Differentially Private Federated Learning

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Overview

Differentially private federated learning studies how to train shared models across organizations or devices without exposing sensitive training data, using formal privacy guarantees to limit information revealed by the model or its updates. Common approaches clip and perturb gradients or client updates with calibrated noise, often alongside secure aggregation, privacy accounting, adaptive clipping, client selection, or parameter-efficient tuning such as LoRA. Work spans medical imaging, language models, intrusion detection, and other tasks with non-IID client data, where utility is assessed against privacy budgets and sometimes membership-inference or poisoning attacks. The central tension is that stronger privacy can reduce accuracy—especially for heterogeneous or rare data—while robustness, fairness, communication costs, and the precise scope of each privacy guarantee also need to be addressed together.

Latest papers

CardsList

65 papers5 papers in the last four weeks, down 55% on the four weeks before. 0.0% of all new papers.

  1. Evaluating Federated Vision-Language and Vision-Only Models for Privacy-Aware Breast Cancer Imaging

    Oct 26, 2026Malithi Mithsara Wanniarachchi Kankanamge, Ning Yang, Sree Bash Debnath +2Medical ImagingMammography Image Classification

    School of Computing, Southern Illinois University, 1230 Lincoln Drive, Carbondale, 62901, IL, USA. · Department of Radiation Oncology, Stritch School of Medicine, Loyola University, 1032 W. Sheridan Rd, Chicago, 60660, IL, USA. · Department of Radiology, University of Texas Southwestern Medical Center, Dallas, 75390, TX, USA.

  2. Pricing Cross-Bank Context in Federated Anti-Money Laundering

    Oct 26, 2026Lidia Losavio, Dario Fenoglio, Martin Gjoreski +1Anti-Money Laundering DetectionFederated Graph Learning

    Università della Svizzera italiana (USI), Lugano, Switzerland

  3. Projection-Based Federated Learning on Compact Submanifolds with Geometry-Independent Differential Privacy

    Oct 24, 2026Thibault Pautrel, Florent Bouchard, Guillaume Ginolhac +2Differentially Private Federated LearningFederated Learning

    Université Paris-Saclay, CentraleSupélec, L2S, Gif-sur-Yvette, France · Université Paris-Saclay, CNRS, CentraleSupélec, L2S, Gif-sur-Yvette, France · Université Savoie Mont Blanc, LISTIC, Annecy, France +1

  4. Federated Differentially Private Optimization via Low-Rank Preconditioning

    Oct 22, 2026Antti Koskela, Tejas Kulkarni, Elias RaninenDifferentially Private Federated LearningDifferential Privacy

    Nokia Bell Labs

  5. Privacy-Preserving Personalized Federated Learning (PPP-FL) for Medical Imaging

    Oct 20, 2026Md Morshedul Islam, Hossain Shahriar, Alfredo CuzzocreaFederated LearningTraining Data Reconstruction Attacks

  6. Private and Distributionally Robust Federated Multiclass Classification

    Oct 9, 2026Andrea P. Hernandez, Michael Ibrahim, Nagi GebraeelDifferentially Private Federated LearningMulticlass Classification

    H. Milton Stewart School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta, GA 30332-0205, USA

  7. Federated Bayesian Surveillance of Mechanical Thrombectomy Adverse Events: A Population Risk Layer for Surgical Digital Twins

    Oct 6, 2026Damini RijhwaniHealthcareDifferentially Private Federated Learning

    Automation Core Inc., Cambridge, MA, USA

  8. SPADE-DFL: Communication-Efficient Decentralized Federated Learning via Derivative-Free Linearized ADMM

    Sep 24, 2026Mengli Wei, Mengkai Zhu, Jiawen Chen +2Communication-Efficient Distributed TrainingBlack-Box Optimization

    School of Mathematics, Southeast University, Nanjing 210096, China

  9. Privacy-Aligned Personalized Federated Learning with Compact Adaptation and Variable-Length Gaussian Communication

    Sep 14, 2026Yilin Xu, Chun Hei Michael Shiu, Chih Wei Ling +1Communication-Efficient Distributed TrainingDifferentially Private Federated Learning

