Differentially private sliced inverse regression in the federated paradigm
Authors: Shuaida He, Jiarui Zhang, Xin Chen | Published: 2023-06-10 | Updated: 2023-08-10
連合学習
FheFL: Fully Homomorphic Encryption Friendly Privacy-Preserving Federated Learning with Byzantine Users
Authors: Yogachandran Rahulamathavan, Charuka Herath, Xiaolan Liu, Sangarapillai Lambotharan, Carsten Maple | Published: 2023-06-08 | Updated: 2024-10-06
Rethinking the Defense Against Free-rider Attack From the Perspective of Model Weight Evolving Frequency
Authors: Jinyin Chen, Mingjun Li, Tao Liu, Haibin Zheng, Yao Cheng, Changting Lin | Published: 2022-06-11
Deep Leakage from Model in Federated Learning
Authors: Zihao Zhao, Mengen Luo, Wenbo Ding | Published: 2022-06-10
Leveraging Centric Data Federated Learning Using Blockchain For Integrity Assurance
Authors: Riadh Ben Chaabene, Darine Amayed, Mohamed Cheriet | Published: 2022-06-09
Analytical Composition of Differential Privacy via the Edgeworth Accountant
Authors: Hua Wang, Sheng Gao, Huanyu Zhang, Milan Shen, Weijie J. Su | Published: 2022-06-09
Dap-FL: Federated Learning flourishes by adaptive tuning and secure aggregation
Authors: Qian Chen, Zilong Wang, Jiawei Chen, Haonan Yan, Xiaodong Lin | Published: 2022-06-08
Rate Distortion Tradeoff in Private Read Update Write in Federated Submodel Learning
Authors: Sajani Vithana, Sennur Ulukus | Published: 2022-06-07
Group privacy for personalized federated learning
Authors: Filippo Galli, Sayan Biswas, Kangsoo Jung, Tommaso Cucinotta, Catuscia Palamidessi | Published: 2022-06-07 | Updated: 2022-09-04
Subject Membership Inference Attacks in Federated Learning
Authors: Anshuman Suri, Pallika Kanani, Virendra J. Marathe, Daniel W. Peterson | Published: 2022-06-07 | Updated: 2023-06-02