Attacks
    Lars Lien Ankile, Anna Midgley, Sebastian Weisshaar
    arXiv 2023. Paper   Github  
    2023-01-17
    2023-01-17
  33. DensePure: Understanding Diffusion Models towards Adversarial Robustness
    Chaowei Xiao, Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Weili Nie, Mingyan Liu, Anima Anandkumar, Bo Li, Dawn Song
    NeurIPS 2022. Paper  
    2022-11-01
    2022-11-01
  34. Differentially Private Diffusion Models
    Tim Dockhorn, Tianshi Cao, Arash Vahdat, Karsten Kreis
    arXiv 2022. Paper   Project  
    2022-10-18
    2022-10-18
  35. Improving Adversarial Robustness by Contrastive Guided Diffusion Process
    Yidong Ouyang, Liyan Xie, Guang Cheng
    arXiv 2022. Paper  
    2022-10-18
    2022-10-18
  36. Fight Fire With Fire: Reversing Skin Adversarial Examples by Multiscale Diffusive and Denoising Aggregation Mechanism
    Yongwei Wang, Yuan Li, Zhiqi Shen
    arXiv 2022. Paper  
    2022-08-22
    2022-08-22
  37. PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D Point Cloud Recognition
    Jiachen Sun, Weili Nie, Zhiding Yu, Z. Morley Mao, Chaowei Xiao
    arXiv 2022. Paper  
    2022-08-21
    2022-08-21
  38. Threat Model-Agnostic Adversarial Defense using Diffusion Models
    Tsachi Blau, Roy Ganz, Bahjat Kawar, Alex Bronstein, Michael Elad
    arXiv 2022. Paper   Github  
    2022-07-17
    2022-07-17
  39. Back to the Source: Diffusion-Driven Test-Time Adaptation
    Jin Gao, Jialing Zhang, Xihui Liu, Trevor Darrell, Evan Shelhamer, Dequan Wang
    arXiv 2022. Paper   Github  
    2022-07-07
    2022-07-07
  40. (Certified!!) Adversarial Robustness for Free!
    Nicholas Carlini, Florian Tramer, Krishnamurthy (Dj)Dvijotham, J. Zico Kolter
    ICLR 2023. Paper  
    2022-06-21
    2022-06-21
  41. Guided Diffusion Model for Adversarial Purification from Random Noise
    Quanlin Wu, Hang Ye, Yuntian Gu
    arXiv 2022. Paper  
    2022-06-17
    2022-06-17
  42. Guided Diffusion Model for Adversarial Purification
    Jinyi Wang, Zhaoyang Lyu, Dahua Lin, Bo Dai, Hongfei Fu
    ICML 2022. Paper   Github  
    2022-05-30
    2022-05-30
  43. Diffusion Models for Adversarial Purification
    Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar
    ICML 2022. Paper   Project   Github  
    2022-05-16
    2022-05-16
  44. TFDPM: Attack detection for cyber-physical systems with diffusion probabilistic models
    Tijin Yan, Tong Zhou, Yufeng Zhan, Yuanqing Xia
    Elsveier Knowledge-Based Systems 2021. Paper  
    2021-12-20
    2021-12-20
  45. Adversarial purification with Score-based generative models
    Jongmin Yoon, Sung Ju Hwang, Juho Lee
    ICML 2021. Paper   Github  
    2021-06-11
    2021-06-11
Counts - 45   Back to top