    Department of Computer Science, City University of Hong Kong · Department of Electrical and Computer Engineering, University of British Columbia · School of Computer Science and Engineering, Hebrew University of Jerusalem

  10. Privacy-enhanced federated learning via asynchronous aggregation and local differential perturbation

    Sep 14, 2026Zhen Zhong, Shini Yang, Liesheng WeiFederated Learning AggregationAsynchronous Federated Learning

    Georgetown University, Washington, D.C., USA · LinkedIn, CA, USA · Shanghai Ocean University, Shanghai, China

  11. Canaries in the Bank: Auditing User-Level Privacy in Private Evolution

    Sep 11, 2026Sai Aparna Aketi, Enayat Ullah, Shripad GadePrivacy AuditingDifferentially Private Federated Learning

    Meta Platforms, Inc. Menlo Park, USA.

  12. A Differentially Private Federated Proximal Optimization Framework for Customer Churn Prediction in Heterogeneous Federated Telecom Networks

    Sep 11, 2026Joydeb Kumar Sana, Subrata Chakraborty, M M Manjurul IslamDifferentially Private Federated LearningTabular Prediction

    Institute of Information and Communication Technology, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh · School of Science and Technology, Faculty of Science, Agriculture, Business and Law, University of New England, Armidale, NSW, Australia · Intelligent Systems Research Centre, Ulster University, Londonderry BT48 7JL, UK

  13. Component-Aware Differential Privacy for Federated Multilingual Speech-LLMs

    Sep 10, 2026Jordi Luque, Fernando López, Aleix SantPrivacy-Preserving Language ModelsDifferentially Private Federated Learning

    Scientific Research Telef´onica Innovaci´on Digital Barcelona, Spain · Telef´onica Innovaci´on Digital Universidad Aut´onoma de Madrid Madrid, Spain · Scientific Research Telef´onica Innovaci´on Digital Universitat Polit`ecnica de Catalunya Barcelona, Spain

  14. RegionFed: Federated Learning for Personalized Query Understanding in Heterogeneous Retail Environments

    Sep 4, 2026Quoc H. Nguyen, Ali Lafzi, Abhijeet Phatak +4Federated LearningHeterogeneous Federated Learning

    Walmart Global Tech Sunnyvale California, USA

  15. Pushing the (Decision) Boundaries: Dynamically Calibrating Differentially Private Noise to Explainability in Federated Learning

    Sep 3, 2026Michael Khavkin, Kichang Lee, Jaeho Jin +2Differentially Private Federated LearningDifferential Privacy

    School of Industrial & Intelligent Systems Engineering, Tel Aviv University · School of Integrated Technology, Yonsei University

  16. Privacy, Robustness, and Fairness Trade-offs in Federated Intrusion Detection: Geometric Indistinguishability at the Aggregation Interface

    Sep 3, 2026Adrita Rahman Tory, ABM Shawkat Ali, Md Abu Layek +1Class-Imbalanced LearningFederated Learning Aggregation

    Bangladesh University of Business and Technology (BUBT), Mirpur-2, Dhaka-1216, Bangladesh · Jagannath University, Dhaka, Bangladesh · University of New South Wales (UNSW), ACT 2601, Australia

  17. Differentially private federated learning with Byzantine-robust aggregation: A cross-domain framework for secure model training in banking and healthcare systems

    Sep 2, 2026Srikumar NayakFederated Learning AggregationByzantine-Robust Federated Learning

    Advanced Artificial Intelligence (AI) Engineering and Cybersecurity Threat Research, LTIMindtree Research, New York City, NY, USA

  18. Private Computation Space: Experience with Trusted Multi-Cluster Federated Learning for Agriculture

    Sep 1, 2026Shuangyu Lei, Muhammad Salman Abid, Jacob Belding +17Privacy-Preserving Federated LearningFederated Learning

    Cornell University USA

  19. SecureDrive-FL: Joint Differential Privacy and Gradient-Aware Selective Homomorphic Encryption for Federated Driver Monitoring

    Aug 27, 2026Baran Can Gül, Hanuma Siddhartha Tunuguntla, Anjana Arvind Naik +3Privacy-Preserving Federated LearningDifferentially Private Federated Learning

