TY - JOUR
T1 - Probabilistic positioning in mobile phone network and its consequences for the privacy of mobility data
AU - Ogulenko, Aleksey
AU - Benenson, Itzhak
AU - Omer, Itzhak
AU - Alon, Barak
N1 - Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2021/1
Y1 - 2021/1
N2 - 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.
AB - 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.
KW - Bayesian inference
KW - Call details record
KW - Location privacy
KW - Mobile phone positioning
UR - http://www.scopus.com/inward/record.url?scp=85092529950&partnerID=8YFLogxK
U2 - 10.1016/j.compenvurbsys.2020.101550
DO - 10.1016/j.compenvurbsys.2020.101550
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AN - SCOPUS:85092529950
SN - 0198-9715
VL - 85
JO - Computers, Environment and Urban Systems
JF - Computers, Environment and Urban Systems
M1 - 101550
ER -