Ghita, Bogdan, Masala, Giovanni Luca, Grosso, Enrico, Lentini, Salvatore, Santos, Nelson (2019) Performance analysis of data fragmentation techniques on a cloud server. International Journal of Grid and Utility Computing, 10 (4). pp. 392-401. ISSN 1741-847X. E-ISSN 1741-8488. (doi:10.1504/IJGUC.2019.10022144) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:91403)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication) | |
Official URL: https://doi.org/10.1504/IJGUC.2019.10022144 |
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.
Item Type: | Article |
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DOI/Identification number: | 10.1504/IJGUC.2019.10022144 |
Uncontrolled keywords: | cloud security; data fragmentation; data security; privacy in cloud computing; information security |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Amy Boaler |
Date Deposited: | 08 Nov 2021 09:31 UTC |
Last Modified: | 05 Nov 2024 12:57 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/91403 (The current URI for this page, for reference purposes) |
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