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Research Paper | Information Technology | India | Volume 6 Issue 1, January 2017 | Rating: 5.4 / 10
Optimizing Healthcare Data Management in the Cloud: Leveraging Intelligent Schemas and Soft Computing Models for Security and Efficiency
Krishna Chaitanya Rao Kathala [2] | Ranadeep Reddy Palle [4]
Abstract: Cloud computing plays a pivotal role in advancing the revolution of sensitive information management within the healthcare sector, facilitating the global exchange of health records through electronic means. Managing vast volumes of healthcare data is a monumental task, considering the multitude of patients whose information must be securely stored for future use. To address these challenges, the healthcare industry is increasingly integrating cloud computing into its systems for enhanced efficiency. This study focuses on evaluating the implementation of cloud computing for the management of extensive data in the healthcare sector. To tackle this objective, we propose an intelligent optimal schema that leverages soft computing models for the classification and management of vast sensitive data in the cloud. The approach begins with the introduction of the smart flower optimization (SFO) algorithm, specifically designed to optimize the cloud central server. This optimization ensures system scalability while concurrently reducing user access time and communication delays. Additionally, a time - limited optimal access control mechanism is employed to safeguard data privacy. The snow leopard optimization (SLO) algorithm is applied to data access, mitigating security flaws and enhancing privacy. Intensive execution appraisals approve the adequacy of the proposed structure, uncovering exceptional exactness, accuracy, review, and F1 - score upsides of 96.16%, 96.44%, 95.83%, and 96.14%, individually. These results emphasize the framework's exceptional capabilities in safeguarding sensitive healthcare data within the cloud computing platform from unauthorized access and maintaining its confidentiality.
Keywords: vast sensitive, data management, data security, cloud computing, soft computing
Edition: Volume 6 Issue 1, January 2017,
Pages: 2477 - 2486