Open Access

ARTICLE

Protecting Data Mobility in Cloud Networks Using Metadata Security

R. Punithavathi^1,*, M. Kowsigan², R. Shanthakumari³, Miodrag Zivkovic⁴, Nebojsa Bacanin⁴, Marko Sarac⁴

1 Department of Information Technology, M.Kumarasamy College of Engineering, Karur, 639113, India
2 Department of Computer Science and Engineering, School of Computing, SRM Institute of Technology, Kattankulathur Campus, Chennai, 603203, India
3 Department of Information Technology, Kongu Engineering College, Erode, 638060, India
4 Singidunum University, Belgrade, 11000, Serbia

* Corresponding Author: R. Punithavathi. Email:

Computer Systems Science and Engineering 2022, 42(1), 105-120. https://doi.org/10.32604/csse.2022.020486

Received 26 May 2021; Accepted 19 July 2021; Issue published 02 December 2021

Abstract

At present, health care applications, government services, and banking applications use big data with cloud storage to process and implement data. Data mobility in cloud environments uses protection protocols and algorithms to secure sensitive user data. Sometimes, data may have highly sensitive information, leading users to consider using big data and cloud processing regardless of whether they are secured are not. Threats to sensitive data in cloud systems produce high risks, and existing security methods do not provide enough security to sensitive user data in cloud and big data environments. At present, several security solutions support cloud systems. Some of them include Hadoop Distributed File System (HDFS) baseline Kerberos security, socket layer-based HDFS security, and hybrid security systems, which have time complexity in providing security interactions. Thus, mobile data security algorithms are necessary in cloud environments to avoid time risks in providing security. In our study, we propose a data mobility and security (DMoS) algorithm to provide security of data mobility in cloud environments. By analyzing metadata, data are classified as secured and open data based on their importance. Secured data are sensitive user data, whereas open data are open to the public. On the basis of data classification, secured data are applied to the DMoS algorithm to achieve high security in HDFS. The proposed approach is compared with the time complexity of three existing algorithms, and results are evaluated.

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Keywords

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