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

42 papers, page 1 of 1

1. ICML 2024A Theoretical Analysis of Backdoor Poisoning Attacks in Convolutional Neural Networks
2. ICML 2024Adversarial Attacks on Combinatorial Multi-Armed Bandits
3. ICML 2024AegisFL: Efficient and Flexible Privacy-Preserving Byzantine-Robust Cross-silo Federated Learning
4. ICML 2024BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression Tasks
5. ICML 2024Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks
6. ICML 2024Beyond the Calibration Point: Mechanism Comparison in Differential Privacy
7. ICML 2024Collective Certified Robustness against Graph Injection Attacks
8. ICML 2024Data Poisoning Attacks against Conformal Prediction
9. ICML 2024DataFreeShield: Defending Adversarial Attacks without Training Data
10. ICML 2024Exact Soft Analytical Side-Channel Attacks using Tractable Circuits
11. ICML 2024Fast Adversarial Attacks on Language Models In One GPU Minute
12. ICML 2024FedREDefense: Defending against Model Poisoning Attacks for Federated Learning using Model Update Reconstruction Error
13. ICML 2024Improved Bounds for Pure Private Agnostic Learning: Item-Level and User-Level Privacy
14. ICML 2024Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy
15. ICML 2024Low-Cost High-Power Membership Inference Attacks
16. ICML 2024Mean Estimation in the Add-Remove Model of Differential Privacy
17. ICML 2024Membership Inference Attacks on Diffusion Models via Quantile Regression
18. ICML 2024Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss
19. ICML 2024Neural Collapse meets Differential Privacy: Curious behaviors of NoisyGD with Near-Perfect Representation Learning
20. ICML 2024Privacy Attacks in Decentralized Learning
21. ICML 2024Privacy Backdoors: Stealing Data with Corrupted Pretrained Models
22. ICML 2024Privacy Profiles for Private Selection
23. ICML 2024Privacy-Preserving Data Release Leveraging Optimal Transport and Particle Gradient Descent
24. ICML 2024Privacy-Preserving Embedding via Look-up Table Evaluation with Fully Homomorphic Encryption
25. ICML 2024Private Truly-Everlasting Robust-Prediction
26. ICML 2024Provable Privacy with Non-Private Pre-Processing
27. ICML 2024Reducing Item Discrepancy via Differentially Private Robust Embedding Alignment for Privacy-Preserving Cross Domain Recommendation
28. ICML 2024Rényi Pufferfish Privacy: General Additive Noise Mechanisms and Privacy Amplification by Iteration via Shift Reduction Lemmas
29. ICML 2024Rethinking DP-SGD in Discrete Domain: Exploring Logistic Distribution in the Realm of signSGD
30. ICML 2024Revisiting Character-level Adversarial Attacks for Language Models
31. ICML 2024Shifted Interpolation for Differential Privacy
32. ICML 2024SignSGD with Federated Defense: Harnessing Adversarial Attacks through Gradient Sign Decoding
33. ICML 2024Split-and-Denoise: Protect large language model inference with local differential privacy
34. ICML 2024The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks
35. ICML 2024The Privacy Power of Correlated Noise in Decentralized Learning
36. ICML 2024Toward Availability Attacks in 3D Point Clouds
37. ICML 2024Trained Random Forests Completely Reveal your Dataset
38. ICML 2024Transferable Facial Privacy Protection against Blind Face Restoration via Domain-Consistent Adversarial Obfuscation
39. ICML 2024Tuning-free Estimation and Inference of Cumulative Distribution Function under Local Differential Privacy
40. ICML 2024Unveiling Privacy, Memorization, and Input Curvature Links
41. ICML 2024Verifying message-passing neural networks via topology-based bounds tightening
42. ICML 2024Watermark Stealing in Large Language Models

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.