Geosecure O: A Method for Secure Distance Calculation for Travel Mode Detection using Outsourced GPS Trajectory Data
Detecting the mode of transportation using multimedia sensory data, such as trajectory data, is an important research problem arising out in many application domains that use location based services (LBS) Due to the large volume, such data is commonly outsourced to third party cloud service providers (CSP) for storage and usage by the LBS providers. The LBS providers typically deploy mode detection algorithms at the CSPs, which leads to continuous tracking of the user's location and raises severe security and privacy concerns among the users. Although many approaches exist in the literature regarding travel mode detection, security, and privacy concerns are not addressed by them. GPS based mode detection algorithms use distance and derived features such as velocity and acceleration. In this paper, we present a method, called GeoSecure O, to securely calculate the distance without revealing the users' location to the LBS provider and utilize it to determine the travel mode. We evaluate the proposed method on the Microsoft GeoLife dataset. Experimental results show that the proposed method not only protects users' location but also achieves an accuracy similar to what is achieved using the data with users' location.
2019 IEEE Fifth International Conference on Multimedia Big Data (BigMM)