App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 10

Committable threshold private set intersection protocol for vertical federated learning

Li Gonglia,b
Li Huihuia
Liu Weichena
Zhang Ena,b
a. School of Computer&Information Engineering(School of Artificial Intelligence), b. Key Laboratory of Artificial Intelligence&Personalized Learning in Education of Henan Province, Henan Normal University, Xinxiang Henan 453007, China
DOI: 10.19734/j.issn.1001-3695.2025.12.0548

Abstract

Vertical federated learning (VFL) involves collaborative training among participants based on intersection samples. To address the problem that small intersection cardinality of participants’ samples leads to unsatisfactory model performance improvement, this paper proposes using the threshold private set intersection (TPSI) protocol to first conduct a threshold test on the intersection cardinality of participants’ sample sets. Only participants with an intersection cardinality exceeding the threshold can initiate VFL training. Existing TPSI suffers from high computational overhead and potential data tampering by senders during execution. To solve these issues, this paper proposes the committable threshold private set intersection (CTPSI) protocol. This protocol performs threshold testing on intersection cardinality under ciphertext, verifies data authenticity based on the Pedersen commitment scheme, obtains the intersection, and achieves resistance against single-sided malicious attacks. Experimental results show that when the set size is 200 and the entry size is 128 B, CTPSI completes execution in 15.61 seconds. Compared with other schemes, the protocol demonstrates significant advantages in computation time.

Foundation Support

国家自然科学基金项目(62372157)
河南省自然科学基金项目(252300421872)
河南省科技攻关计划项目(232102211057)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.12.0548
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 10

Publish History

[2026-07-08] Accepted Paper

Cite This Article

李功丽, 李慧慧, 刘威辰, 等. 面向纵向联邦的可承诺门限隐私集合交集协议 [J]. 计算机应用研究, 2026, 43 (10). (2026-07-30). https://doi.org/10.19734/j.issn.1001-3695.2025.12.0548. (Li Gongli, Li Huihui, Liu Weichen, et al. Committable threshold private set intersection protocol for vertical federated learning [J]. Application Research of Computers, 2026, 43 (10). (2026-07-30). https://doi.org/10.19734/j.issn.1001-3695.2025.12.0548. )

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  • Application Research of Computers Monthly Journal
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    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.

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