文献类型：期刊文献

英文题名：Big Data Privacy Management: A Vision Paper

作者：Meng, Xiaofeng[1];Zhang, Xiaojian[2]

第一作者：Meng, Xiaofeng

通讯作者：Meng, XF[1]

机构：[1]Renmin Univ China, Informat Sch, Beijing, Peoples R China;[2]Henan Univ Econ & Law, Sch Comp & Informat Engn, Zhengzhou, Peoples R China

第一机构：Renmin Univ China, Informat Sch, Beijing, Peoples R China

通讯机构：[1]corresponding author), Renmin Univ China, Informat Sch, Beijing, Peoples R China.

年份：2020

起止页码：40-45

外文期刊名：2020 SECOND IEEE INTERNATIONAL CONFERENCE ON TRUST, PRIVACY AND SECURITY IN INTELLIGENT SYSTEMS AND APPLICATIONS (TPS-ISA 2020)

收录：EI(收录号：20210609889447);Scopus(收录号：2-s2.0-85100431462);WOS:【CPCI-S(收录号:WOS:000852719900005)】；

基金：This work was supported by National Natural Science Foundation of China (Grant No: 61502146, 91746115, and 91646203).

语种：英文

外文关键词：big data; security and privacy; privacy risk; privacy active management

摘要：The growing trend towards big data and cloud computing provides enormous data-driven applications such as location-based services. However, it also creates many potential risks for some individuals in big data scenarios. These risks are further complicated by the security and privacy constraints on the individuals' data that are inherently sensitive. To handle these risks and challenges, this paper proposes our vision of an active, adaptive, and scalable framework for sharing and processing potentially sensitive data. We identify the main privacy risks and technical challenges and present some preliminary solutions. The key idea of this framework is that it integrates risk active monitoring, risk active assessment, privacy active management, accountable systems, and law and regulation to ensure big data security and privacy in the whole system. We believe that this conceptual framework may provide a helpful and useful foundation for big data privacy management and will open up many existing research challenges.