计算机应用研究2026，Vol.43Issue(4)：1005-1012,8.DOI:10.19734/j.issn.1001-3695.2025.09.0301
基于区块链和联邦学习的隐私保护去中心化推荐系统
Privacy-preserving decentralized recommendation system based on blockchain and federated learning
摘要
Abstract
With the overload of Internet information,intelligent recommendation systems have emerged and are widely used to recommend products,content,and services to specific users.Yet,these systems require large amounts of user data to train their models.How to ensure the privacy and security of user data while maintaining model performance has become a pressing issue.Traditional recommendation systems suffer from problems such as data sparsity,and sharing raw data directly also can violate user privacy.This paper proposed a privacy-preserving decentralized federated learning recommendation system.It uti-lized the peer-to-peer network and immutable data storage features of blockchain to ensure data security and system decentrali-zation.In this system,user data was decomposed into private parameters(containing privacy information)and public parame-ters(containing item feature information)through matrix factorization.Users trained locally,kept their private parameters,and shared only the public parameters,which protected user privacy.Blockchain was introduced to coordinate the training process,where its leader aggregated local public parameters into a global public parameter.Users then downloaded and syn-chronized these parameters to conduct the next training round.Furthermore,it proposed a high-performance,low-consumption consensus mechanism based on a dynamic random seed algorithm,and the model's privacy-preserving performance was ana-lyzed.Experiments show that this system is superior to traditional centralized learning frameworks in terms of both privacy pro-tection and recommendation accuracy,while also offering strong scalability and practical usability.关键词
去中心化/联邦学习/隐私保护/推荐系统/区块链Key words
decentralization/federated learning/privacy protection/recommendation system/blockchain分类
信息技术与安全科学引用本文复制引用
郭剑岚,陈俞强,卢荣,李光程..基于区块链和联邦学习的隐私保护去中心化推荐系统[J].计算机应用研究,2026,43(4):1005-1012,8.基金项目
广东省自然科学基金资助项目(2020A1515110162) （2020A1515110162）
广东省哲学社会科学规划项目(GD25CSH06) （GD25CSH06）
广东省普通高校创新团队资助项目(2025KCXTD094) （2025KCXTD094）
广东省普通高校特色创新项目(2025KTSCX373) （2025KTSCX373）
2021年东莞市农村振兴战略专项基金资助项目(20211800400102) （20211800400102）
东莞市松山湖科技特派员项目(20234384-01KCJ-G,20234369-01KCJ-G,20234400-01KCJ-G) （20234384-01KCJ-G,20234369-01KCJ-G,20234400-01KCJ-G）
