The (Co-)Location Sharing Game: Benefits and Privacy Implications of (Co)-Location Sharing with Interdependences

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Ressource 1Télécharger: Olteanu2019PoPETS.pdf (1292.18 [Ko])
Etat: Public
Version: Author's accepted manuscript
Licence: Non spécifiée
ID Serval
serval:BIB_2A6E03A65E35
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Institution
Titre
The (Co-)Location Sharing Game: Benefits and Privacy Implications of (Co)-Location Sharing with Interdependences
Titre de la conférence
Proceedings on Privacy Enhancing Technologies
Auteur(s)
Olteanu A.-M., Humbert M., Huguenin K., Hubaux J.-P.
Statut éditorial
Publié
Date de publication
05/2019
Peer-reviewed
Oui
Volume
2019
Numéro
2
Pages
5-25
Langue
anglais
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.
Open Access
Oui
Création de la notice
12/11/2018 14:28
Dernière modification de la notice
12/12/2021 6:37
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