Location Privacy of Cellular Networks : Measurements, Models, and Analysis

Location privacy refers to the protection of personal information related to one’s physical position. In the digital age, our devices—smartphones, wearable, and even cars—are constantly communicating with various networks, making it possible to track our movements and infer sensitive information about our lives, habits, and preferences. In this thesis, we investigate to what extent a cellular network can perform a privacy localization attack against a moving user. We considered two localization algorithms to measure the accuracy of the performance of the localization attacks: weighted non-linear least squares and non-weighted non-linear least squares. Furthermore, we investigated the impact of base station density, base station configuration, and base station separation distance. Simulation results show that the maximum localization accuracy that can be achieved was 10.2% and 20.4% meters at sigma values of 3 and 5, respectively.