Title :
Geo-Location Inference Attacks: From Modelling to Privacy Risk Assessment (Short Paper)
Author :
Nunez del Prado Cortez, Miguel ; Frignal, Jesus
Author_Institution :
LAAS, Toulouse, France
Abstract :
Despite the commercial success of Location-Based Services (LBS), the sensitivity of the data they manage, specially those concerning the user´s location, makes them a suitable target for geo-location inference attacks. These attacks are a new variant of traditional inference attacks aiming at disclosing personal aspects of users´ life from their geo-location datasets. Since this threat might dramatically compromise the privacy of users, and so the confidence of LBS, a deeper knowledge of geo-location inference attacks becomes essential to protect LBS. To contribute to this goal, this short paper makes a step forward to model well-known types of geo-location inference attacks as a previous step to quantitatively assess the privacy risk they pose.
Keywords :
data privacy; mobile computing; risk management; LBS; geo-location datasets; geo-location inference attacks; location-based services; privacy risk assessment modelling; Data privacy; Hidden Markov models; Privacy; Security; Semantics; Trajectory;
Conference_Titel :
Dependable Computing Conference (EDCC), 2014 Tenth European
Conference_Location :
Newcastle
DOI :
10.1109/EDCC.2014.32