An Efficient Big Data Security and Privacy in Healthcare for Enhancing Remote Sensing and Monitoring: A Technological Perspective based on ACL for Preserving Big Data Analytics in Cloud

Abstract

The growing adoption of big data technologies in healthcare has significantly enhanced patient care, diagnostics, and system efficiency. Yet, this transformation brings with it serious concerns about the security and privacy of sensitive medical information. The health care industry is in a critical phase of intelligence with the rapid advancement of modern information technology. With the increased use of healthcare big data, the issue of information security is increasingly becoming critical in the management of smart healthcare care, including the leak of patient privacy, the most critical issue. Thus, the enhancement of information management of intelligent health care during the age of big data is a significant aspect of long-term sustainable development of the hospitals. This paper has initially determined the most influential indicators to influence the privacy disclosure of big data in managing health care and presented a comprehensive overview of the current landscape in healthcare data security and thereafter set the privacy and security based access control model, which has been applied on the security and management of big data in utilization of medical data, and solves the issue of actual data breach where actual problems are involved. Lastly, the model is contrasted with the state-of-the-art techniques. The paper offers a comparative analysis of proposed solution considering numerous parameters and highlights critical gaps for building more secure and trustworthy healthcare systems. The findings confirm that the model is useful in the evaluation of the existing safety threats and forecasting the scope of the various risk factors, by demonstrating that Network Segmentation and Cloud Usage (Hybrid) have significantly enhanced the results by 1.5% and 6.7% respectively and the User Access mechanism is upgraded by 1.5% and 6.7% respectively. The Audit Trail and Compliance is also improving as the proposed technique examines ACL and explores key global regulatory frameworks like the GDPR and HIPAA. The outcome of this study suggests that the proposed access control model is resistant to most cyber-attacks in big data, and it is also demonstrated that the offered framework can be used as a starting point in order to develop secure and safe medical big data solutions. Therefore, this study can be valuable to future scholars to understand the information about the security and privacy of big data in the medical field and ways to implement countermeasures.