A Network-Driven Approach to Theft Detection in Shared Computing Environments

Abstract

In shared computing environments such as university computer labs, the risk of hardware theft is often overlooked by traditional cybersecurity measures. This project proposes and evaluates a lightweight, network-driven system for detecting potential hardware theft in real time. The solution relies on a “heartbeat” mechanism where each client device sends regular check-in signals to a central server. If a device stops reporting, the system flags it as potentially compromised.

A prototype was implemented and tested under controlled conditions, where it reliably detected critical hardware removal events. The system proved effective at generating timely alerts and minimising false positives during normal reboots. A web-based interface was developed, enabling administrators to monitor devices efficiently.

The findings highlight both the potential and the limitations of network-based monitoring in theft prevention and suggest future enhancements such as integration with maintenance schedules and machine learning. Overall, the project demonstrates that a simple, low-overhead network-based solution can offer substantial improvements in theft detection in shared-use IT environments.