大数据背景下隐私保护方法研究.pdf

信息与电脑
算法语言 China Computer&Communication 2018 年第 7 期
大数据背景下隐私保护方法研究
林  青
（西安培华学院，陕西 西安  710125）
摘 要：笔者介绍了隐私保护的几个方面，首先是传统的隐私保护技术，重点介绍了匿名技术。其后介绍了隐私保
护的新兴概念——差分隐私。差分隐私模型是一种被广泛认可的严格的隐私保护模型，它通过向数据集里添加随机噪声，
来影响攻击者窃取数据中的敏感信息，它不依赖攻击者的背景知识，并且可以定量分析隐私泄露的风险。
关键词：隐私保护；匿名技术；差分隐私
中图分类号：    文献标识码：A    文章编号：1003-9767（2018）07-050-03
Research on Privacy Protection Method in Big Data Background
Lin Qing
(Xi'an Peihua University, Xi'an Shaanxi 710125, China)
Abstract:
The author introduces several aspects of privacy protection. The first is the traditional privacy protection technology
and focuses on anonymous technology. It then introduced the emerging concept of privacy protection - differential privacy. The
differential privacy model is a widely accepted and strict privacy protection model. It adds random noise to the data set to influence
the attacker to steal sensitive information in the data. It does not depend on the attacker's background knowledge and can be
quantitatively analyzed. The risk of privacy leaks.
Key words:
privacy pro