Multilevel Security Embedded Information Retrieval and Tracking on Cloud Environments

Cloud Computing is emerging technology that provides services of storage and platform software to large organizations, but some of them are still hesitant to shift their setups on the cloud due to security issues and risks. Thus, it is important to address the security issues and problems in cloud systems. In this research we contributed to a multilevel security (MLS) framework based on data sensitivity and security that provides adequate level of data security based on various classifications and categories. The proposed multilevel security embedded information retrieval tool in this paper encompasses suitable access control combined with Security Enhanced Linux (SELinux) that facilitates classification of the data based on subsequent changes in the sensitivity levels of the data and changes in the security measures to cope with the dynamic and vulnerable changes in cloud security threats. To implement the proposed MLS framework, the SELinux system is applied as a testbed to retrieve information and track the history of the data retrieved.