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Perceived Right to Privacy by Information Systems Professionals in Big Data Collection.

机译:信息系统专业人员在大数据收集中享有的隐私权。

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摘要

Although privacy is not a new term in big data analytics, the phenomena underlying why it continues to crop up in literature as a little investigated and undervalued concern remains unexplored. This endeavor is particularly relevant, especially given that cloud technology continues to foster the enormous amounts of collected data by the Internet of Things (IoT) gadgets, and by users of e-commerce and social media sites. The exploration and focus on privacy expectations by information systems professionals (ISPs) may begin to address privacy preservation at the most basic, first-stages of big data collection, as sensitive information initially becomes available to IT personnel. ISPs must recognize personal and private information in the collection process to ensure preservation before completion of data analysis (Lin, 2016). Today's interconnected technologies and businesses make it necessary to address privacy at the most fundamental stage, collection, to assure proper protocols remain in place for data mining purposes. This study explores the lived experiences of a small group of ISPs to understand better what privacy means to them at the time data is being gathered to address the disconnect between analysts and private information and begin to set a foundation for future discussions on the perceived rights to privacy, privacy-preservation, and initiate an open dialogue for further research.
机译:尽管隐私在大数据分析中并不是一个新名词,但由于一些经过调查和被低估的关注,为什么它在文学中不断涌现的潜在现象仍未得到探索。这项工作特别有意义,特别是考虑到云技术继续促进物联网(IoT)小工具以及电子商务和社交媒体网站用户的大量收集数据。随着敏感信息最初可供IT人员使用,信息系统专业人员(ISP)对隐私期望的探索和关注可能会开始在最基本的大数据收集第一阶段解决隐私保护问题。 ISP必须在收集过程中识别个人和私人信息,以确保在完成数据分析之前将其保存(Lin,2016年)。当今互连的技术和业务使得有必要在最基本的收集阶段解决隐私问题,以确保为数据挖掘目的保留适当的协议。这项研究探索了一小组ISP的生活经验,以便在收集数据以解决分析师与私人信息之间的脱节之时更好地了解隐私对他们意味着什么,并开始为以后讨论感知的权利奠定基础。隐私,保护隐私并发起公开对话以进一步研究。

著录项

  • 作者

    Mayhew, Lauren A.;

  • 作者单位

    Colorado Technical University.;

  • 授予单位 Colorado Technical University.;
  • 学科 Computer science.
  • 学位 D.C.S.
  • 年度 2017
  • 页码 111 p.
  • 总页数 111
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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