The Big List Of AI Model Inversion Attack And Defense References And Resources

Note that the below are in alphabetical order. Enjoy!

1. A curated list of resources for model inversion attack (MIA) – https://github.com/AndrewZhou924/Awesome-model-inversion-attack
2. A GAN-Based Defense Framework Against Model Inversion Attacks – https://ieeexplore.ieee.org/document/10184476
3. A Methodology for Formalizing Model-Inversion Attacks – https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7536387&casa_token=ClIVAMYo6dcAAAAA:u75HHyFHj5lBRec9h5SqOZyAsL2dICcWIuQPCj6ltk8McREFCaM4ex42mv3S-oNPiGJLDfUqg0qL
4. A Review of Confidentiality Threats Against Embedded Neural Network Models – https://arxiv.org/pdf/2105.01401
5. A Survey of Privacy Attacks in Machine Learning – https://arxiv.org/pdf/2007.07646
6. A Survey on Gradient Inversion: Attacks, Defenses and Future Directions – https://arxiv.org/pdf/2206.07284
7. Algorithms that Remember: Model Inversion Attacks and Data Protection Law – https://arxiv.org/abs/1807.04644
8. An Attack-Based Evaluation Method for Differentially Private Learning Against Model Inversion Attack – https://ieeexplore.ieee.org/document/8822435
9. Are Large Pre-Trained Language Models Leaking Your Personal Information? – https://aclanthology.org/2022.findings-emnlp.148.pdf
10. Attacks against Machine Learning Privacy (Part 1): Model Inversion Attacks with the IBM-ART Framework – https://franziska-boenisch.de/posts/2020/12/model-inversion/
11. Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks – https://arxiv.org/pdf/2310.06549
12. Bilateral Dependency Optimization: Defending Against Model-inversion Attacks – https://arxiv.org/pdf/2206.05483
13. Black-Box Face Recovery from Identity Features – https://arxiv.org/pdf/2007.13635
14. Boosting Model Inversion Attacks with Adversarial Examples – https://arxiv.org/abs/2306.13965
15. Breaching FedMD: Image Recovery via Paired-Logits Inversion Attack – https://arxiv.org/pdf/2304.11436
16. Breaking the Black-Box: Confidence-Guided Model Inversion Attack for Distribution Shift – https://arxiv.org/html/2402.18027v1
17. Broadening Differential Privacy for Deep Learning Against Model Inversion Attacks – https://ieeexplore.ieee.org/document/9378274
18. C2FMI: Corse-to-Fine Black-Box Model Inversion Attack – https://ieeexplore.ieee.org/document/10148574
19. Deep Face Recognizer Privacy Attack: Model Inversion Initialization by a Deep Generative Adversarial Data Space Discriminator – https://ieeexplore.ieee.org/document/9306253
20. Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps – https://arxiv.org/pdf/1312.6034
21. Deep Learning Model Inversion Attacks and Defenses: A Comprehensive Survey – https://arxiv.org/abs/2501.18934
22. Defending Model Inversion and Membership Inference Attacks via Prediction Purification – https://arxiv.org/pdf/2005.03915
23. Evaluating Gradient Inversion Attacks and Defenses in Federated Learning – https://arxiv.org/abs/2112.00059
24. Evaluation Indicator for Model Inversion Attack – https://drive.google.com/file/d/1rl77BGtGHzZ8obWUEOoqunXCjgvpzE8d/view
25. Exploiting Explanations for Model Inversion Attacks – https://openaccess.thecvf.com/content/ICCV2021/papers/Zhao_Exploiting_Explanations_for_Model_Inversion_Attacks_ICCV_2021_paper.pdf
26. Exploring Model Inversion Attacks in the Black-box Setting – https://petsymposium.org/popets/2023/popets-2023-0012.php
27. Exploring Privacy-Preserving Techniques on Synthetic Data as a Defense Against Model Inversion Attacks – https://link.springer.com/chapter/10.1007/978-3-031-49187-0_1
28. Extracting Prompts by Inverting LLM Outputs – https://arxiv.org/pdf/2405.15012
29. Finding MNEMON: Reviving Memories of Node Embeddings – https://arxiv.org/pdf/2204.06963
30. GAMIN: An Adversarial Approach to Black-Box Model Inversion – https://arxiv.org/pdf/1909.11835
31. How Model Inversion Attacks Compromise AI Systems – https://securing.ai/ai-security/model-inversion/
