• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学 ›› 2024, Vol. 46 ›› Issue (06): 1032-1040.

• 计算机网络与信息安全 • 上一篇    下一篇

区块链环境中的隐私保护推荐算法研究

赵文韬,官礼和,何建国,唐昊   

  1. (重庆交通大学数学与统计学院,重庆 400074)

  • 收稿日期:2023-05-17 修回日期:2023-08-23 接受日期:2024-06-25 出版日期:2024-06-25 发布日期:2024-06-17
  • 基金资助:
    国家自然科学基金(12271067);重庆市高校创新研究群体项目(CXQT21021);重庆市研究生联合培养基地建设项目(JDLHPYJD2021016)

A privacy protection recommendation algorithm in block chain environment

ZHAO Wen-tao,GUAN Li-he,HE Jian-guo,TANG Hao   

  1. (School of Mathematics and Statistics,Chongqing Jiaotong University,Chongqing 400074,China)
  • Received:2023-05-17 Revised:2023-08-23 Accepted:2024-06-25 Online:2024-06-25 Published:2024-06-17

摘要: 针对区块链环境中推荐算法难以抵御恶意攻击和推荐效果不佳的问题,一方面,提出了基于整数向量的快速同态加密算法,对用户数据进行隐私保护,其安全性由LWE问题保证;另一方面,基于E2LSH设计了一种高效的个性化推荐算法,该算法根据哈希桶编号进行密钥分发,从而使得同一哈希桶中的用户能进行同态加密运算并快速计算相似度。在区块链+IPFS的基础系统模型上,使用公用数据集与最新相关的隐私保护推荐算法进行了对比实验,实验结果表明,所提算法在安全性和隐私性得到保障的同时拥有理想的推荐效果和速度。

关键词: 区块链, 隐私保护, 局部敏感哈希, 同态加密

Abstract: For the problem that recommendation algorithms in the blockchain environment are difficult to resist malicious attacks and have poor recommendation results. On the one hand, a fast homomorphic encryption algorithm based on integer vector is proposed to protect the privacy protection of user data, and its security is guaranteed by the LWE problem. On the other hand, an efficient recommendation algorithm is designed based on E2LSH, which distributes the key according to the hash bucket number, so that users under the same hash bucket can perform homomorphic encryption operations and quickly calculate the similarity. On the basic system model of blockchain+IPFS, a comparison experiment with the latest relevant privacy-preserving recommendation algorithms is conducted using public datasets. The results show that the algorithms in this paper have an ideal recommendation effect and speed while security and privacy are guaranteed.


Key words: blockchain, privacy protection, locality sensitive hashing, homomorphic encryption