Privacy

Follow this field Ask about this field

Recent momentum

emerging

0 papers in the last 28 days · 0.0% of indexed attention

Twelve weeks of publication activity for this topic as it is defined today.

Weekly history

Recent digests

What was published in this field, kept on the site without email delivery.

Period ending 2026-09-21

17 new papers

A weekly snapshot of new work published in Privacy.

Period ending 2026-09-14

15 new papers

A weekly snapshot of new work published in Privacy.

Period ending 2026-09-07

20 new papers

A weekly snapshot of new work published in Privacy.

Inside this field

Focused directions

Focused topic

AI Privacy Risks and Protection

Within Privacy

230 papersExplore

Focused topic

Differential Privacy

Within Privacy

171 papersExplore

Focused topic

Privacy-Preserving Framework

Within Privacy

139 papersExplore

Focused topic

Homomorphic Encryption

Within Privacy

50 papersExplore

Focused topic

Efficient Privacy Loss

Within Privacy

31 papersExplore

Focused topic

Privacy-Utility Trade-Offs

Within Privacy

29 papersExplore

Focused topic

Diffie-Hellman

Within Privacy

24 papersExplore

559 papers

Latest in Privacy

Browse all topics →

On Privacy Leakage in Tabular Diffusion Models: Influential Factors, Attacker Knowledge, and Metrics
May 7, 2026Masoumeh Shafieinejad, D. B. Emerson, Behnoosh Zamanlooy +5Efficient Privacy Loss Synthetic Tabular Data
FedAttr: Towards Privacy-preserving Client-Level Attribution in Federated LLM Fine-tuning
May 7, 2026Su Zhang, Junfeng Guo, Heng HuangFederated Learning Privacy-Preserving Framework
Trade-off Functions for DP-SGD with Subsampling based on Random Shuffling: Tight Upper and Lower Bounds
May 7, 2026Marten van Dijk, Murat Bilgehan ErtanDifferential Privacy Stochastic Gradient Descent
CRISP: Compositional Relations as Invariant Structural Priors for Domain Generalization
May 7, 2026Dat Nguyen, Duc-Duy NguyenMultimodal Domain Generalization Domain Generalization
Quadratic Objective Perturbation: Curvature-Based Differential Privacy
May 7, 2026Daniel Cortild, Coralia CartisDifferential Privacy Empirical Risk Minimization
Enabling Federated Inference via Unsupervised Consensus Embedding
May 7, 2026Yui Hashimoto, Takayuki Nishio, Yuichi Kitagawa +1Federated Learning Privacy-Preserving Framework
CFE-PPAR: Compression-friendly encryption for privacy-preserving action recognition leveraging video transformers
May 7, 2026Haiwei Lin, Shoko Imaizumi, Hitoshi KiyaNeural Video Codecs Open-Vocabulary Action Recognition
Privacy Without Losing Place: A Paradigm for Private Retrieval in Spatial RAGs
May 6, 2026Kennedy Edemacu, Mohammad Mahdi Shokri, Vinay M. Shashidhar +1AI Privacy Risks and Protection Retrieval Task
How Far Are VLMs from Privacy Awareness in the Physical World? An Empirical Study
May 6, 2026Junran Wang, Xinjie Shen, Zehao Jin +1Real-World Environments AI Privacy Risks and Protection
Position: Embodied AI Requires a Privacy-Utility Trade-off
May 6, 2026Xiaoliang Fan, Jiarui Chen, Zhuodong Liu +6Privacy-Utility Trade-Offs AI Privacy Risks and Protection
Breaking the Quality-Privacy Tradeoff in Tabular Data Generation via In-Context Learning
May 6, 2026Xinyan Han, Yan Lu, Xiaoyu Lin +5Synthetic Tabular Data Synthetic Data
Knowledge-Free Correlated Agreement for Incentivizing Federated Learning
May 6, 2026Leon Witt, Togrul Abbasli, Kentaroh Toyoda +2Federated Learning Fairness-Aware Learning
