mlsanityData to 14 Oct 2026

Data Forensics in Diffusion Models: A Systematic Analysis of Membership Privacy

arXiv 2302.07801 ↗First posted 15 Feb 2023cs.LG cs.CRcited by 10

On the map: Diffusion models → Robustness, privacy and adversarial aspects

Abstract (arXiv)

In recent years, diffusion models have achieved tremendous success in the field of image generation, becoming the stateof-the-art technology for AI-based image processing applications. Despite the numerous benefits brought by recent advances in diffusion models, there are also concerns about their potential misuse, specifically in terms of privacy breaches and intellectual property infringement. In particular, some of their unique characteristics open up new attack surfaces when considering the real-world deployment of such models. With a thorough investigation of the attack vectors, we develop a systematic analysis of membership inference attacks on diffusion models and propose novel attack methods tailored to each attack scenario specifically relevant to diffusion models. Our approach exploits easily obtainable quantities and is highly effective, achieving near-perfect attack performance (>0.9 AUCROC) in realistic scenarios. Our extensive experiments demonstrate the effectiveness of our method, highlighting the importance of considering privacy and intellectual property risks when using diffusion models in image generation tasks.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Placed in Robustness, privacy and adversarial aspects, one of 14 directions in Diffusion models. Builds on 31 of its 43 references that are in the map. First posted on arXiv 15 Feb 2023.

Builds on

31 of 43 references.

Closest ancestors · 5

Same direction, newest first

  1. 2023Membership Inference Attacks against Diffusion Models7 Feb
  2. 2023Are Diffusion Models Vulnerable to Membership Inference Attacks?2 Feb
  3. 2023Extracting Training Data from Diffusion Models30 Jan
  4. 2023Membership Inference of Diffusion Models24 Jan
  5. 2022Differentially Private Diffusion Models18 Oct

Other references · 26

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  2. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  4. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  5. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 9,122
  6. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  7. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
  8. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
  9. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
  10. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 6,013
  11. 2022LAION-5B: An open large-scale dataset for training next generation image-text modelscited by 4,152
  12. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,101
14 more
  1. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,761
  2. 2014Deep Learning Face Attributes in the Wildcited by 3,693
  3. 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,988
  4. 2016Deep Learning with Differential Privacycited by 2,728
  5. 2016Membership Inference Attacks against Machine Learning Modelscited by 2,281
  6. 2021Variational Diffusion Modelscited by 1,153
  7. 2020Improved Techniques for Training Score-Based Generative Modelscited by 1,043
  8. 2021Membership Inference Attacks From First Principlescited by 878
  9. 2018ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Modelscited by 498
  10. 2020Systematic Evaluation of Privacy Risks of Machine Learning Modelscited by 292
  11. 2019White-box vs Black-box: Bayes Optimal Strategies for Membership Inferencecited by 271
  12. 2019Reconstruction and Membership Inference Attacks against Generative Modelscited by 122
  13. 2022Membership Inference Attacks Against Text-to-image Generation Modelscited by 69
  14. 2020On the Difficulty of Membership Inference Attackscited by 6

Built on by

Cited by year

Citing papers per year: 2023: 6; 2024: 3; 2025: 1.

10 papers.

  1. 2023DIRE for Diffusion-Generated Image Detectioncited by 390
  2. 2023Detecting Images Generated by Deep Diffusion Models using their Local Intrinsic Dimensionalitycited by 44
  3. 2023Challenges and Remedies to Privacy and Security in AIGC: Exploring the Potential of Privacy Computing, Blockchain, and Beyondcited by 14
  4. 2023The Inadequacy of Similarity-based Privacy Metrics: Privacy Attacks against "Truly Anonymous" Synthetic Datasetscited by 14
  5. 2025The DCR Delusion: Measuring the Privacy Risk of Synthetic Datacited by 11
  6. 2024DP-TLDM: Differentially Private Tabular Latent Diffusion Modelcited by 5
  7. 2024Artifact Feature Purification for Cross-domain Detection of AI-generated Imagescited by 5
  8. 2023PriSampler: Mitigating Property Inference of Diffusion Modelscited by 4
  9. 2024Trinity Detector:text-assisted and attention mechanisms based spectral fusion for diffusion generation image detectioncited by 4
  10. 2023Trustworthy Large Models in Vision: A Surveycited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2023Towards More Realistic Membership Inference Attacks on Large Diffusion Models
  2. 2026Noise as a Probe: Membership Inference Attacks on Diffusion Models Leveraging Initial Noise
  3. 2023Black-box Membership Inference Attacks against Fine-tuned Diffusion Models
  4. 2025Enhancing Membership Inference Attacks on Diffusion Models from a Frequency-Domain Perspective
  5. 2023Privacy Threats in Stable Diffusion Models
  6. 2023Membership Inference Attacks on Diffusion Models via Quantile Regression
  7. 2024Dual-Model Defense: Safeguarding Diffusion Models from Membership Inference Attacks through Disjoint Data Splitting
  8. 2024Towards Black-Box Membership Inference Attack for Diffusion Models