University of Twente Student Theses


Monitoring crowd dynamics by passively sniffing cellular traffic

Redonet Klip, T.H. (2020) Monitoring crowd dynamics by passively sniffing cellular traffic.

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Abstract:Monitoring crowd dynamics assists in a multitude of scenarios. Examples are safety regulations at events, urban planning, and marketing strategies. A common way to monitor crowds is to detect smartphones by capturing Wi-Fi probe requests. However, this method produces noisy datasets. In this work, alternative ways to detect mobile phones are trying to be found. This research chose to focus on cellular networks, in particular the GSM network. GSM uses paging requests to wake up mobile phones for incoming traffic. These paging requests contain an identifier, the TMSI. The assumption is made that mobile phones can be detected, identified, and tracked through the paging requests they receive. This work conducted several experiments to validate this assumption. A Software Defined Radio (SDR) Dongle was used to sniff paging requests. Simultaneously, a mobile phone with custom firmware was used in different scenarios. It turns out that the paging channel of the GSM network does not provide enough paging requests to track mobile phones. However, more modern cellular networks like LTE, which is used for more applications than GSM, might have more potential since they also use paging requests containing a TMSI. This work also did a literature research on physical layer identification, where wireless devices are identified by the raw radio waves they emit.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:50 technical science in general
Programme:Embedded Systems MSc (60331)
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