Title :

FOUGERE: User-Centric Location Privacy in Mobile Crowdsourcing Apps

Author(s) :

Meftah, Lakhdar [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Rouvoy, Romain [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Institut Universitaire de France [IUF]
Chrisment, Isabelle [Auteur]
Resilience and Elasticity for Security and ScalabiliTy of dynamic networked systems [RESIST]

Scientific editor(s) :

José Pereira
Laura Ricci

Conference title :

DAIS 2019 - 19th IFIP International Conference on Distributed Applications and Interoperable Systems

City :

Kongens Lyngby

Country :

Danemark

Start date of the conference :

2019-06-17

Book title :

Lecture Notes in Computer Science

Journal title :

Distributed Applications and Interoperable Systems

Publisher :

Springer International Publishing

Publication date :

2019

English keyword(s) :

LPPM
mobile crowdsourcing
Location privacy

HAL domain(s) :

Informatique [cs]/Système d'exploitation [cs.OS]
Informatique [cs]/Web
Informatique [cs]/Informatique mobile
Informatique [cs]/Informatique ubiquitaire
Informatique [cs]/Génie logiciel [cs.SE]
Informatique [cs]

English abstract : [en]

Mobile crowdsourcing is being increasingly used by industrial and research communities to build realistic datasets. By leveraging the capabilities of mobile devices, mobile crowdsourcing apps can be used to track participants' ...
Show more >Mobile crowdsourcing is being increasingly used by industrial and research communities to build realistic datasets. By leveraging the capabilities of mobile devices, mobile crowdsourcing apps can be used to track participants' activity and to collect insightful reports from the environment (e.g., air quality, network quality). However, most of existing crowdsourced datasets systematically tag data samples with time and location stamps, which may inevitably lead to user privacy leaks by discarding sensitive information. This paper addresses this critical limitation of the state of the art by proposing a software library that improves user privacy without compromising the overall quality of the crowdsourced datasets. We propose a decentralized approach, named Fougere, to convey data samples from user devices to third-party servers. By introducing an a priori data anonymization process, we show that Fougere defeats state-of-the-art location-based privacy attacks with little impact on the quality of crowd-sourced datasets.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

ANR Project :

Comprendre et diagnostiquer les dégradations des communications de bout en bout dans l'Internet

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL