Title: Performance analysis of data fragmentation techniques on a cloud server

Authors: Nelson Santos; Salvatore Lentini; Enrico Grosso; Bogdan Ghita; Giovanni Masala

Addresses: Big Data Group, University of Plymouth, Drake Circus, PL4 8AA, Plymouth, UK ' Big Data Group, University of Plymouth, Drake Circus, PL4 8AA, Plymouth, UK ' Computer Vision Laboratory, University of Sassari, Viale Mancini, 5, 07100, Sassari, Italy ' Centre for Security, Communications and Network Research, University of Plymouth, Drake Circus, PL4 8AA, Plymouth, UK ' Big Data Group, University of Plymouth, Drake Circus, PL4 8AA, Plymouth, UK

Abstract: The advancements in virtualisation and distributed computing have allowed the cloud paradigm to become very popular among users and resources. It allows companies to save costs on infrastructure and maintenance and to focus on the development of products. However, this fast-growing paradigm has brought along some concerns from users, such as the integrity and security of the data, particularly in environments where users rely entirely on providers to secure their data. This paper explores different techniques to fragment data on the cloud and prevent direct unauthorised access to the data. It explores their performance on a cloud instance, where the total time to perform the operation, including the upload and download of the data, is considered. Results from this experiment indicate that fragmentation algorithms show better performance compared to encryption. Moreover, when combining encryption with fragmentation, there is an increase in the security, with the trade-off of the performance.

Keywords: cloud security; data fragmentation; data security; privacy in cloud computing; information security.

DOI: 10.1504/IJGUC.2019.100902

International Journal of Grid and Utility Computing, 2019 Vol.10 No.4, pp.392 - 401

Received: 11 Jun 2018
Accepted: 12 Sep 2018

Published online: 16 Jul 2019 *

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