计算机科学
差别隐私
隐私软件
互联网隐私
信息隐私
计算机安全
差速器(机械装置)
数据挖掘
工程类
航空航天工程
作者
Ying Zhao,Jia Tina Du,Jinjun Chen
摘要
Differential privacy has been a de facto privacy standard in defining privacy and handling privacy preservation. It has had great success in scenarios of local data privacy and statistical dataset privacy. As a primitive definition, standard differential privacy has been adapted to a wide range of practical scenarios. In this work, we summarize differential privacy adaptations in specific scenarios and analyze the correlations between data characteristics and differential privacy design. We mainly present them in two lines including differential privacy adaptations in local data privacy and differential privacy adaptations in statistical dataset privacy. With a focus on differential privacy design, this survey targets providing guiding rules in differential privacy design for scenarios, together with identifying potential opportunities to adaptively apply differential privacy in more emerging technologies and further improve differential privacy itself with the assistance of cryptographic primitives.
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