AI-Based Security Attack Pathway for Cardiac Medical Diagnosis Systems (CMDS)

The Cardiac Medical Diagnosis Systems (CMDS) are targeted by the cyber attackers. This paper is motivated by the recent cyber-attacks happened during the COVID 19 that have resulted in the compromise of medical data. This study was carried out to demonstrate how the CMDS can be breached into using an AI-based ethical attack pathway and propose security solutions to prevent such beaches. This study is based on an established simulation platform with an open source medical system, the OpenEMR. The system was fed with the ECGs data from the PhysioNet/ Computing in Cardiology (CinC) Challenge 2017. This paper proposed the AI based hacking pathway following the NIST pen-testing methodology based on our previous identified vulnerability related to authentication. We then presented cyber security recommendations to prevent such AI-based attacks. Future work will consider a realistic CMDS, such as the arrhythmia detection and classification in ambulatory ECGs to find out how the algorithms core can be hacked and protected.