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Big privacy: challenges and opportunities of privacy study in the age of big data

机译:大隐私:大数据时代隐私研究的挑战与机遇

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摘要

One of the biggest concerns of big data is privacy. However, the study on big data privacy is still at a very early stage. We believe the forthcoming solutions and theories of big data privacy root from the in place research output of the privacy discipline. Motivated by these factors, we extensively survey the existing research outputs and achievements of the privacy field in both application and theoretical angles, aiming to pave a solid starting ground for interested readers to address the challenges in the big data case. We first present an overview of the battle ground by defining the roles and operations of privacy systems. Second, we review the milestones of the current two major research categories of privacy: data clustering and privacy frameworks. Third, we discuss the effort of privacy study from the perspectives of different disciplines, respectively. Fourth, the mathematical description, measurement, and modeling on privacy are presented. We summarize the challenges and opportunities of this promising topic at the end of this paper, hoping to shed light on the exciting and almost uncharted land.
机译:大数据最令人关注的问题之一就是隐私。但是,关于大数据隐私的研究仍处于早期阶段。我们相信即将到来的大数据隐私解决方案和理论源于隐私学科的就地研究成果。受这些因素的驱使,我们在应用和理论角度对隐私领域的现有研究成果和成就进行了广泛的调查,旨在为感兴趣的读者解决大数据案例中的挑战奠定坚实的起点。我们首先通过定义隐私系统的角色和操作来概述战场。其次,我们回顾了当前隐私的两个主要研究类别的里程碑:数据聚类和隐私框架。第三,我们分别从不同学科的角度讨论隐私研究的工作。第四,介绍了关于隐私的数学描述,测量和建模。在本文结尾处,我们总结了这个充满希望的主题所面临的挑战和机遇,希望借此阐明令人兴奋且几乎未知的土地。

著录项

  • 作者

    Yu, Shui;

  • 作者单位
  • 年度 2016
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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