Security & Privacy
1,222 papers (5 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Papers per year
1
2
1
2
1
6
9
6
10
8
12
35
41
55
102
169
174
237
282
69
'10
'15
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'25
Papers (including subtopics)
Fully Decentralized Certified Unlearning
CVPR 2026
Hyperion: Private Token Sampling with Homomorphic Encryption
ACL 2026
Imprecise Probabilities for Privacy–Accuracy Trade-offs in Bayesian Networks
UAI 2026
Improved Regret in Stochastic Decision-Theoretic Online Learning under Differential Privacy
ALT 2026
Improving the Convergence of Private Shuffled Gradient Methods with Public Data
UAI 2026
Invited Open Problem: Does Differential Privacy Make PAC Learning Much Harder?
COLT 2026
JANUS: Cross-World, Cooperative Nested Virtualization for Secure Containers
OSDI 2026
LDP-Slicing: Local Differential Privacy for Images via Randomized Bit-Plane Slicing
CVPR 2026
Minimax density estimation in the adversarial framework under local differential privacy
JMLR 2026
Minimax optimal differentially private synthetic data for smooth queries
COLT 2026
Mitigating Backdoor Attacks via Trigger Reconstruction and Model Hardening
WACV 2026
Nearly Linear-Time User-Level DP-SCO with Optimal Rates
COLT 2026
Nested SEV: Secure and Generic SEV Support for Nested Virtualization
OSDI 2026
On Purely Private Covariance Estimation
ALT 2026
On the Curse of Dimensionality in Private Sparse Covariance Estimation and PCA
COLT 2026
Osprey: Transparent and Efficient Virtual Memory for Secure Computation
OSDI 2026
Overcoming Copyright Barriers in Corpus Distribution Through Non-Reversible Hashing
ACL 2026
Over-Threshold Multiparty Private Set Intersection for Collaborative Network Intrusion Detection
NSDI 2026
PDR: A Plug-and-Play Positional Decay Framework for LLM Pre-training Data Detection
ACL 2026
PECCVAI: Overcoming the Brittleness of AI Image Watermarking Under Visual Paraphrasing Attacks
CVPR 2026
Personalized Federated Training of Diffusion Models with Privacy Guarantees
CVPR 2026
Powerful Training-Free Membership Inference Against Fine-Tuned Autoregressive Language Models
ACL 2026
Privacy Collapse: Benign Fine-Tuning Can Break Contextual Privacy in Language Models
ACL 2026
Privacy-Preserving Robustness Verification for Neural Networks
UAI 2026
Privacy-R1: Privacy-Aware Multi-LLM Agent Collaboration via Reinforcement Learning
ACL 2026