doi: 10.18178/jacn.2023.11.1.285
Distributed Multilevel Secure Data Access Using SELinux-Enhanced Linux over Cloud Environments
,
,
Hanke Kimm
2
- 1 Department of Computer Science, East Stroudsburg University, PA, 18301, USA
- 2 Department of Computer Science, Stony Brook University, Stony Brook, NY, 11794, USA
- Manuscript received November 20, 2022
- revised February 2, 2023
- accepted March 29, 2023
Abstract
Cloud computing is an emerging technology, which provides a spectrum of services such as database, networks, software, storage over the cloud to many organizations on the internet; there is no need of keeping local servers for the organizations that adapt cloud computing for storing and accessing data and services, provided by remote servers. However, there are organization still hesitant to accommodate a cloud system due to security issues and risks. In this work, Security-Enhanced Linux (SELinux) with MultiLevel Security (MLS) framework is applied as a cloud security model; SELinux runs based on sensitivity and category labels of subject and objects − mostly users and data files respectively. The proposed MLS data access is a framework that employs data classification that works on subsequent changes in the sensitivity levels of subjects and objects to meet the dynamic changes of cloud security. To implement the proposed secure data access framework over the cloud system, the Fedora 35 system with SELinux is used as a testbed. We also present that data modification history can be retrieved on a MLS system by using user sensitivity and data information labels.
Keywords
- Security-enhanced Linux
- multilevel security
- data access
- cloud computing
How to Cite
Haklin Kimm, Eun-Joo Lee, and Hanke Kimm, "Distributed Multilevel Secure Data Access Using SELinux-Enhanced Linux over Cloud Environments," Journal of Advances in Computer Networks, vol. 11, no. 1, pp. 1-7, 2023. https://doi.org/ 10.18178/jacn.2023.11.1.285
Copyright & License
Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).