Combined approach of tokenization and mining to secure and optimize big data in cloud storage

Shanto Roy, Ahmedur Rahman Shovon, Md. Whaiduzzaman
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引用次数: 15

Abstract

The era of technology is now shifting towards the Cloud Computing and today's computation tends to be provisioned as a service rather than a product. Recently Cloud Computing has become more portable and flexible in such way so that we call it having a super computer in our pockets. Despite the potential application of cloud computing, data security is still questionable in privacy issue due to insider threats and data breaches. After the internet of things (IoT) emerges, in Big data arena both data security and storage optimization at the same time has been a crying need. In this paper, we propose an enhanced framework of security model including tokenization with a view to eradicating the privacy issue of sensor data and ensuring storage optimization. Tokenization provides a wider range of security by protecting data from malicious insider threats or data breaches in cloud. Our proposed tokenization process optimizes cloud storage instances as well with a little prior mining in order to convert large data sets into small ones.
令牌化和挖掘相结合的方法来保护和优化云存储中的大数据
技术时代正在转向云计算,今天的计算倾向于作为服务而不是产品来提供。最近,云计算变得更加便携和灵活,以至于我们把它称为口袋里的超级计算机。尽管云计算具有潜在的应用前景,但由于内部威胁和数据泄露,数据安全在隐私问题上仍然存在问题。随着物联网(IoT)的出现,在大数据领域,数据安全和存储优化已经成为迫切需要。在本文中,我们提出了一个增强的安全模型框架,包括令牌化,以期消除传感器数据的隐私问题并确保存储优化。通过保护数据免受恶意内部威胁或云中的数据泄露,令牌化提供了更广泛的安全性。我们提出的标记化过程也优化了云存储实例,并进行了一些预先挖掘,以便将大数据集转换为小数据集。
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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