Secure and Privacy-Preserving Federated Learning for Next-Generation Underground Mine Safety
Authors: Mohamed Elmahallawy, Sanjay Madria, Samuel Frimpong | Published: 2025-12-09
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PrivTune: Efficient and Privacy-Preserving Fine-Tuning of Large Language Models via Device-Cloud Collaboration
Authors: Yi Liu, Weixiang Han, Chengjun Cai, Xingliang Yuan, Cong Wang | Published: 2025-12-09
Whistledown: Combining User-Level Privacy with Conversational Coherence in LLMs
Authors: Chelsea McMurray, Hayder Tirmazi | Published: 2025-11-17
Tuning without Peeking: Provable Privacy and Generalization Bounds for LLM Post-Training
Authors: Ismail Labiad, Mathurin Videau, Matthieu Kowalski, Marc Schoenauer, Alessandro Leite, Julia Kempe, Olivier Teytaud | Published: 2025-07-02
A Privacy-Preserving Indoor Localization System based on Hierarchical Federated Learning
Authors: Masood Jan, Wafa Njima, Xun Zhang | Published: 2025-07-02
Multi-Dimensional Randomized Response
Authors: Josep Domingo-Ferrer, Jordi Soria-Comas | Published: 2020-10-21 | Updated: 2020-12-19
Privacy for All: Demystify Vulnerability Disparity of Differential Privacy against Membership Inference Attack
Authors: Bo Zhang, Ruotong Yu, Haipei Sun, Yanying Li, Jun Xu, Hui Wang | Published: 2020-01-24
Federated Learning with Autotuned Communication-Efficient Secure Aggregation
Authors: Keith Bonawitz, Fariborz Salehi, Jakub Konečný, Brendan McMahan, Marco Gruteser | Published: 2019-11-30
Secure Federated Submodel Learning
Authors: Chaoyue Niu, Fan Wu, Shaojie Tang, Lifeng Hua, Rongfei Jia, Chengfei Lv, Zhihua Wu, Guihai Chen | Published: 2019-11-06 | Updated: 2019-11-11
Privacy for Free: Communication-Efficient Learning with Differential Privacy Using Sketches
Authors: Tian Li, Zaoxing Liu, Vyas Sekar, Virginia Smith | Published: 2019-11-03 | Updated: 2019-12-06