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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 11

Privacy-preserving scheme for blockchain-based federated learning using dynamic group signatures

Zhang Menga
Gu Chunshengb
Zhang Yanb
Shi Peizhongb
Jing Zhengjunb
a. School of Mechanical Engineering, b. School of Computer Engineering, Jiangsu University of Technology, Changzhou 213000, China
DOI: 10.19734/j.issn.1001-3695.2025.03.0097

Abstract

Blockchain-based federated learning is a decentralized machine learning approach that enables distributed clients to collaboratively train models. However, existing blockchain-based federated learning systems lacked adequate protection for sensitive attributes such as user identities, making collusion attacks between malicious trainers and validators easy to execute. This paper proposed a blockchain-based federated learning privacy protection scheme (DGS-BCFL) that innovatively integrated dynamic group signatures with blockchain federated learning. The scheme first utilized the anonymity of dynamic group signatures to protect user identity privacy while enabling traceability of malicious users' anonymous identities and revocation of low-contribution malicious participants. Second, it developed a contribution-based adaptive incentive algorithm to ensure fairness by rewarding nodes according to their workload intensity and functional roles. Finally, the performance of DGS-BCFL was evaluated on the FEMNIST dataset. Experimental results showed that when facing collusion attacks from malicious nodes, DGS-BCFL achieved an 89.36% success rate in resisting such attacks, representing a 24.92% improvement over VBFL. The scheme also demonstrated 26.13% higher model accuracy compared to BDFL. Therefore, the proposed scheme not only maintains the high robustness of BCFL but also demonstrates superior performance in model accuracy.

Foundation Support

国家自然科学基金资助项目(61672270,61602216)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.03.0097
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 11

Publish History

[2025-07-07] Accepted Paper

Cite This Article

张蒙, 古春生, 张言, 等. 基于动态群签名的区块链联邦学习隐私保护方案 [J]. 计算机应用研究, 2025, 42 (11). (2025-07-08). https://doi.org/10.19734/j.issn.1001-3695.2025.03.0097. (Zhang Meng, Gu Chunsheng, Zhang Yan, et al. Privacy-preserving scheme for blockchain-based federated learning using dynamic group signatures [J]. Application Research of Computers, 2025, 42 (11). (2025-07-08). https://doi.org/10.19734/j.issn.1001-3695.2025.03.0097. )

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.

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