Ensuring privacy and confidentiality of data on the cloud using an enhanced homomorphism scheme

Cloud computing is one of the widest phenomena embraced in information technology. This result from numerous advantages associated with it making many organizations and individuals offload their data to cloud. Encryption schemes restrict access unauthorized clients, helping attain confidentiality privacy. The modification ciphertext clients’ on cloud demand downloading, deciphering, editing, finally uploading back by sharing private key service provider tedious. application homomorphism, allows computation be performed no decipher activity which helps avoid surfacing sensitive client stored In this paper, an Enhanced Homomorphism Scheme (EHS) proposed based Good Prime Numbers (GPN), Linear Congruential Generator (LCG), Fixed Sliding Window Algorithm (FSWA), Gentry’s homomorphism scheme. A dataset Kaggle database was used test algorithm. variety tests were conducted using algorithm such as Uniqueness ciphertext, addition multiplication property full execution times 2^n (n ∈ 2,3,4,5) sizes. comparison time EHS New Fully (NFHS), (EHES). From comparison, had lowest encryption when a size 24kb executed but higher decryption 567.6667 ± 96.38911when 8kb used. On other hand, 32kb, EHES highest 1274ms having 551.2222 82.68746 indicating percentage decrease 56.73%. confirms that are dependent not size.