Differential Privacy in the Extensive-Form Bandit Problem
May 6, 2026Stephen Pasteris, Rahul Savani, Theodore TurocyDifferential Privacy Imperfect-Information Games
FL-Sailer: Efficient and Privacy-Preserving Federated Learning for Scalable Single-Cell Epigenetic Data Analysis via Adaptive Sampling
May 6, 2026Guangyi Zhang, Yi Dai, Yiyun He +1Federated Learning Single-Cell Rna Sequencing
FairHealth: An Open-Source Python Library for Trustworthy Healthcare AI in Low-Resource Settings
May 5, 2026Farjana YesminHealthcare Privacy-Preserving Framework
Integrating Feature Correlation in Differential Privacy with Applications in DP-ERM
May 5, 2026Tianyu Wang, Luhao Zhang, Rachel CummingsDifferential Privacy AI Privacy Risks and Protection
FIBER: A Differentially Private Optimizer with Filter-Aware Innovation Bias Correction
May 5, 2026Duc Dm, Thao Do, Minh Son Hoang +3Differential Privacy Optimizer Design
Graph Reconstruction from Differentially Private GNN Explanations
May 5, 2026Rishi Raj Sahoo, Jyotirmaya Shivottam, Subhankar MishraDifferential Privacy Graph Neural Networks
Stable Multimodal Graph Unlearning via Feature-Dimension Aware Quantile Selection
May 5, 2026Jingjing Zhou, Yongshuai Yang, Qing Qing +5Federated Graph Learning Graph Foundation Model
parHSOM: A novel parallel Hierarchical Self-Organizing Map implementation
May 4, 2026Rebekah Lane, Logan Cummins, Andy Perkins +3Intrusion Detection Homomorphic Encryption
MuCALD-SplitFed: Causal-Latent Diffusion for Privacy-Preserving Multi-Task Split-Federated Medical Image Segmentation
May 4, 2026Chamani Shiranthika, Hadi Hadizadeh, Parvaneh SaeediFederated Learning Medical Image Segmentation
Private Speech Classification without Collapse: Stabilized DP Training and Offline Distillation
May 4, 2026Yadi Wen, Tianxin Li, Enji Liang +2Speaker Recognition Efficient Privacy Loss
Privacy Preserving Machine Learning Workflow: from Anonymization to Personalized Differential Privacy Budgets in Federated Learning
May 4, 2026Judith Sáinz-Pardo Díaz, Álvaro López GarcíaFederated Learning Differential Privacy
Graph Federated Unlearning for Privacy Preservation
May 4, 2026Ruotong Ma, Wentao Yu, Qizhou Wang +2Federated Graph Learning Federated Learning
On the Privacy of LLMs: An Ablation Study
May 4, 2026Karima Makhlouf, Lamiaa Basyoni, Syed Khaderi +4Membership Inference Attacks Language Model Evasion Attacks
Misclassification Rate and Privacy-Utility Trade-offs in Graph Convolutional Networks via Subsampling Stability
May 3, 2026Yexin Zhang, Zhongtian Ma, Qiaosheng Zhang +1Differential Privacy Privacy-Utility Trade-Offs
Federated Semi-Supervised Graph Neural Networks with Prototype-Guided Pseudo-Labeling for Privacy-Preserving Gestational Diabetes Mellitus Prediction
May 3, 2026G. Victor Daniela, A. Mallikarjuna Reddya, Uday Kumar Addankia +2Federated Graph Learning Gnn-Based Detectors
Class-Aware Adaptive Differential Privacy in Deep Learning for Sensor-Based Fall Detection
May 3, 2026Joydeb Kumar SanaRobust Fall Detection Differential Privacy
Stabilizing Private LASSO under Heterogeneous Covariates via Anisotropic Objective Perturbation
May 2, 2026Haruka Tanzawa, Ayaka SakataDifferential Privacy Lasso
A Target-Free Harmonization Method for MRI
May 2, 2026Minjun Kim, Dong Ju Mun, Hwihun Jeong +4Magnetic Resonance Imaging Reconstruction Magnetic Resonance Imaging
Metric-Normalized Posterior Leakage (mPL): Attacker-Aligned Privacy for Joint Consumption
