基于大数据分析的隐私信息保护系统设计与实现  

Design and Implementation of Privacy Iinformation Protection System Based on Big Data Analysis

作　　者：盛丹丹 Sheng Dandan(Institute of Geology,China Earthquake Administration,Beijing 100029)

机构地区：[1]中国地震局地质研究所,北京100029

出　　处：《信息安全研究》2023年第9期914-920,共7页Journal of Information Security Research

摘　　要：为保证隐私信息的安全性,实现信息的人性化加密,避免发生隐私信息泄露风险,设计基于大数据分析的隐私信息保护系统.云设施层以Kubernetes集群技术为核心,为系统功能提供基础设施保障,在此基础上,大数据处理层通过筛选、去重等操作处理信息后,通过文件传输协议传送信息至信息保护层,该层以TBS架构为基础,引入MapReduce编程模型,并行存储海量信息,同时基于属性分类的隐私信息保护模型,实现隐私信息保护.测试结果显示:该系统能够完成海量信息的并行存储,信息记录链接结果均在0.22以下,隐私信息的泄露风险较低,确保信息呈现时的隐私性;并且KL散度均在0.18以内,隐私保护后信息的可用性良好.In order to ensure the security of private information,realize the humanized encryption of information,and avoid the risk of privacy information leakage,a privacy information protection system based on big data analysis is designed.The cloud infrastructure layer takes Kubernetes cluster technology as the core to provide infrastructure support for system functions.On this basis,the big data processing layer processes information through filtering,de-duplication and other operations,and then transmits information to the information protection layer through file transfer protocol.This layer is based on the TBS architecture,introduces MapReduce programming model,stores massive information in parallel.At the same time,privacy information protection model based on attribute classification is used to realize privacy information protection.The test results show that the system can complete the parallel storage of massive information,the information record link results are below 0.22,and the risk of privacy information disclosure is low,ensuring the privacy of information presentation;Moreover,the KL dispersion is within 0.18,and the information availability is good after privacy protection.

关 键 词：大数据 信息安全 隐私保护系统 Kubernetes集群技术 并行存储 属性分类 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]