TY - GEN
T1 - Enhancing Medical Device Security
T2 - 9th International Conference on Cyber Security, Privacy in Communication Networks, ICCS 2023
AU - Küfner, Jan J.K.
AU - Tahir, Sabeen
AU - Bakhsh, Sheikh Tahir
AU - Mohaisen, Linda
AU - Danso, Samuel
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024/9/18
Y1 - 2024/9/18
N2 - 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.
AB - 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.
KW - Graphical user interfaces (GUIs)
KW - Kotlin software
KW - Medical device security vulnerabilities
KW - Patient safety
UR - http://www.scopus.com/inward/record.url?scp=85205117027&partnerID=8YFLogxK
U2 - 10.1007/978-981-97-3973-8_27
DO - 10.1007/978-981-97-3973-8_27
M3 - Conference contribution
AN - SCOPUS:85205117027
SN - 9789819739721
T3 - Lecture Notes in Networks and Systems
SP - 431
EP - 452
BT - AI Applications in Cyber Security and Communication Networks - Proceedings of 9th International Conference on Cyber Security, Privacy in Communication Networks ICCS 2023
A2 - Hewage, Chaminda
A2 - Nawaf, Liqaa
A2 - Kesswani, Nishtha
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 9 December 2023 through 10 December 2023
ER -