May 1, 2026Gaoyi Chen, Minghao Li, Weishi Shi +4Differential Privacy AI Privacy Risks and Protection
A Systematic Exploration of Text Decomposition and Budget Distribution in Differentially Private Text Obfuscation
May 1, 2026Stephen Meisenbacher, Angelo Kleinert, Florian MatthesDifferential Privacy Obfuscation
When RAG Chatbots Expose Their Backend: An Anonymized Case Study of Privacy and Security Risks in Patient-Facing Medical AI
May 1, 2026Alfredo Madrid-García, Miguel RujasChatbots AI Privacy Risks and Protection
FedKPer: Tackling Generalization and Personalization in Medical Federated Learning via Knowledge Personalization
May 1, 2026Zoe Fowler, Ghassan AlRegibFederated Learning Fedavg
Unlearning Offline Stochastic Multi-Armed Bandits
May 1, 2026Zichun Ye, Runqi Wang, Xuchuang Wang +3Unlearning Aims Multi-Armed Bandits
Shuffling-Aware Optimization for Private Vector Mean Estimation
Apr 30, 2026Shun Takagi, Seng Pei LiewDifferential Privacy Single-Message Shuffle Model
DeRelayL: Sustainable Decentralized Relay Learning
Apr 30, 2026Haihan Duan, Tengfei Ma, Yuyang Qin +4Decentralization Privacy-Preserving Framework
Taming Noise-Induced Prototype Degradation for Privacy-Preserving Personalized Federated Fine-Tuning
Apr 30, 2026Yuhua Wang, Qinnan Zhang, Xiaodong Li +6Federated Learning Differential Privacy
Privacy-Preserving Federated Learning via Differential Privacy and Homomorphic Encryption for Cardiovascular Disease Risk Modeling
Apr 30, 2026Gaurang Sharma, Juha Pajula, Aada Illikainen +4Federated Learning Homomorphic Encryption
APPSI-139: A Parallel Corpus of English Application Privacy Policy Summarization and Interpretation
Apr 30, 2026Pengyun Zhu, Qiheng Sun, Long Wen +7Summarization Text Corpora
Asynchronous Federated Unlearning with Invariance Calibration for Medical Imaging
Apr 29, 2026Zhaoyuan Cai, Xinglin ZhangUnsupervised Privacy-Preserving Framework
Differentially-Private Text Rewriting reshapes Linguistic Style
Apr 29, 2026Stefan ArnoldDifferential Privacy Stylistic Fidelity
Fidelity, Diversity, and Privacy: A Multi-Dimensional LLM Evaluation for Clinical Data Augmentation
Apr 29, 2026Guillermo Iglesias, Gema Bello-Orgaz, María Navas-Loro +3Synthetic Data Mental Health
Near-Optimal Cryptographic Hardness of Learning With Homogeneous Halfspaces Under Gaussian Marginals
Apr 29, 2026Jizhou Huang, Brendan JubaOptimal Sample Complexity Homomorphic Encryption
Meta-Learning and Targeted Differential Privacy to Improve the Accuracy-Privacy Trade-off in Recommendations
Apr 29, 2026Peter Müllner, Dominik Kowald, Markus Schedl +1Differential Privacy Efficient Privacy Loss
Privacy-Preserving Federated Learning Framework for Distributed Chemical Process Optimization
Apr 28, 2026Teetat Pipattaratonchai, Aueaphum AueawatthanaphisutChemical Process Systems Federated Learning
A Survey on Split Learning for LLM Fine-Tuning: Models, Systems, and Privacy Optimizations
Apr 27, 2026Zihan Liu, Yizhen Wang, Rui Wang +2Large Language Model Fine-Tuning Privacy-Preserving Framework
Do Protective Perturbations Really Protect Portrait Privacy under Real-world Image Transformations?
Apr 26, 2026Ruiqing Sun, Xingshan Yao, Zhijing Wu +6Visual Degradation Portraits
Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning with Adaptive Quantization and Differential Privacy
Apr 25, 2026Emre Ardıç, Yakup GençFederated Learning Differential Privacy
