Krypterad men spårbar: Hur WiFi-trafik kan avslöja användarbeteenden

Abstract

This study investigates what information about devices and user behavior can be extracted through passive analysis of wireless network traffic. By developing a pro totype system for data collection and traffic analysis, the feasibility of identifying device type, operating system, currently active application, user activities, and be havioral patterns over time is examined. The results indicate that it is possible, to some extent, to identify device type and operating system based on observable traffic patterns. However, the identification of user activities and specific applica tions remains uncertain and is affected by traffic variability and limited access to representative datasets. Furthermore, general behavioral patterns, such as recurring periods of activity, can be inferred, albeit with limited accuracy. Several factors in fluencing the reliability of the analysis are identified, including variations in signal strength and limitations inherent in passive traffic collection. These factors compli cate the consistent association of observed traffic with individual devices over time. Overall, the study demonstrates that network traffic analysis can provide insights into device characteristics and user behavior, even without access to the content of communication. At the same time, the accuracy is limited, and the results should be interpreted with caution, particularly when generalizing to more complex environ ments. The study thus highlights both the possibilities and limitations of this type of analysis, as well as the associated privacy implications.