Medical Data Analytics for Secure Multi-party-primarily based Cloud Computing utilizing Homomorphic Encryption

Abstract

Cloud computing has emerged as a vibrant part of today's modern world, providing computer services such as data storage, managing and processing via the internet. For the most part, cloud applications emphasize a multi-tenant structure to provide support for several customers in a single instance. A multi-tenancy situation involving the allocation of resources in cloud storage and the risks associated with it, in which confidentiality or integrity may be compromised. Homomorphic encryption is one such technique which guarantees to franchise in safeguarding information under cryptographic domain. The proposed modified Algebra Homomorphic Encryption scheme based on updated ElGamal (AHEE) encryption scheme is designed in such a way that the cloud administrators do not obtain any information about the medical data. This scheme is quantitatively evaluated using metrics such as encryption time and decryption time. The experimental results using UCI Machine Learning Repository ECG data set show that the proposed scheme achieved shorter encryption time of 6.61 ms and decryption time of 5.94 ms and also analyze this secured datum using big data analytics.