Cloud Security Enhancement using BGV Fully Homomorphic Encryption

Cloud computing empowers enterprises to efficiently manage big data and discovery of useful information which are the most fundamental challenges for big data enabled applications. The cloud offered unlimited resources that can store, manage and analyze massive and heterogeneous data to improve the quality assurance of application services. Nevertheless, cloud computing is exposed to enormous external and internal privacy breaches and leakage threats. Fully Homomorphic Encryption (FHE) is used as an emerging and powerful cryptosystem that can carry out analysis tasks on encrypted data. This research work proposes an approach for securing cloud data transmission using the Brakerski-Gentry-Vaikuntanathan (BGV) algorithm and self-key mutation technique. The proposed model is synchronized with the user role to generate tokens and keys for securing data on the cloud, and the algorithm used for key and token generation depends on the type of user or tenant. The proposed method is tested and compared with an existing method for key generation time, encryption time, and decryption time across different plain text sizes. The results show that the proposed method outperforms the existing method in all aspects.