32. Improved Techniques for Model Inversion Attack – https://www.researchgate.net/publication/344552055_Improved_Techniques_for_Model_Inversion_Attack
33. Improving Robustness to Model Inversion Attacks via Mutual Information Regularization – https://arxiv.org/pdf/2009.05241
34. Information Leakage in Embedding Models – https://arxiv.org/pdf/2004.00053
35. Inverting Gradients – How easy is it to break privacy in federated learning? – https://proceedings.neurips.cc/paper/2020/hash/c4ede56bbd98819ae6112b20ac6bf145-Abstract.html
36. Inverting visual representations with convolutional networks – https://arxiv.org/pdf/1506.02753
37. KART: Parameterization of Privacy Leakage Scenarios from Pre-trained Language Models – https://arxiv.org/pdf/2101.00036v1
38. Knowledge-Enriched Distributional Model Inversion Attacks – https://arxiv.org/pdf/2010.04092
39. Label-Only Model Inversion Attacks via Boundary Repulsion – https://arxiv.org/pdf/2203.01925
40. Language Model Inversion – https://arxiv.org/abs/2311.13647
41. Machine Learning Models that Remember Too Much – https://arxiv.org/pdf/1709.07886
42. MIRROR: Model Inversion for Deep Learning Network with High Fidelity – https://www.cs.purdue.edu/homes/an93/static/papers/ndss2022_model_inversion.pdf
43. Model Inversion: The Essential Guide – https://www.nightfall.ai/ai-security-101/model-inversion
44. Model inversion and membership inference: Understanding new AI security risks and mitigating vulnerabilities – https://www.hoganlovells.com/en/publications/model-inversion-and-membership-inference-understanding-new-ai-security-risks-and-mitigating-vulnerabilities
45. Model Inversion Attack by Integration of Deep Generative Models: Privacy-Sensitive Face Generation From a Face Recognition System – https://dl.acm.org/doi/abs/10.1109/TIFS.2022.3140687
46. Model Inversion Attack with Least Information and an In-depth Analysis of its Disparate Vulnerability – https://openreview.net/pdf?id=x42Lo6Mkcrf
47. Model Inversion Attack against a Face Recognition System in a Black-Box Setting – http://www.apsipa.org/proceedings/2021/pdfs/0001800.pdf
48. Model inversion attacks against collaborative inference – https://dl.acm.org/doi/10.1145/3359789.3359824
49. Model Inversion Attacks against Graph Neural Networks – https://arxiv.org/pdf/2209.07807
50. Model Inversion Attacks: A Growing Threat to AI Security – https://www.tillion.ai/blog/model-inversion-attacks-a-growing-threat-to-ai-security
51. Model Inversion Attacks: A Survey of Approaches and Countermeasures – https://arxiv.org/html/2411.10023v1
52. Model Inversion Attacks Against Collaborative Inference – http://palms.ee.princeton.edu/system/files/Model+Inversion+Attack+against+Collaborative+Inference.pdf
53. Model Inversion Attacks And The Board – https://www.linkedin.com/pulse/model-inversion-attacks-board-dr-sunando-roy-rjsof
54. Model Inversion Attacks for Prediction Systems: Without knowledge of Non-Sensitive Attributes – https://ieeexplore.ieee.org/document/8476925
55. Model Inversion Attacks on Homogeneous and Heterogeneous Graph Neural Networks – https://arxiv.org/pdf/2310.09800
56. Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures – https://dl.acm.org/doi/10.1145/2810103.2813677
57. Model Inversion Robustness: Can Transfer Learning Help? – https://openaccess.thecvf.com/content/CVPR2024/papers/Ho_Model_Inversion_Robustness_Can_Transfer_Learning_Help_CVPR_2024_paper.pdf
58. Neural Network Inversion in Adversarial Setting via Background Knowledge Alignment – https://dl.acm.org/doi/abs/10.1145/3319535.3354261?casa_token=J81Ps-ZWXHkAAAAA%3AFYnXo7DQoHpdhqns8x2TclKFeHpAQlXVxMBW2hTrhJ5c20XKdsounqdT1Viw1g6Xsu9FtKj85elxQaA
59. Overlearning Reveals Sensitive Attributes – https://arxiv.org/pdf/1905.11742
60. Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks – https://arxiv.org/pdf/2201.12179
61. Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations – https://proceedings.mlr.press/v162/ghiasi22a/ghiasi22a.pdf
