Enhancing Medical Device Security: Exploring the Exploitability and Impact of GUI Vulnerabilities Through a Hacking Tool Experiment

In the context of medical device security, the risks associated with graphical user interfaces (GUIs) have not received sufficient attention despite extensive research on vulnerabilities in such devices. To bridge this gap, the proposed technique aims to investigate the exploitability and impact of GUI vulnerabilities in medical equipment. By providing a proof of concept for the exploitability of GUI flaws, this research contributes to the ongoing efforts in securing medical devices, safeguarding patient safety, and protecting personal information. To address the aforementioned research gap, an experiment is conducted. This experiment encompasses the development of a hacking tool utilizing artificial intelligence (AI) to facilitate the evaluation of the effectiveness of cyberattacks. The experiment primarily focused on a simulated medical device, which consisted of an Android tablet running Kotlin software. The results of the experiment demonstrated that the hacking device exhibited inconsistent performance when used to compromise the GUIs of medical devices. While the device had limitations in terms of set-up time, reliability, adaptability, and speed, potential enhancements were identified and recommended for future iterations.