Computer Science > Cryptography and Security
arXiv:2211.11577 (cs)
[Submitted on 18 Nov 2022]
Title:Data Privacy in Multi-Cloud: An Enhanced Data Fragmentation Framework
View a PDF of the paper titled Data Privacy in Multi-Cloud: An Enhanced Data Fragmentation Framework, by Randolph Loh and 1 other authors
View PDFAbstract:Data splitting preserves privacy by partitioning data into various fragments to be stored remotely and shared. It supports most data operations because data can be stored in clear as opposed to methods that rely on cryptography. However, majority of existing data splitting techniques do not consider data already in the multi-cloud. This leads to unnecessary use of resources to re-split data into fragments. This work proposes a data splitting framework that leverages on existing data in the multi-cloud. It improves data splitting mechanisms by reducing the number of splitting operations and resulting fragments. Therefore, decreasing the number of storage locations a data owner manages. Broadcasts queries locate third-party data fragments to avoid costly operations when splitting data. This work examines considerations for the use of third-party fragments and application to existing data splitting techniques. The proposed framework was also applied to an existing data splitting mechanism to complement its capabilities.
| Comments: | Keywords: Data Storage, Multi-Cloud, Cloud Security, Privacy Preservation, Privacy Enhancing, Data Splitting;this https URL |
| Subjects: | Cryptography and Security (cs.CR); Distributed, Parallel, and Cluster Computing (cs.DC) |
| Cite as: | arXiv:2211.11577 [cs.CR] |
| (orarXiv:2211.11577v1 [cs.CR] for this version) | |
| https://doi.org/10.48550/arXiv.2211.11577 arXiv-issued DOI via DataCite | |
| Journal reference: | In 2021 18th International Conference on Privacy, Security and Trust (PST), pp. 1-5. IEEE, 2021 |
| Related DOI: | https://doi.org/10.1109/PST52912.2021.9647746 DOI(s) linking to related resources |
Submission history
From: Vrizlynn L. L. Thing [view email][v1] Fri, 18 Nov 2022 10:39:31 UTC (316 KB)
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View a PDF of the paper titled Data Privacy in Multi-Cloud: An Enhanced Data Fragmentation Framework, by Randolph Loh and 1 other authors
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