Privacy Attacks papers, 2023–2026

Key findings

• Privacy Attacks went from 124 papers in 2023 to 219 in 2026, roughly 1.8x in three years.
• ICLR publishes the most Privacy Attacks work: 262 papers from 2023 to 2026, 38% of the four-venue total.
• The fastest-growing overlap is with Alignment and Safety: papers tagged with both rose from 2 in 2023 to 80 in 2026.
• Among the 5 topics under Federated and Privacy, it ranks #1 by 2026 paper count; the fastest grower in the group, Secure Aggregation, is up 1.8x versus 1.8x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Private Empirical Defense Against Privacy Audits
• ICML 2026A Statistical Framework for Analyzing Specification Resistance to Learnware-Inversion Risks
• ICLR 2026(Token-Level) \textbf{InfoRMIA}: Stronger Membership Inference and Privacy Assessment for LLMs
• CVPR 2026Out of Sight Out of Track Adversarial Attacks on Propagation-based
• NeurIPS 2025A Reliable Cryptographic Framework for Empirical Machine Unlearning Evaluation
• ICML 2025A Certified Unlearning Approach without Access to Source Data
• ICLR 2025Adversarial Attacks on Data Attribution
• CVPR 2025Adv-CPG: A Customized Portrait Generation Framework with Facial Adversarial Attacks
• NeurIPS 2024Reproducibility Study on Adversarial Attacks Against Robust Transformer Trackers
• ICML 2024Collective Certified Robustness against Graph Injection Attacks
• ICLR 2024Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks
• CVPR 2024Efficient Privacy-Preserving Visual Localization Using 3D Ray Clouds
• NeurIPS 2023Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information
• ICML 2023Data Poisoning Attacks Against Multimodal Encoders
• ICLR 2023Adversarial Attacks on Adversarial Bandits
• CVPR 2023Can't Steal? Cont-Steal! Contrastive Stealing Attacks Against Image Encoders
• NeurIPS 2026Adaptive Target-Charging with Privacy Filters and Individual Accounting
• ICML 2026How does Bayesian Sampling help Membership Inference Attacks?
• ICLR 2026Beyond Membership: Limitations of Add/Remove Adjacency in Differential Privacy
• CVPR 2026Revisiting Geometric Obfuscation with Dual Convergent Lines for Privacy-Preserving Image

All Privacy Attacks papers

124 papers, page 1 of 3

1. CVPR 2023Can't Steal? Cont-Steal! Contrastive Stealing Attacks Against Image Encoders
2. CVPR 2023CLIP2Protect: Protecting Facial Privacy Using Text-Guided Makeup via Adversarial Latent Search
3. CVPR 2023DartBlur: Privacy Preservation With Detection Artifact Suppression
4. CVPR 2023Defending Against Patch-Based Backdoor Attacks on Self-Supervised Learning
5. CVPR 2023Dynamic Generative Targeted Attacks With Pattern Injection
6. CVPR 2023Efficient Loss Function by Minimizing the Detrimental Effect of Floating-Point Errors on Gradient-Based Attacks
7. CVPR 2023Enhancing the Self-Universality for Transferable Targeted Attacks
8. CVPR 2023Ensemble-Based Blackbox Attacks on Dense Prediction
9. CVPR 2023Learning To Generate Image Embeddings With User-Level Differential Privacy
10. CVPR 2023Make Landscape Flatter in Differentially Private Federated Learning
11. CVPR 2023Minimizing Maximum Model Discrepancy for Transferable Black-Box Targeted Attacks
12. CVPR 2023Paired-Point Lifting for Enhanced Privacy-Preserving Visual Localization
13. CVPR 2023Physical-World Optical Adversarial Attacks on 3D Face Recognition
14. CVPR 2023Privacy-Preserving Adversarial Facial Features
15. CVPR 2023Privacy-Preserving Representations Are Not Enough: Recovering Scene Content From Camera Poses
16. CVPR 2023Progressive Backdoor Erasing via Connecting Backdoor and Adversarial Attacks
17. CVPR 2023Re-Thinking Model Inversion Attacks Against Deep Neural Networks
18. CVPR 2023Reinforcement Learning-Based Black-Box Model Inversion Attacks
19. CVPR 2023Robust Single Image Reflection Removal Against Adversarial Attacks
20. CVPR 2023SegLoc: Learning Segmentation-Based Representations for Privacy-Preserving Visual Localization
21. CVPR 2023Sibling-Attack: Rethinking Transferable Adversarial Attacks Against Face Recognition
22. CVPR 2023The Best Defense Is a Good Offense: Adversarial Augmentation Against Adversarial Attacks
23. CVPR 2023The Resource Problem of Using Linear Layer Leakage Attack in Federated Learning
24. CVPR 2023Towards Benchmarking and Assessing Visual Naturalness of Physical World Adversarial Attacks
25. CVPR 2023TrojDiff: Trojan Attacks on Diffusion Models With Diverse Targets
26. ICLR 2023A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy
27. ICLR 2023Adversarial Attacks on Adversarial Bandits
28. ICLR 2023Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries
29. ICLR 2023CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning
30. ICLR 2023Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models
31. ICLR 2023Differentially Private $L_2$-Heavy Hitters in the Sliding Window Model
32. ICLR 2023Disparate Impact in Differential Privacy from Gradient Misalignment
33. ICLR 2023Distributed Differential Privacy in Multi-Armed Bandits
34. ICLR 2023Easy Differentially Private Linear Regression
35. ICLR 2023Effective passive membership inference attacks in federated learning against overparameterized models
36. ICLR 2023Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
37. ICLR 2023Extracting Robust Models with Uncertain Examples
38. ICLR 2023Few-shot Backdoor Attacks via Neural Tangent Kernels
39. ICLR 2023Incompatibility Clustering as a Defense Against Backdoor Poisoning Attacks
40. ICLR 2023Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning
41. ICLR 2023Individual Privacy Accounting with Gaussian Differential Privacy
42. ICLR 2023Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples
43. ICLR 2023Measuring Forgetting of Memorized Training Examples
44. ICLR 2023MPCFORMER: FAST, PERFORMANT AND PRIVATE TRANSFORMER INFERENCE WITH MPC
45. ICLR 2023Panning for Gold in Federated Learning: Targeted Text Extraction under Arbitrarily Large-Scale Aggregation
46. ICLR 2023Quantifying Memorization Across Neural Language Models
47. ICLR 2023Regression with Label Differential Privacy
48. ICLR 2023Robust Multivariate Time-Series Forecasting: Adversarial Attacks and Defense Mechanisms
49. ICLR 2023Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning
50. ICML 2023Adversarial Parameter Attack on Deep Neural Networks

FAQ

How many Privacy Attacks papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

698 in total: 124 in 2023, 180 in 2024, 175 in 2025, 219 in 2026.

How many Privacy Attacks papers are at NeurIPS 2026?

NeurIPS 2026 has 55 Privacy Attacks papers, versus 45 the year before.

How many Privacy Attacks papers are at ICLR 2026?

ICLR 2026 has 102 Privacy Attacks papers, versus 83 the year before.

How many Privacy Attacks papers are at ICML 2026?

ICML 2026 has 38 Privacy Attacks papers, versus 29 the year before.

How many Privacy Attacks papers are at CVPR 2026?

CVPR 2026 has 24 Privacy Attacks papers, versus 18 the year before.

Which conference publishes the most Privacy Attacks papers?

ICLR, with 262 papers from 2023 to 2026.