支持K-近邻搜索的区块链泛用型数据隐私保护方法  

Blockchain Universal Data Privacy Protection Method Supporting K-Nearest Neighbor Search

作　　者：王胜 潘正高[1] 董全德[1] WANG Sheng;PAN Zheng-gao;DONG Quan-de(School of Information Engineering,Suzhou University,Suzhou 234000,China)

机构地区：[1]宿州学院信息工程学院,安徽宿州234000

出　　处：《辽宁大学学报（自然科学版）》2024年第2期147-157,共11页Journal of Liaoning University：Natural Sciences Edition

基　　金：安徽省教育厅软件工程专业卓越工程师培养创新项目(2020zyrc163);宿州学院科研平台开放课题(2020ykf02);安徽省重点研究与技术开发计划项目(202004a06020045)。

摘　　要：随着区块链泛用型数据应用场景的不断扩大,其涉及的数据隐私越来越多,数据隐私泄露可能导致个人信用受损,带来财产损失甚至身份盗用等.合理高效地进行用户身份信息及数据隐私保护是确保区块链泛用型数据安全的关键问题.为此,本文提出了支持K-近邻搜索的区块链泛用型数据隐私保护方法,采集区块链泛用型数据,利用k-prototypes算法,聚类区块链泛用型数据,并控制分类属性和数值属性.在此基础上,本文支持K-近邻搜索,建立区块链泛用型数据系统模型,确定区块链泛用型数据敏感区域,实现区块链泛用型数据隐私保护.实验结果表明,本文所提方法具有较好的区块链泛用型数据隐私保护效果,能够有效提高区块链泛用型数据隐私保护安全性,缩短区块链泛用型数据隐私保护时间.With the continuous expansion of blockchain universal data application scenarios,it involves more and more data privacy.Data privacy leakage may lead to personal credit damage,property losses,and even identity theft.Reasonable and efficient protection of user identity information and data privacy is a key issue in ensuring the security of blockchain universal data.To this end,a blockchain universal data privacy protection method that supports K-nearest neighbor search has been proposed.Collect blockchain universal data,use k-prototypes algorithm to cluster blockchain universal data,and control classification and numerical attributes.On this basis,this article supports K-nearest neighbor search,establishes a blockchain universal data system model,identifies sensitive areas of blockchain universal data,and achieves blockchain universal data privacy protection.The experimental results show that the proposed method has a good effect on blockchain universal data privacy protection,can effectively improve the security of blockchain universal data privacy protection,and shorten the time for blockchain universal data privacy protection.

关 键 词：K-近邻搜索 区块链 泛用型数据 k-prototypes算法 数据隐私保护 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]