Abstract
This research aims to evaluate the detection and management capabilities of an integrated security system named Sentinel, developed within an MQTT-based IoT simulation environment, against various cyberattack scenarios targeting IoT devices. It virtually models four types of devices and systematically applies attack types such as flooding, spoofing, data tampering, and unauthorized device access. The intrusion detection system module successfully detects anomalies based on messages frequency, content, timestamps, and device IP matching, achieving high accuracy especially in flood attacks. However, its detection capability remained limited for complex spoofing scenarios. Findings indicate that temporal analysis plays a critical role in anomaly detection and suggest the need for integration of behavior-based security mechanisms.