摘要
目前,数据挖掘与知识发现技术日渐成熟,个人对自身隐私的保护意识也逐渐增强。用于数据挖掘的发布数据中往往包含隐私数据,需要在数据发布之前进行数据脱敏处理。在知识发现与信息保护之间,隐私保护数据挖掘技术变得日益重要。隐私保护数据挖掘技术在挖掘出隐藏的、先前未知的、潜在有用的知识时,可以避免敏感数据和信息泄露。文中总结了已有的隐私保护数据发布技术,将分布式随机化与现有算法相结合,降低了信息损失率,增加了数据可用性。
At present,data mining and knowledge discovery technology is becoming more and more mature,and individuals'awareness of privacy protection is also gradually enhanced.Published data used for data mining often contains private data,which requires data desensitization before data publication.Between knowledge discovery and information protection,Privacy-preserving data mining becomes increasingly important.PPDM can avoid sensitive data and information leakage when discovers hidden,previously unknown and potentially useful knowledge is unearthed.This paper summarizes the existing privacy protection data release technologies,and combines distributed randomization with existing algorithms to reduce information loss rate and increase data availability.
作者
何清
HE Qing(People's Hospital of Rizhao,Rizhao,Shandong 276827,China)
出处
《移动信息》
2023年第7期190-192,共3页
MOBILE INFORMATION
关键词
数据挖掘
隐私保护
医疗安全
分布式随机化
Data mining
Privacy protection
Medical safety
Distributed randomization
