Big data anonymization with spark

Yavuz Canbay, Ş. Sağiroğlu
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引用次数: 11

Abstract

Privacy is an important issue for big data including sensitive attributes. In the case of directly sharing or publishing these data, privacy breach occurs. In order to overcome this problem, previous studies were focused on developing big data anonymization techniques on Hadoop environment. When compared to Hadoop, Spark facilitates to develop faster applications with the help of keeping data in memory instead of hard disk. Despite a number of projects were developed on Hadoop, now this trend is shifting to Spark. In addition, the problem of anonymizing big data streams for real-time applications can be solved with Spark technology. Hence to sum up, Spark is the main technology facilitates developing both faster anonymization applications and big data stream anonymization solutions. In this study, anonymization techniques, big data technologies and privacy preserving big data publishing was reviewed and a big data anonymization model based on Spark was proposed for the first time. It is expected that the proposed model might help to researchers to solve big data privacy issues and also provide solutions for new generation privacy violations problems.
使用spark实现大数据匿名化
隐私是包含敏感属性的大数据的一个重要问题。在直接共享或发布这些数据的情况下,会发生隐私泄露。为了克服这一问题,以往的研究主要集中在Hadoop环境下开发大数据匿名化技术。与Hadoop相比,Spark通过将数据保存在内存而不是硬盘中来帮助开发更快的应用程序。尽管有许多项目是在Hadoop上开发的,但现在这一趋势正在转向Spark。此外,实时应用的大数据流匿名化问题也可以通过Spark技术来解决。总之,Spark是开发更快的匿名化应用程序和大数据流匿名化解决方案的主要技术。本研究综述了匿名化技术、大数据技术和保护隐私的大数据发布,并首次提出了基于Spark的大数据匿名化模型。期望所提出的模型可以帮助研究者解决大数据隐私问题,也为新一代隐私侵犯问题提供解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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