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.
|Número de páginas
|Publicada - 1 ene. 2014
|Publicado de forma externa
|Proceedings - 2014 10th European Dependable Computing Conference, EDCC 2014 -
Duración: 1 ene. 2014 → …
|Proceedings - 2014 10th European Dependable Computing Conference, EDCC 2014
|1/01/14 → …