Cyber Security and Layering of Medical Data Using Machine Learning Algorithms

For a few years, all industries have felt the magic of technological advancements, and one of the fastest-growing industries has been the healthcare industry. Many technologies have now enabled doctors to diagnose and treat patients more accurately than ever. The Health Insurance Portability and Accountability Act of 1996 (HIPAA) is a law that was enacted by the 104th United States Congress to protect sensitive information in the healthcare industry from being accessed by cybercriminals. It established guidelines for physical and technical security measures to be put in place, such as workstation security, device and media controls, and facility access controls. Technical safeguards include the use of unique identification numbers, emergency access procedures, automatic logoff, encryption, and decryption. The adoption of healthcare technology can be a complex process, requiring careful planning and implementation. Organizations are spending large amounts of funding to become more integrated and secure but need more time or money to update software. This paper demonstrates the deployment of data layers on Medical Data. Patient records are kept in a remote server and are accessed only when required by algorithms that show the trends at macro levels. In this paper, we have exhibited the deployment of this layer using a disease prediction model that presents current and possible future trends of the disease occurrence.