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Challenges on Anonymity, Privacy, and Big Data

机译:匿名,隐私和大数据方面的挑战

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This paper provides an overview of the tools and methodologies for data privacy protection that can cope with the challenges raised by the Big Data storage and analytics processing, with focus on anonymity. Preserving individual privacy is one of the major issues in the context of Big Data, as while handling huge volumes of data, it is possible that sensitive or personally identifiable information ends up disclosed. In fact, even when dealing with anonymized raw data, sensitive information may be extracted through analytics. Preserving anonymity is particularly difficult because it should be done while allowing the analytics to produce useful insight about the data. We further discuss these challenges and future research directions in order to perform big data analytics in a privacy-compliant way.
机译:本文概述了数据隐私保护的工具和方法,这些工具和方法可以应对由大数据存储和分析处理引起的挑战,重点是匿名性。保护个人隐私是大数据环境中的主要问题之一,因为在处理海量数据时,最终可能会泄露敏感或个人身份信息。实际上,即使在处理匿名原始数据时,也可以通过分析来提取敏感信息。保留匿名性特别困难,因为应在允许分析产生有关数据的有用见解的同时进行。我们将进一步讨论这些挑战和未来的研究方向,以便以符合隐私的方式执行大数据分析。

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