Detection System for Passive Network Eavesdropping

Eavesdropping on computer networks poses significant risks, including theft of personal data, unauthorized access, and user tracking. Passive eavesdropping is particularly challenging to detect and often becomes evident only after data misuse. This paper highlights the inherent risks of data traffic eavesdropping and introduces a method to detect passive eavesdropping in Wi-Fi networks. The proposed detection method analyzes user behavior through the traffic patterns generated that are integrated into an automatically configured server platform. The server infrastructure was designed to closely mimic real user traffic. Experimental verification demonstrated the system’s effectiveness in identifying instances of passive eavesdropping. This significantly improves the security of Wi-Fi networks.