Performance analysis of data fragmentation techniques on a cloud server
dc.contributor.author | Santos, N | |
dc.contributor.author | Lentini, S | |
dc.contributor.author | Grosso, E | |
dc.contributor.author | Ghita, B | |
dc.contributor.author | masala, giovanni | |
dc.date.accessioned | 2020-02-10T12:33:04Z | |
dc.date.available | 2020-02-10T12:33:04Z | |
dc.date.issued | 2019-01-01 | |
dc.identifier.issn | 1741-847X | |
dc.identifier.issn | 1741-8488 | |
dc.identifier.other | 4 | |
dc.identifier.uri | http://hdl.handle.net/10026.1/15370 | |
dc.description.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. | |
dc.format.extent | 392-401 | |
dc.language.iso | en | |
dc.title | Performance analysis of data fragmentation techniques on a cloud server | |
dc.type | journal-article | |
dc.type | Journal Article | |
plymouth.issue | 4 | |
plymouth.volume | 10 | |
plymouth.publication-status | Published | |
plymouth.journal | International Journal of Grid and Utility Computing | |
dc.identifier.doi | 10.1504/IJGUC.2019.100902 | |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics | |
plymouth.organisational-group | /Plymouth/Users by role | |
plymouth.organisational-group | /Plymouth/Users by role/Academics | |
dcterms.dateAccepted | 2019-01-01 | |
dc.rights.embargodate | 2022-1-25 | |
dc.identifier.eissn | 1741-8488 | |
dc.rights.embargoperiod | Not known | |
rioxxterms.versionofrecord | 10.1504/IJGUC.2019.100902 | |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | |
rioxxterms.licenseref.startdate | 2019-01-01 | |
rioxxterms.type | Journal Article/Review |