Sym-CS-HFL: A secure and efficient solution for privacy-preserving heterogeneous federated learning.
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| Title: | Sym-CS-HFL: A secure and efficient solution for privacy-preserving heterogeneous federated learning. |
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| Authors: | Wang, Jinzhao1, jinzhaowang@stu.usc.edu.cn, Tian, Wenlong1,2, wenlongtian@usc.edu.cn, Tang, Junwei3, jwtang@wtu.edu.cn, Ye, Xuming1, xumingye@stu.usc.edu.cn, Wan, Yaping1, ypwan@aliyun.com, Xu, Zhiyong4, zxu@suffolk.edu, Chen, Lingna1, linda_cjx@163.com |
| Source: | Journal of Information Security & Applications; Nov2025, Vol. 94, pN.PAG-N.PAG, 1p |
| Database: | Applied Science & Technology Source |
| ISSN: | 22142126 |
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| DOI: | 10.1016/j.jisa.2025.104253 |
