Cybersecurity Attack-Resilience Authentication Mechanism for Intelligent Healthcare System

Abstract

People focus on the intelligent healthcare system expecting sufficient medical facilities even from a remote location. However, to make the healthcare system more trustworthy, secure access control plays a vital role in resisting several cyber-attacks. Security threat on medical data is highly sensitive since it is associated with life risks. When a user accesses a healthcare system through the Internet, the main concern is preventing unauthorized access to vital healthcare-related data. Traditional authentication (based on a password, smartcard, and/or biometric) provides a solution to allow such kind of application only to the authorized users. But once a user is authenticated, and he/she is idle for a while, the chances of security threat are reasonably high. This article has designed an intelligent user recognization mechanism for continuous monitoring of the user’s activity throughout the session. We have made the system user-friendly through single sign-on and eliminated trusted third-party dependence to avoid data breaches. Once the authentication is performed, then in a later stage, the continuous monitoring mechanism based on machine learning techniques helps to decide the user’s unique behavior allowing the application server to make better decisions regarding the user’s authenticity in the current session. The security analysis shows that the proposed system is more secure than the traditional authentication mechanisms.