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Abstract
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Article Information:
Data Classification Based on Confidentiality in Virtual Cloud Environment
Munwar Ali Zardari, Low Tang Jung and Mohamed Nordin B. Zakaria
Corresponding Author: Munwar Ali Zardari
Submitted: November 23, 2013
Accepted: March 08, 2014
Published: October 05, 2014 |
Abstract:
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The aim of this study is to provide suitable security to data based on the security needs of data. It is very difficult to decide (in cloud) which data need what security and which data do not need security. However it will be easy to decide the security level for data after data classification according to their security level based on the characteristics of the data. In this study, we have proposed a data classification cloud model to solve data confidentiality issue in cloud computing environment. The data are classified into two major classes: sensitive and non-sensitive. The K-Nearest Neighbour (K-NN) classifier is used for data classification and the Rivest, Shamir and Adelman (RSA) algorithm is used to encrypt sensitive data. After implementing the proposed model, it is found that the confidentiality level of data is increased and this model is proved to be more cost and memory friendly for the users as well as for the cloud services providers. The data storage service is one of the cloud services where data servers are virtualized of all users. In a cloud server, the data are stored in two ways. First encrypt the received data and store on cloud servers. Second store data on the cloud servers without encryption. Both of these data storage methods can face data confidentiality issue, because the data have different values and characteristics that must be identified before sending to cloud severs.
Key words: Cloud computing, data classification, data confidentiality/sensitivity, distributed computing, K-NN, non-sensitive, RSA
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Cite this Reference:
Munwar Ali Zardari, Low Tang Jung and Mohamed Nordin B. Zakaria, . Data Classification Based on Confidentiality in Virtual Cloud Environment . Research Journal of Applied Sciences, Engineering and Technology, (13): 1498-1509.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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