    Institute of Industrial Automation and Software Engineering, University of Stuttgart, Stuttgart, Germany · EngD Automotive Systems Design, Eindhoven University of Technology (TU/e), Eindhoven, The Netherlands

  20. An Adaptive Gradient Clipping and Noise Injection Mechanism for Differentially Private Federated Learning

    Aug 15, 2026Wenjing Wei, Alla Jammine, Farid Nait-AbdesselamPrivacy-Preserving Federated LearningDifferentially Private Federated Learning

    Universit´e Paris Cit´e

  21. Towards Privacy-Preserving Federated Prompt Tuning under Data Heterogeneity: A Subspace-Decomposed Expert Approach

    Jul 23, 2026Yuhua Wang, Xiaodong Li, Yihao Guo +6VLM AdaptationDifferentially Private Federated Learning

    School of Artificial Intelligence, Beihang University Beijing, China · Center for the Applied Statistics, School of Statistics, Renmin University of China Beijing, China · School of Computer Science & Technology, Beijing Jiaotong University Beijing, China +2

  22. Collaborative Synthetic Data Generation for Knowledge Transfer in Federated Learning

    Jul 8, 2026Maximilian Andreas Hoefler, Karsten Mueller, Wojciech SamekNon-IID Federated LearningFederated Learning

    Fraunhofer Heinrich Hertz Institute · BIFOLD Technical University Berlin

  23. Escaping Iterative Parameter-Space Noise: Differentially Private Learning with a Hypernetwork

    Jun 25, 2026Naoki Nishikawa, Shokichi Takakura, Satoshi HasegawaPrivacy-Preserving MLDifferentially Private Federated Learning

    The University of Tokyo · LY Corporation

  24. Your Privacy My Cloak: Backdoor Attacks on Differentially Private Federated Learning

    Jun 15, 2026Xiaolin Li, Ning Wang, Ninghui Li +1Backdoor Attacks in Federated LearningDifferentially Private Federated Learning

    Purdue University West Lafayette, IN, USA · University of South Florida Tampa, FL, USA

  25. DPDL: Towards Differential Privacy Preservation in Decentralized Stochastic Learning on Non-IID Data

    Jun 3, 2026Yunsheng Yuan, Xue Xiao, Lina Wang +1Decentralized LearningPrivacy-Preserving ML

    School of Computer Science and Technology, Shandong University, Qingdao 266237, China · Inspur Cloud Information Technology Co, Ltd.

  26. IntraShuffler: A Privacy Preserving Framework for Heterogeneous DP Federated Learning

    Jun 1, 2026Farhin Farhad Riya, Olivera Kotevska, Jinyuan Stella SunFederated Learning AggregationPrivacy-Preserving ML

    University of Tennessee, Knoxville, USA · Oak Ridge National Laboratory, USA

  27. Canonicalized Stable-List Replay for Private Federated Continual Learning over Language-Model Embeddings

    May 29, 2026Ibne Farabi Shihab, Abu Sa-Adat Mohamed Moon-Im Al Ahsan, Anuj SharmaFederated Continual LearningReplay-Based Continual Learning

    Department of Computer Science, Iowa State University · Department of Computer Science & Engineering, BRAC University · Department of Civil, Construction & Environmental Engineering, Iowa State University

  28. A Van Trees Lower Bound for Fully Interactive Differentially Private Federated Learning

    May 19, 2026T. Tony Cai, Yicheng LiDifferentially Private Federated LearningDifferential Privacy

    Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA. · KLATASDS-MOE, School of Statistics, East China Normal University, Shanghai, China.

  29. FedMental: Evaluating Federated Learning for Mental Health Detection from Social Media Data

    May 18, 2026Nuredin Ali Abdelkadir, Anjali Ratnam, Zeerak Talat +1Depression DetectionMental Health

    University of Minnesota · University of Edinburgh

  30. Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning

    May 18, 2026Arnab Auddy, Xiangni Peng, Subhadeep PaulFederated Learning AggregationCommunication-Efficient Distributed Training

    Department of Statistics · The Ohio State University