Abstract—Cloud is an attractive computing paradigm for providing different kinds of computing services. Without realizing all day long, people are using cloud computing and their components. In the same way, without user’s knowledge the data can be stolen at any time. Every second huge amount of data is uploaded in the cloud worldwide. Data storage and retrieval is a tedious task, but cloud makes it easy for all levels of users and also provides many service advantages to the end users. Apart from all these benefits, cloud pulls back because of security of data uploaded in the cloud. Security of data is a vital research area in cloud, and needs to be addressed. To enhance the security of data in the cloud, this paper proposes an enhanced data obfuscation method-GLObfus to protect the numerical data which are uploaded to the cloud. The proposed obfuscation method uses different mathematical calculations and functions to convert the data into meaningless data. The numerical data prepared to add are obfuscated prior to storage in the cloud area. The proposed technique is applied as a cloud utility and hosted on a cloud platform as a service and examined with current obfuscation strategies with respect to time and security. From the effects, it's far discovered that the proposed obfuscation technique-GLObfus is more efficient than the current obfuscation strategies with respect to obfuscation time and de-obfuscation time and security level.
Index Terms—Cloud security, cloud storage, data obfuscation, data security.
D. I. George Amalarethinam and Lalu P. George are with Jamal Mohamed College, Bharathidasan University, Tamil Nadu, India (e-mail: di_george@ymail.com, icelalu@gmail.com).
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Cite:D. I. George Amalarethinam and Lalu P. George , "GLObfus: An Enhanced Data Security Method to Protect Numerical Data in Public Cloud Storage," International Journal of Computer Theory and Engineering vol. 12, no. 5, pp. 113-117, 2020.
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
