A Prevention Technique-Based Framework for Securing Healthcare Data

Data security is the process of safeguarding digital information, such as that contained in a database, from malicious entities and uninvited human behaviour, such as a cyberattack or a data breach. Since most medical records are currently housed on an antiquated digital file management system, malicious actions have been committed frequently due to our government's lack of interest in the healthcare industry, putting patients’ health at risk and causing financial loss. Hospitals and the insurance industry are at great danger of financial loss as a result of these frauds. In this paper, we discuss a framework that uses a method that primarily verifies the records to guard against malicious activity. If malicious activity has so far taken place, it will be detected using machine learning (ML) technology, maintaining the confidentiality, integrity, and availability (CIA) of the EHR. The primary goal of our framework is to provide a secure environment for EHR and give the investigators leads that they can follow up on and perhaps recover from, recuperate from, or refer to the proper authorities or agencies.