Probabilistic positioning in mobile phone network and its consequences for the privacy of mobility data

Aleksey Ogulenko, Itzhak Benenson*, Itzhak Omer, Barak Alon

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


The traditional approach to mobile phone positioning is based on the assumption that the geographical location of a cell tower recorded in a Call Details Record (CDR) is a proxy for a device's location. A Voronoi tessellation is then constructed based on the entire network of cell towers and this tessellation is considered as a coordinate system, with the device located in a Voronoi polygon of a cell tower that is recorded in the CDR. If Voronoi-based positioning is correct, the uniqueness of the device trajectory is very high, and the device can be identified based on 3–5 of its recorded locations. We investigate a probabilistic approach to device positioning that is based on knowledge of each antennas' parameters and number of connections, as dependent on the distance to the antenna. The critical difference between the Voronoi-based and the real world layout is in the essential overlap of the antennas' service areas: The device that is located in a cell tower's polygon can be served by a more distant antenna that is chosen by the network system to balance the network load. Combining data on the distance distribution of the number of connections available for each antenna in the network, we resolve the overlap problem by applying Bayesian inference and construct a realistic distribution of the device location. Probabilistic device positioning demands a full revision of mobile phone privacy and new full set of tools for data analysis.

Original languageEnglish
Article number101550
JournalComputers, Environment and Urban Systems
StatePublished - Jan 2021


FundersFunder number
Israeli Ministry of Absorption
Israeli Ministry of Science and Technology
Ministry of Aliyah and Immigrant Absorption
Tel Aviv University
Ministry of Science and Technology, Israel


    • Bayesian inference
    • Call details record
    • Location privacy
    • Mobile phone positioning


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