Development of a Network Intrusion Detection and Alerting System

Cyber Security — 2025, Undergraduate

This study developed a web-based network intrusion detection and alerting system that monitors network traffic for suspicious signatures and anomalous patterns. The system logs events, raises alerts, and presents dashboards of detected incidents to administrators. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, Flask, and SQLite. The findings showed that the system improved detection visibility and reduced response time to suspicious activity, while achieving a high System Usability Scale score. The study recommends integration with firewall logs and periodic rule updates.

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