An Ensemble Data Security on Cloud Healthcare Systems

The widespread use of cloud computing in healthcare systems has resulted in numerous advantages, such as increased scalability, cost efficiency, and access to medical data. The sensitive nature of healthcare data, on the other hand, poses significant challenges to its security and privacy in the cloud environment. In this study, an Advanced Integrated Data Security (AIDS) approach for cloud-based healthcare systems aims to address the vulnerabilities caused by data breaches and unauthorized access. The proposed AIDS is the data security framework that employs several security mechanisms to improve the overall security of healthcare data stored and processed in the cloud. It combines complementary techniques such as encryption, access control, anomaly detection, and intrusion prevention to create a comprehensive security infrastructure. Encryption algorithms transform healthcare data into an unreadable format that can only be accessed with appropriate decryption keys, ensuring the confidentiality and integrity of the data. An advanced role-based access control system is developed to manage user permissions and prevent unauthorized access to sensitive information. Anomaly detection techniques also detect abnormal patterns and behaviors in the cloud environment. Potential security breaches can be seen in real-time by continuously monitoring system logs and network traffic, allowing for prompt response and mitigation measures. Intrusion prevention systems actively prevent and block unauthorized access attempts, network attacks, and malicious activities to improve overall security. These systems analyze incoming and outgoing traffic using various detection algorithms to identify and thwart potential threats. The ensemble data security strategy capitalizes on the synergistic effects of combining multiple security mechanisms. The framework improves the resilience of cloud-based healthcare systems against data breaches and cyber threats by integrating encryption, access control, anomaly detection, and intrusion prevention. This work lays the groundwork for future research and development on data security in cloud-based healthcare systems. The proposed ensemble approach provides a robust and comprehensive solution for protecting sensitive healthcare data while enabling secure and trusted cloud-based healthcare services.