App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 5

HEAFed: homomorphic encryption-based communication-efficient asynchronous federated learning algorithm

Wang Bin1,2,3,4
Zheng Bing1,2,3
Chen Yun1,2,3
1. School of Information and Electronic Technology, Jiamusi University, Jiamusi Heilongjiang 154007, China
2. Heilongjiang Province Key Laboratory of Autonomous Intelligence and Information Processing, School of Information and Electronic Technology, Jiamusi University, Jiamusi Heilongjiang 154007, China
3. Jiamusi Key Laboratory of Satellite Navigation Technology and Equipment Engineering Technology, Jiamusi Heilongjiang 154007, China
4. Science and Technology Office, Jiamusi University, Jiamusi Heilongjiang 154007, China
DOI: 10.19734/j.issn.1001-3695.2025.08.0375

Abstract

Federated learning systems face risks of privacy data theft by attackers or semi-honest servers, and also suffer from low accuracy and inefficiency in unstable communication environments. To address these issues, this paper proposed an efficient communication asynchronous federated learning algorithm based on homomorphic encryption, named HEAFed. The algorithm first utilized the Chinese Remainder Theorem (CRT) to compress client parameter updates. It then employed an improved Paillier algorithm to encrypt the optimized parameter updates, ensuring user privacy security. Furthermore, it introduced an asynchronous aggregation mechanism with parameter adjustment, effectively incorporating the training outcomes of delayed clients. Experiments were conducted on the MNIST and CIFAR-10 datasets. Results show that HEAFed outperforms traditional privacy-preserving federated learning methods in both accuracy and efficiency. It performs especially well in unstable communication environments. Compared with four baseline algorithms, HEAFed improves accuracy by 12.59% to 43.09%.

Foundation Support

黑龙江省高等学校基本科研业务费优秀创新团队建设项目(2023-KYYWF-0639)
佳木斯大学博士专项科研基金启动项目(JMSUBZ2022-12)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.08.0375
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 5

Publish History

[2026-01-13] Accepted Paper

Cite This Article

王斌, 郑兵, 陈运. HEAFed：同态加密的高效通信异步联邦学习算法 [J]. 计算机应用研究, 2026, 43 (5). (2026-01-20). https://doi.org/10.19734/j.issn.1001-3695.2025.08.0375. (Wang Bin, Zheng Bing, Chen Yun. HEAFed: homomorphic encryption-based communication-efficient asynchronous federated learning algorithm [J]. Application Research of Computers, 2026, 43 (5). (2026-01-20). https://doi.org/10.19734/j.issn.1001-3695.2025.08.0375. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)