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A General Overview of Privacy-Preserving Big Data Management and Analytics Models, Methods and Techniques in Specific Domains: Static and Dynamic Distributed Environments

机译:特定领域的隐私保护大数据管理和分析模型,方法和技术概述:静态和动态分布式环境

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Privacy-preserving big data management and analytics is gaining the momentum within the research community, and several current research efforts aim to provide solutions to the challenges that emerge when models, techniques and algorithms must be delivered on top of massive, distributed big data repositories, especially with regards to emerging distributed settings such as Clouds and social networks. In this paper, at the convergence of the contexts of static and dynamic distributed environments, we provide a general overview of models, issues and approaches, along with some reference frameworks. Indeed, both static and dynamic distributed environments are relevant cases of settings where the privacy of big data turns to be critical. Finally, we discuss emerging research directions.
机译:保持隐私的大数据管理和分析正在研究领域内蓬勃发展,当前的一些研究工作旨在为必须在大型分布式大数据存储库之上交付模型,技术和算法时出现的挑战提供解决方案,尤其是针对新兴的分布式环境,例如云和社交网络。在本文中,在静态和动态分布式环境的上下文融合中,我们提供了模型,问题和方法的概述,以及一些参考框架。确实,静态和动态分布式环境都是与设置有关的情况,在这种情况下,大数据的隐私变得至关重要。最后,我们讨论了新兴的研究方向。

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