Predicting Users' Motivations behind Location Check-Ins and Utility Implications of Privacy Protection Mechanisms - Université Toulouse 1 Capitole Accéder directement au contenu
Communication Dans Un Congrès Année : 2015

Predicting Users' Motivations behind Location Check-Ins and Utility Implications of Privacy Protection Mechanisms

Résumé

Location check-ins contain both geographical and semantic information about the visited venues, in the form of tags (e.g., “restaurant”). Such data might reveal some personal information about users beyond what they actually want to disclose, hence their privacy is threatened. In this paper, we study users’ motivations behind location check-ins, and we quantify the effect of a privacy-preserving technique (i.e., generalization) on the perceived utility of check-ins. By means of a targeted user study on Foursquare (N = 77), we show that the motivation behind Foursquare check-ins is a mediator of the loss of utility caused by generalization. Using these findings, we propose a machine learning method for determining the motivation behind each check-in, and we design a motivation-based predictive model for utility. Our results show that the model accurately predicts the loss of utility caused by semantic and geographical generalization; this model enables the design of utility-aware, privacy-enhancing mechanisms in location-based social networks.
Fichier principal
Vignette du fichier
Bilogrevic2015NDSS.pdf (422.45 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01076554 , version 1 (03-12-2014)

Identifiants

Citer

Igor Bilogrevic, Kévin Huguenin, Stefan Mihaila, Reza Shokri, Jean-Pierre Hubaux. Predicting Users' Motivations behind Location Check-Ins and Utility Implications of Privacy Protection Mechanisms. 22nd Network and Distributed System Security Symposium (NDSS), Feb 2015, San Diego, CA, United States. ⟨10.14722/ndss.2015.23032⟩. ⟨hal-01076554⟩
787 Consultations
460 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More