Key result
Ethical hacking of an open-source Cardiac Medical Diagnosis System successfully identified a major authentication vulnerability, allowing unauthorized access to sensitive ECG data.
Why the study?
Recent cyber attacks have targeted medical systems and compromised diagnosis results, motivating an evaluation of how Cardiac Medical Diagnosis Systems (CMDS) can be hacked and how to prevent such attacks.
Ethical hacking of a simulated Cardiac Medical Diagnosis System revealed major authentication vulnerabilities, highlighting the critical need for cybersecurity defenses to protect sensitive ECG data.
Prompts security audits for cardiac diagnostic software; leaves open prevalence across commercial platforms.
The medical systems have been targeted by the cyber attackers. This paper is motivated by the recent attacks that have resulted in the compromise of diagnosis results. This study was undertaken to show how the Cardiac Medical Diagnosis Systems (CMDS) can be hacked and propose security recommendations to prevent such attacks. We build a simulation platform by implementing an open source medical system. We feed the ECGs data from the PhysioNet/Computing in Cardiology (CinC) Challenge 2017 to the open source medical system. We then follow the OWASP pen-testing methodology to perform the ethical hacking. The hacking was successful and we have identified a major vulnerability of the system related to authentication. Finally, we are able to gain access to the sensitive ECG data. We then proposed cyber recommendations to prevent such attacks. Future work will consider using a mature CMDS, such as the arrhythmia detection and classification in ambulatory ECGs to investigate how the core of the algorithms can be attacked and protected.
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He et al. (2019) studied Cardiac Medical Diagnosis Systems (CMDS) cybersecurity. Ethical hacking (OWASP pen-testing methodology) was evaluated on Vulnerability identification and access to sensitive ECG data. Ethical hacking of an open-source Cardiac Medical Diagnosis System successfully identified a major authentication vulnerability, allowing unauthorized access to sensitive ECG data.
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