Privacy-Preserving Continual Federated Clustering via Adaptive Resonance Theory

被引：0
|
作者：
Masuyama, Naoki [1 ]
Nojima, Yusuke [1 ]
Toda, Yuichiro [2 ]
Loo, Chu Kiong [3 ]
Ishibuchi, Hisao [4 ]
Kubota, Naoyuki [5 ]
机构：
[1] Osaka Metropolitan University, Graduate School of Informatics, Department of Core Informatics, Sakai, Osaka,599-8531, Japan
[2] Okayama University, Faculty of Environmental, Life, Natural Science and Technology, Okayama,700-8530, Japan
[3] Universiti Malaya, Faculty of Computer Science and Information Technology, Department of Artificial Intelligence, Kuala Lumpur,50603, Malaysia
[4] Southern University of Science and Technology, Department of Computer Science and Engineering, Shenzhen,518055, China
[5] Tokyo Metropolitan University, Graduate School of Systems Design, Department of Mechanical Systems Engineering, Asahigaoka, Hino, Tokyo,191-0065, Japan
来源：
IEEE Access | 2024年 / 12卷
关键词：
Compendex;
D O I：
10.1109/ACCESS.2024.3467114
中图分类号：
学科分类号：
摘要：
Federated learning
引用
收藏
页码：139692 / 139710
相关论文
共 50 条
  • [21] Poster: Towards Privacy-Preserving Federated Recommendation via Synthetic Interactions
    Ariyarathna, Thirasara
    Kanhere, Salil S.
    Paik, Hye-Young
    PROCEEDINGS 45TH IEEE SYMPOSIUM ON SECURITY AND PRIVACY WORKSHOPS, SPW 2024, 2024, : 297 - 297
  • [22] CryptoFE: Practical and Privacy-Preserving Federated Learning via Functional Encryption
    Qian, Xinyuan
    Li, Hongwei
    Hao, Meng
    Yuan, Shuai
    Zhang, Xilin
    Guo, Song
    2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022), 2022, : 2999 - 3004
  • [23] PILE: Robust Privacy-Preserving Federated Learning Via Verifiable Perturbations
    Tang, Xiangyun
    Shen, Meng
    Li, Qi
    Zhu, Liehuang
    Xue, Tengfei
    Qu, Qiang
    IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, 2023, 20 (06) : 5005 - 5023
  • [24] FedMDO: Privacy-preserving Federated Learning via Mixup Differential Objective
    You X.
    Liu C.
    Li J.
    Sun Y.
    Liu X.
    IEEE Transactions on Circuits and Systems for Video Technology, 2024, 34 (10) : 1 - 1
  • [25] Secure and Privacy-Preserving Federated Learning via Co-Utility
    Domingo-Ferrer, Josep
    Blanco-Justicia, Alberto
    Manjon, Jesus
    Sanchez, David
    IEEE INTERNET OF THINGS JOURNAL, 2022, 9 (05): : 3988 - 4000
  • [26] CrowdFA: A Privacy-Preserving Mobile Crowdsensing Paradigm via Federated Analytics
    Zhao, Bowen
    Li, Xiaoguo
    Liu, Ximeng
    Pei, Qingqi
    Li, Yingjiu
    Deng, Robert H.
    IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2023, 18 : 5416 - 5430
  • [27] CROWDFL: Privacy-Preserving Mobile Crowdsensing System Via Federated Learning
    Zhao, Bowen
    Liu, Ximeng
    Chen, Wei-Neng
    Deng, Robert H.
    IEEE TRANSACTIONS ON MOBILE COMPUTING, 2023, 22 (08) : 4607 - 4619
  • [28] A Strong Privacy-Preserving and Efficient Fingerprint Authentication via Clustering
    Liu, Jingwei
    Zhou, Zihan
    Sun, Rong
    Du, Xiaojiang
    Guizani, Mohsen
    IEEE CONFERENCE ON GLOBAL COMMUNICATIONS, GLOBECOM, 2023, : 5889 - 5894
  • [29] Privacy-Preserving and Reliable Decentralized Federated Learning
    Gao, Yuanyuan
    Zhang, Lei
    Wang, Lulu
    Choo, Kim-Kwang Raymond
    Zhang, Rui
    IEEE TRANSACTIONS ON SERVICES COMPUTING, 2023, 16 (04) : 2879 - 2891
  • [30] Privacy-preserving federated learning on lattice quantization
    Zhang, Lingjie
    Zhang, Hai
    INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING, 2023, 21 (06)
12345