Continuous Authentication using Smart Health Monitoring System
Pavithra D R1, Supritha R2

1Pavithra D R, Department of Bachelor of Engineering in Electronics and Communication, Sri Jayachamarajendra College of Engineering, Mysuru (Karnataka), India.
2Supritha R, Department of Bachelor of Engineering in Electronics and Communication, has received her Bachelor of Engineering in Electronics and Communication, Vidyavardhaka College of Engineering, Mysuru (Karnataka), India.

Manuscript received on 18 June 2019 | Revised Manuscript received on 25 June 2019 | Manuscript published on 30 June 2019 | PP: 2319-2324 | Volume-8 Issue-5, June 2019 | Retrieval Number: E7814068519/19©BEIESP
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Abstract: The main security issue in most of the computer is user identification and authentication. In traditional authentication schemes, the user is only validated during initial login which provides low security for the system. Hence continuous authentication has to be done to resolve the security issue. With increase in the number of smartphone users, continuous validation of the authenticated user is important. Continuous authentication mechanism can be made using two behavioral traits: app usage and touch based. There is a worldwide increase in the usage of apps that works on touchscreen, hence both can be used for authentication. Hence, the continuous authentication will be based on app usage and touch screen based which provide high security. In this paper, smart health monitoring system is used for continuous authentication. The data which is collected from wearable biomedical sensors for continuous health monitoring can also be used for continuous authentication. Although the biomedical signals are not highly discriminative a robust machine learning to obtain high accuracy levels is used. An android app is developed to gather data and send to cloud for data storage. The user is validated based on the decisions from the classifiers. The proposed work does not need any extra model for data collection as it uses the data gathered for health monitoring purpose, it can be used for low cost applications.
Keywords: Authentication, Wearable Biomedical Sensors, Machine Learning, Security.

Scope of the Article: Biomedical Computing