Improved sun flow optimization (I-SFO) algorithm based de-centralized information flow control for multi-tenant cloud virtual machines

A novel multi-tenant decentralized information flow control (MT-DIFC) model is introduced in this research work. In cloud computing, the MT-DIFC allows a larger pool of resources to be shared among a larger number of people without compromising privacy and security. Initially, the sensitive data is isolated from the rest on the basis of the security level. Then, these sensitive data are subjected to encryption via an improved signcryption algorithm. At the receiver end, the decryption takes place based on the computed two-level trust model. Interestingly, here the direct, as well as indirect trust, is computed for the ones who request for access privileges to the data owners. Based on the computed trust level, the access privilege is provided to the user's request; and here the level of document readability and downloading capability will be decided by the data owner. Based on the computed trust level, the decryption of the data (only the permitted data-level access provided by the owner) is accomplished. Furthermore, the improved sun flow optimization algorithm (I-SFO) has been introduced for optimal key generation. This I-SFO model is validated by varying its weight function W from 100, 150 and 200, respectively. In addition, a non-parametric analysis has been carried out to validate the efficiency of I-SFO. Accordingly, the outcomes reveal that the proposed work has attained the least cost function, while fixing W=100, 150 and 200, respectively.