The (Co-)Location Sharing Game - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Proceedings on Privacy Enhancing Technologies Année : 2019

The (Co-)Location Sharing Game

Résumé

Most popular location-based social networks, such as Facebook and Foursquare, let their (mobile) users post location and co-location (involving other users) information. Such posts bring social benefits to the users who post them but also to their friends who view them. Yet, they also represent a severe threat to the users' privacy, as co-location information introduces interdependences between users. We propose the first game-theoretic framework for analyzing the strategic behaviors, in terms of information sharing, of users of OSNs. To design parametric utility functions that are representative of the users' actual preferences, we also conduct a survey of 250 Facebook users and use conjoint analysis to quantify the users' benefits of sharing vs. viewing (co)-location information and their preference for privacy vs. benefits. Our survey findings expose the fact that, among the users, there is a large variation, in terms of these preferences. We extensively evaluate our framework through data-driven numerical simulations. We study how users' individual preferences influence each other's decisions, we identify several factors that significantly affect these decisions (among which, the mobility data of the users), and we determine situations where dangerous patterns can emerge (e.g., a vicious circle of sharing, or an incentive to over-share)--even when the users share similar preferences.
Fichier principal
Vignette du fichier
Olteanu2019PETS.pdf (2.95 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-01584427 , version 1 (29-04-2019)

Identifiants

Citer

Alexandra-Mihaela Olteanu, Mathias Humbert, Kévin Huguenin, Jean-Pierre Hubaux. The (Co-)Location Sharing Game. Proceedings on Privacy Enhancing Technologies, 2019, 2019 (2), pp.5-25. ⟨10.2478/popets-2019-0017⟩. ⟨hal-01584427⟩

Collections

TDS-MACS
132 Consultations
47 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More