Cybersecurity Threats in Industrial Healthcare Systems

• •Industrial healthcare systems are increasingly targeted by cyberattacks due to protocol vulnerabilities.
• •The EDND approach improves intrusion detection performance significantly over traditional methods.
• •The IEC 60870-5-104 protocol is identified as particularly insecure, necessitating enhanced security measures.

The industrial healthcare environment faces increasing cyber threats due to the insecure IEC 60870-5-104 protocol, which is widely used for communication among medical devices and IoT sensors. An ensemble deep neural decision tree (EDND) approach has been developed to enhance intrusion detection in these systems. The performance of this method was evaluated using TCP/IP and IEC 60870-5-104 protocols, showing a 9.37% accuracy and 9.66% F1-score improvement over existing methodologies. The rise in cyberattacks targeting industrial healthcare systems has been documented, with a notable increase compared to non-industrial sectors. The proposed IDS can help network administrators monitor and analyze traffic to mitigate these risks. This research was presented at the 2026 International Conference on Intelligent Control and Information Processing.