Training Machine Learning Models on Encrypted Data: A Privacy-Preserving Framework using Homomorphic Encryption
Apr 25, 2026Alexandre Marques, Beatriz Sá, Rui Botelho +1Homomorphic Encryption Privacy-Preserving Framework
Tessera: Secure, Near-Line-Rate Weight Streaming for UMA Edge Accelerators
Apr 25, 2026Animan NaskarSparse Deep Neural Network Accelerators Homomorphic Encryption
PrivSTRUCT: Untangling Data Purpose Compliance of Privacy Policies in Google Play Store
Apr 24, 2026Bhanuka Silva, Anirban Mahanti, Aruna Seneviratne +1AI Privacy Risks and Protection Transparency
PrivUn: Unveiling Latent Ripple Effects and Shallow Forgetting in Privacy Unlearning
Apr 23, 2026Xiaoyi Chen, Haoyuan Wang, Siyuan Tang +4Exact Unlearning Efficient Privacy Loss
Differentially Private De-identification of Dutch Clinical Notes: A Comparative Evaluation
Apr 23, 2026Michele Miranda, Xinlan Yan, Nishant Mishra +4Anonymization Differential Privacy
Synthetic Data in Education: Empirical Insights from Traditional Resampling and Deep Generative Models
Apr 22, 2026Tapiwa Amion Chinodakufa, Ashfaq Ali Shafin, Khandaker Mamun AhmedSynthetic Data Privacy-Preserving Framework
Differentially Private Model Merging
Apr 22, 2026Qichuan Yin, Manzil Zaheer, Tian LiDifferential Privacy Continual Model Merging
Differentially Private Clustered Federated Learning with Privacy-Preserving Initialization and Normality-Driven Aggregation
Apr 22, 2026Jie Xu, Haaris Mehmood, Rogier Van Dalen +2Federated Learning Differential Privacy
Reinforcing privacy reasoning in LLMs via normative simulacra from fiction
Apr 21, 2026Matt Franchi, Madiha Zahrah Choksi, Harold Triedman +1Social Norms Fiction
Behavioral Transfer in AI Agents: Evidence and Privacy Implications
Apr 21, 2026Shilei Luo, Zhiqi Zhang, Hengchen Dai +1Artificial Intelligence Agents Social Dynamics
An AI Agent Execution Environment to Safeguard User Data
Apr 21, 2026Robert Stanley, Avi Verma, Lillian Tsai +2AI Privacy Risks and Protection Artificial Intelligence Agents

May 7, 2026 · cs.LGJ/K move · Enter open · S save

On Privacy Leakage in Tabular Diffusion Models: Influential Factors, Attacker Knowledge, and Metrics

Masoumeh Shafieinejad, D. B. Emerson, Behnoosh Zamanlooy, Elaheh Bassak+4

Vector Institute · McMaster University · University of Toronto · University of Waterloo

Tabular data plays an important role in many fields and industries, including those with elevated privacy considerations and risks. As such, there is a rising interest in generating high-quality synthetic proxies for real tabular data as a means of reducing privacy risk and proprietary data exposure. With tabular diffusion models (TDMs) demonstrating leading performance in synthesizing such data, understanding and measuring the privacy risks associated with these models is imperative. Leveraging state-of-the-art membership inference attacks for TDMs in both black- and white-box settings, this work quantifies the impact of training setup, synthesis choices, and attacker knowledge on privacy leakage. Moreover, the results demonstrate that adversaries need not have perfect knowledge of the training setup, identical data distributions, or massive compute resources to construct successful attacks. Finally, the pitfalls associated with applying heuristic privacy metrics, such as distance-to-closest record, are revealed.

Efficient Privacy Loss Synthetic Tabular Data Membership Inference Attacks

Open paper Ask about it PDF