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

45 papers, page 1 of 1

1. NeurIPS 2025A Reliable Cryptographic Framework for Empirical Machine Unlearning Evaluation
2. NeurIPS 2025A Set of Generalized Components to Achieve Effective Poison-only Clean-label Backdoor Attacks with Collaborative Sample Selection and Triggers
3. NeurIPS 2025Attack by Yourself: Effective and Unnoticeable Multi-Category Graph Backdoor Attacks with Subgraph Triggers Pool
4. NeurIPS 2025Blackbox Model Provenance via Palimpsestic Membership Inference
5. NeurIPS 2025Blameless Users in a Clean Room: Defining Copyright Protection for Generative Models
6. NeurIPS 2025Competitive Advantage Attacks to Decentralized Federated Learning
7. NeurIPS 2025Consensus-Robust Transfer Attacks via Parameter and Representation Perturbations
8. NeurIPS 2025Convex Approximation of Two-Layer ReLU Networks for Hidden State Differential Privacy
9. NeurIPS 2025Deep Learning with Plausible Deniability
10. NeurIPS 2025Distributional Adversarial Attacks and Training in Deep Hedging
11. NeurIPS 2025Dual-Flow: Transferable Multi-Target, Instance-Agnostic Attacks via $\textit{In-the-wild}$ Cascading Flow Optimization
12. NeurIPS 2025Efficient Federated Learning against Byzantine Attacks and Data Heterogeneity via Aggregating Normalized Gradients
13. NeurIPS 2025Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment
14. NeurIPS 2025Exploring the limits of strong membership inference attacks on large language models
15. NeurIPS 2025FracFace: Breaking The Visual Clues—Fractal-Based Privacy-Preserving Face Recognition
16. NeurIPS 2025From Counterfactuals to Trees: Competitive Analysis of Model Extraction Attacks
17. NeurIPS 2025From Dormant to Deleted: Tamper-Resistant Unlearning Through Weight-Space Regularization
18. NeurIPS 2025Harnessing the Universal Geometry of Embeddings
19. NeurIPS 2025LOMIA: Label-Only Membership Inference Attacks against Pre-trained Large Vision-Language Models
20. NeurIPS 2025LoSplit: Loss-Guided Dynamic Split for Training-Time Defense Against Graph Backdoor Attacks
21. NeurIPS 2025More effort is needed to protect pedestrian privacy in the era of AI
22. NeurIPS 2025Nearly-Linear Time Private Hypothesis Selection with the Optimal Approximation Factor
23. NeurIPS 2025On the Robustness of Verbal Confidence of LLMs in Adversarial Attacks
24. NeurIPS 2025Optimal Best Arm Identification under Differential Privacy
25. NeurIPS 2025Optimal Regret of Bandits under Differential Privacy
26. NeurIPS 2025Practical Bayes-Optimal Membership Inference Attacks
27. NeurIPS 2025Private Training Large-scale Models with Efficient DP-SGD
28. NeurIPS 2025Probabilistic Reasoning with LLMs for Privacy Risk Estimation
29. NeurIPS 2025Provable Watermarking for Data Poisoning Attacks
30. NeurIPS 2025Reconstruction and Secrecy under Approximate Distance Queries
31. NeurIPS 2025Rethinking the Role of Verbatim Memorization in LLM Privacy
32. NeurIPS 2025Robust Satisficing Gaussian Process Bandits Under Adversarial Attacks
33. NeurIPS 2025Setting $\varepsilon$ is not the Issue in Differential Privacy
34. NeurIPS 2025SilentStriker: Toward Stealthy Bit-Flip Attacks on Large Language Models
35. NeurIPS 2025Statistical Parity with Exponential Weights
36. NeurIPS 2025Stealthy Yet Effective: Distribution-Preserving Backdoor Attacks on Graph Classification
37. NeurIPS 2025The Cost of Compression: Tight Quadratic Black-Box Attacks on Sketches for $\ell_2$ Norm Estimation
38. NeurIPS 2025Toward Efficient Inference Attacks: Shadow Model Sharing via Mixture-of-Experts
39. NeurIPS 2025Tracing Back the Malicious Clients in Poisoning Attacks to Federated Learning
40. NeurIPS 2025Train to Defend: First Defense Against Cryptanalytic Neural Network Parameter Extraction Attacks
41. NeurIPS 2025TransferBench: Benchmarking Ensemble-based Black-box Transfer Attacks
42. NeurIPS 2025Vanish into Thin Air: Cross-prompt Universal Adversarial Attacks for SAM2
43. NeurIPS 2025Vid-SME: Membership Inference Attacks against Large Video Understanding Models
44. NeurIPS 2025What Really is a Member? Discrediting Membership Inference via Poisoning
45. NeurIPS 2025⁠When Data Can't Meet: Estimating Correlation Across Privacy Barriers

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.