IDAP’26September 5–6, 2026

Network Security · Machine Learning · IoT / IIoT

Evaluating Machine Learning Models for Network Anomaly Detection in IoT Environments

A controlled comparison of five classical machine-learning models for binary IoT/IIoT anomaly detection

Bilal ABDULHADIPresenter
Mhd Raja ABOU HARBCo-author

Computer Engineering Department · Biruni University

CONNECTED ENVIRONMENTSmart homeIoT endpointHealthcareIoT endpointTransportIoT endpointIndustryIIoT endpointAttack trafficAnomalous pathnormal trafficanomalyGatewayTraffic streamML detectorBinary decisionAnomaly identifiedAttack_label = 1DEVICES → TRAFFIC → ANOMALY → DETECTION
10th International Artificial Intelligence and Data Processing Symposium01 / 13
01/13