Harshvardhan

About the Project

In contrast to the Electronic Medical Record (EMR) and Electronic Health Record (EHR) systems that are created to maintain and manage patient data by health professionals and organizations, Personal Health Record (PHR) systems are operated and managed by patients. Therefore, it necessitates increased attention to the importance of security and privacy challenges, as patients are most often unfamiliar with the potential security threats that can result from release of their health data. On the other hand, the use of PHR systems is increasingly becoming an important part of the healthcare system by sharing patient information among their circle of care. To have a system with a more favorable interface and a high level of security, it is crucial to provide a mobile application for PHR that can continuously verify if the correct person is using the application. In this work we propose a method known as Continuous Proof of Presence (CPoP) authentication, which has the potential to provide an extra layer of security. The system studies the benign user’s interactions with their device such as typing speed, number of fingers used while typing, pressure applied on the screen, the orientation of the device while typing, the duration of touch actions. We then studied various machine learning models that could perform binary classification and predict if the correct user used the device.