A Study on Autoencoder-based Reconstruction Method for Wi-Fi Location Data with Erasures,

Tetsushi Ohki and Akira Otsuka
Proceedings of the 2017 on Multimedia Privacy and Security, Dallas, Texas, USA, pp.13–18, Oct 2017.


Anonymization is one of the major processes to protect location-based services (LBS) from privacy leakage. However, there are many discussions about de-anonymization attacks to LBS and whether anonymization processing is a su cient countermeasure for privacy leakage. In this paper, we proposed a novel method to reconstruct the location of user considering the time series using the Markov Transition Field (MTF) and Denoising Auto Encoder (DAE). We also focused on Wi-Fi location data including many erasures errors. We conducted an evaluation of de-anonymization attack using our reconstruction method to the Wi-Fi location dataset that was consisted of 10000 devices / four weeks in the four wards of Tokyo. We con rmed that the successful attack rate (SAR) was 24% when the number of candidate devices was 100 and 6% when that was 10000 devices.