Data Protection Security Model Using Glowworm Swarm-Based Whale Optimized Framework Throughout The Cloud Computing World

Abstract

Preservation of security is urgently needed to minimize the disclosure of confidential patient data. Numerous methods of privacy protection are implemented in the cloud system, but in the cloud world, preserving personal data of the user is still a challenging problem. An important privacy protection policy must therefore be built to protect the user's medical data. The input medical data is initially obtained and introduced to the filter system to conduct the process of privacy protection. The filtering process is advanced using the 2D Infinite Impulse Response (IIR) filter which uses the filter factoring model to generate a filter matrix. The filtering matrix generated is used to create the data preserved for the security wherein the filter vector is focused on the planned Glowworm Swarm Whale Optimization Algorithm (GWOA), the Glowworm Swarm Optimization (GSO) and Whale Optimization Algorithm (WOA) integration. The data stored resulting in privacy is subjected to the data storage system, where the stored data is registered. Instead, the retained data is stored in the information environment's information management system to allow user access with greater privacy and utility.  With higher privacy, the proposed algorithm achieved better quality and utility values of 0.2698 and 0.8786, accordingly when the key size is 256 when using Switzerland database.