Cloud-based healthcare architecture for securing and monitoring healthcare data.
Journal:
Journal of health organization and management
Published Date:
Jun 25, 2026
Abstract
PURPOSE: A new method known as Lionized Remora optimization based Recurrent Neural Network (LRObRNN) is recommended to enhance the safety of medical information stored on cloud servers to tackle these issues. DESIGN/METHODOLOGY/APPROACH: To safeguard patient data, healthcare organizations must thoughtfully choose reliable and compliant cloud service providers while implementing robust security measures. Storing patient information in cloud systems raises issues with illegal access and data breaches. FINDINGS: The LRObRNN generates a secret key using Lionized Remora optimization and employs cryptography to encrypt sensitive healthcare data. Continuous monitoring ensures the security of data transmission by identifying irregularities. ORIGINALITY/VALUE: Leveraging Recurrent Neural Networks the system analyzes sequential data, enabling the detection of patterns and potential security breaches during data transmission. The performance evaluation includes metrics such as encryption and decryption time, confidentiality rate, processing time, resource usage and efficiency, which are compared with other existing models.
Authors
Keywords
No keywords available for this article.
