Enhancing Data Security in Cloud using Random Pattern Fragmentation and a Distributed NoSQL Database
dc.contributor.author | Santos, NL | |
dc.contributor.author | Ghita, B | |
dc.contributor.author | Masala, GL | |
dc.date.accessioned | 2021-05-18T12:57:55Z | |
dc.date.available | 2021-05-18T12:57:55Z | |
dc.date.issued | 2019-10 | |
dc.identifier.isbn | 9781728145693 | |
dc.identifier.issn | 1062-922X | |
dc.identifier.uri | http://hdl.handle.net/10026.1/17145 | |
dc.description.abstract |
The cloud computing model has become very popular among users, as it has proven to be a cost-effective solution to store and process data, thanks to recent advancements in virtualization and distributed computing. Nevertheless, in the cloud environment, the user entrusts the safekeeping of its data entirely to the provider, which introduces the problem of how secure such data is and whether its integrity has been maintained. This paper proposes an approach to the data security in cloud by utilizing a random pattern fragmentation algorithm and combining it with a distributed NoSQL database. This not only increases the security of the data by storing it in different nodes and scramble all the bytes, but also allows the user to implement an alternative method of securing data. The performance of the approach is compared to other approaches, along with AES 256 encryption. Results indicate a significant performance improvement over encryption, highlighting the capabilities of this method for cloud stored data, as it creates a layer of protection without additional overhead. | |
dc.format.extent | 3735-3740 | |
dc.language.iso | en | |
dc.publisher | IEEE | |
dc.title | Enhancing Data Security in Cloud using Random Pattern Fragmentation and a Distributed NoSQL Database | |
dc.type | conference | |
dc.type | Conference Proceeding | |
plymouth.author-url | https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000521353903122&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008 | |
plymouth.date-start | 2019-10-06 | |
plymouth.date-finish | 2019-10-09 | |
plymouth.volume | 2019-October | |
plymouth.publisher-url | https://ieeexplore.ieee.org/xpl/conhome/8906183/proceeding | |
plymouth.conference-name | 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) | |
plymouth.publication-status | Published | |
plymouth.journal | 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) | |
dc.identifier.doi | 10.1109/smc.2019.8914454 | |
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 | 2022-1-21 | |
dc.rights.embargoperiod | Not known | |
rioxxterms.versionofrecord | 10.1109/smc.2019.8914454 | |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | |
rioxxterms.licenseref.startdate | 2019-10 | |
rioxxterms.type | Conference Paper/Proceeding/Abstract |