A hybrid neuro-fuzzy-inspired intrusion detection system achieved an AUC of 0.904 and an F1 score of 0.823 for detecting DDoS attacks in an extended IoMT scenario including ECG traffic.
A hybrid neuro-fuzzy intrusion detection system effectively identifies DDoS attacks in IoMT environments with ECG monitoring, achieving an AUC of 0.904 and enabling rapid automated threat mitigation.
Distributed denial-of-service (DDoS) attacks pose a critical threat to the availability of the Internet of Medical Things (IoMT). This paper proposes an intrusion detection system (IDS) based on a hybrid neuro-fuzzy-inspired approach to identify DDoS attacks in IoMT environments. The architecture combines an ensemble of decision trees, a sigmoidal smoothing mechanism, and a multilayer neural meta-classifier, enabling the modeling of nonlinear relationships between legitimate and malicious traffic without requiring explicit fuzzy rules or a formal fuzzy inference mechanism. The evaluation was conducted using the public DoS/DDoS-MQTT-IoT dataset, which was extended by incorporating legitimate traffic generated by electrocardiography (ECG) monitoring devices to approximate real operational IoMT conditions. The model was validated using stratified cross-validation and bootstrap procedures. In the extended IoMT scenario including ECG traffic, the proposed approach achieved an area under the ROC curve (AUC) of 0.904 and an F1 score of 0.823. Finally, the IDS was integrated into an intrusion detection and prevention system (IDPS) capable of detecting anomalous traffic patterns within three seconds and automatically blocking malicious IP addresses after repeated detections.
Parra et al. (Fri,) conducted a other in DDoS attacks in IoMT environments. Hybrid neuro-fuzzy-inspired intrusion detection system (IDS) was evaluated on Area under the ROC curve (AUC) and F1 score for detecting DDoS attacks. A hybrid neuro-fuzzy-inspired intrusion detection system achieved an AUC of 0.904 and an F1 score of 0.823 for detecting DDoS attacks in an extended IoMT scenario including ECG traffic.