62. Practical Black Box Model Inversion Attacks Against Neural Nets – https://link.springer.com/chapter/10.1007/978-3-030-93733-1_3
63. Practical Defences Against Model Inversion Attacks for Split Neural Networks – https://arxiv.org/pdf/2104.05743
64. PRID: Model Inversion Privacy Attacks in Hyperdimensional Learning Systems – https://dl.acm.org/doi/abs/10.1109/DAC18074.2021.9586217
65. Privacy and Security Issues in Deep Learning: A Survey – https://ieeexplore.ieee.org/abstract/document/9294026
66. Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing – https://www.usenix.org/system/files/conference/usenixsecurity14/sec14-paper-fredrikson-privacy.pdf
67. Privacy Preserving Facial Recognition Against Model Inversion Attacks – https://ieeexplore.ieee.org/document/9322508
68. Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting – https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8429311
69. Privacy Risks of General-Purpose Language Models – https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9152761
70. Privacy Vulnerability of Split Computing to Data-Free Model Inversion Attacks – https://arxiv.org/abs/2107.06304
71. Pseudo Label-Guided Model Inversion Attack via Conditional Generative Adversarial Network – https://arxiv.org/pdf/2302.09814
72. Reconstructing Training Data from Diverse ML Models by Ensemble Inversion – https://arxiv.org/pdf/2111.03702
73. Reducing Risk of Model Inversion Using Privacy-Guided Training – https://arxiv.org/pdf/2006.15877
74. Reinforcement Learning-Based Black-Box Model Inversion Attacks – https://arxiv.org/pdf/2304.04625
75. ResSFL: A Resistance Transfer Framework for Defending Model Inversion Attack in Split Federated Learning – https://openaccess.thecvf.com/content/CVPR2022/html/Li_ResSFL_A_Resistance_Transfer_Framework_for_Defending_Model_Inversion_Attack_CVPR_2022_paper.html
76. Re-thinking Model Inversion Attacks Against Deep Neural Networks – https://arxiv.org/pdf/2304.01669
77. Robust or Private? (Model Inversion Part II) – https://gab41.lab41.org/robust-or-private-model-inversion-part-ii-94d54fd8d4a5
78. Sentence Embedding Leaks More Information than You Expect: Generative Embedding Inversion Attack to Recover the Whole Sentence – https://arxiv.org/pdf/2305.03010
79. SoK: Model Inversion Attack Landscape: Taxonomy, Challenges, and Future Roadmap – https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10221914
80. Sparse Black-Box Inversion Attack with Limited Information – https://ieeexplore.ieee.org/document/10095514
81. Text Embedding Inversion Security for Multilingual Language Models – https://arxiv.org/abs/2401.12192
82. Text Revealer: Private Text Reconstruction via Model Inversion Attacks against Transformers – https://arxiv.org/pdf/2209.10505
83. The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks – https://arxiv.org/abs/1911.07135
84. The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks – https://www.usenix.org/system/files/sec19-carlini.pdf
85. Threats to the Model: Model Inversion – https://www.ituonline.com/comptia-securityx/comptia-securityx-1/threats-to-the-model-model-inversion/
86. Transferable Embedding Inversion Attack: Uncovering Privacy Risks in Text Embeddings without Model Queries – https://aclanthology.org/2024.acl-long.230/
87. Uncovering a model’s secrets (Model Inversion Part I) – https://gab41.lab41.org/uncovering-a-models-secrets-model-inversion-part-i-ce460eab93d6
88. Understanding Deep Image Representations by Inverting Them – https://openaccess.thecvf.com/content_cvpr_2015/papers/Mahendran_Understanding_Deep_Image_2015_CVPR_paper.pdf
89. UnSplit: Data-Oblivious Model Inversion, Model Stealing, and Label Inference Attacks Against Split Learning – https://arxiv.org/pdf/2108.09033
90. Unstoppable Attack: Label-Only Model Inversion via Conditional Diffusion Model – https://arxiv.org/pdf/2307.08424
91. Variational Model Inversion Attacks – https://proceedings.neurips.cc/paper/2021/file/50a074e6a8da4662ae0a29edde722179-Paper.pdf

Thanks for reading!