Fully homomorphic encryption-based optimal key encryption for privacy preservation in the cloud sector

Abstract

Cloud computing infrastructure has been specifically designed to handle vast amounts of data as well as relevant details that are most basic for data-intensive applications. However, cloud computing has been exposed to various internal and external security threats along with privacy concerns. Therefore, an intelligent framework named privacy preservation in the cloud sector (PPCS) is implemented in this work. The main phases taken up in the proposed security model are data sanitization and restoration. The data stored in the cloud infrastructure is subjected to a data sanitization operation. In the data sanitization process, the data is transformed into another form, where the confidential data has been preserved by the optimal key generation operation. An improved meta-heuristic algorithm called Improved Class Topper Optimization (ICTO) derived from existing Class Topper Optimization (CTO) is designed for performing the optimal key generation. This algorithm aids in optimizing the key generated in the data sanitization technique. To offer more security to the cloud environment, the encryption of the generated optimal key is done by fully homomorphic encryption (FHE). It permits the preservation of confidentiality in sensitive data. The performance results of the designed approach illustrated the ability of this technique to prevent attacks without increasing energy consumption and latency.