Secure E-Health Management Automated Insights Generation for Datasets Classifications in Machine Learning on Cloud Framework

Authors

  • G. Raja Ramesh Research Scholar, School of Computing Science & Engineering, Galgotias University, Greater Noida, India
  • Rajesh E. Professor, School of Computing Science & Engineering, Galgotias University, Greater Noida, India

Keywords:

Cloud computing, AI, healthcare, secure, cryptography, PHE, information evaluation

Abstract

Cloud computing provides great solutions to these problems by providing convenient, on-demand service whenever and wherever it is needed. With cloud-based health care solutions, hospitals and clinics may avoid spending money on expensive infrastructure upgrades and save money on routine maintenance. Clouds in the health and wellness industry are salable and can handle fluctuating loads. When it comes to healthcare, cloud-based services may include fail-safes like disaster recovery and redundancy to protect against failures and lessen the impact of service interruptions. The health and wellness cloud is the central data repository that facilitates effective data access and sharing. Our system's PHE schemes and Re-encryption algorithms are based on the below group choice issue, different logarithms, and bi-linear enhancements. Due to the time-consuming decryption and memory- intensive re-encryption processes, system performance may suffer.We use a PHE system and a Re-encryption formula based on a combination of the sub-team-choice problem, separate logarithms, and bi-linear transformations in our system. Due to the time- consuming decryption process and the memory requirements of re-encryption, the system's efficiency may suffer. In order to enhance the accuracy of both prediction and protection, the AI principle has been combined with a variety of algorithmic perspectives, including as categorization and grouping, deep semantic network, and quantum semantic network. In addition to reducing phm strikes by an estimated 100 percent, the recommended designs also boost cloud customers' faith in the service and the bottom lines of cloud service providers (CSPs). Since data security and data personal privacy are the primary worries in today digital age, this study attempts to erase such problems and assist in end-to-end protection and secrecy of persons' info live in cloud environment corporation. This finding demonstrates how the cloud environment ends up being really useful for consumers in terms of security.

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Published

07.01.2024

How to Cite

Ramesh, G. R. ., & E., R. . (2024). Secure E-Health Management Automated Insights Generation for Datasets Classifications in Machine Learning on Cloud Framework. International Journal of Intelligent Systems and Applications in Engineering, 12(10s), 239–252. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4373

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Section

Research Article