INTELLIGENT CYBERSECURITY FOR IOMT SYSTEMS IN PSYCHIATRY: AN AI-DRIVEN APPROACH IN HEALTH 4.0

The rapid expansion of the Internet of Medical Things (IoMT) has increased the vulnerability of healthcare infrastructures to cyberattacks, particularly in sensitive domains such as psychiatry. In this paper, we propose ICAP-IoMT(Intelligent Cybersecurity Approach for Psychiatry in Internet of Medical Things), a novel hybrid model designed to enhance intrusion detection by integrating both network traffic data (BoT-IoT dataset) and psychiatric clinical data (PHQ-9, GAD-7, and related variables).The methodology relies on rigorous data preprocessin g, training with a Random Forest classifier, and systematic evaluation using standardmetrics(Accuracy,Precision,Recall,F1score).Experiment al results, obtained under the same conditions as the benchmark model SNN-IoMT (Benmalek et al., 2025), demonstrate that ICAP-IoMT consistently outperforms the reference across all metrics.