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大数据隐私动态防护框架

Dynamic Privacy Preserving Framework For Large Data
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摘要 大数据创造经济和社会效益的同时,也为隐私保护以及数据安全带来前所未有的风险。目前,隐私已经成为大数据应用领域亟待突破的难题,本文分析了隐私保护的现状与挑战,提出了一个以数据为核心的、全生命周期的、系统性的隐私动态防护技术框架,以降低大数据应用实践中的泄露风险,探索行之有效的隐私管理解决方案。 Big data bring about not only significant economic and social benefits,but also great risks and challenges on privacy protection.Currently,privacy has been considered as one of the greatest problems related big data. This paper analyzes the challenges, and provides a data-centric, life-cycle, systematic and dynamic privacy protection technology framework, in order to reduce the risk of privacy leakage in the practice of big data applications and explore effective privacy management solutions.
作者 刘孟旭 LIU Meng-xu(The information center of Henan Province,Henan Zhengzhou,450046)
机构地区 河南省信息中心
出处 《软件》 2019年第7期183-184,201,共3页 Software
关键词 大数据 隐私风险 动态隐私防护框架 隐私泄露 Big data Privacy risk Dynamic privacy preserving framework Privacy leakage
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
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