Architecture of an Intelligent Security Monitoring System for IoT Devices in a Protected Digital Educational Environment

Key Points

• The study aims to develop an intelligent security monitoring system for IoT devices in educational settings.
• Utilized Isolation Forest and One-Class SVM models on a Raspberry Pi 4.
• Enabled local processing of network traffic to enhance data privacy.
• Focused on edge-oriented architecture for efficient anomaly detection.
• Achieved a detection accuracy of 0.962.
• Successfully identified network anomalies with minimal data privacy concerns.