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FOUGERE: User-Centric Location Privacy in ...
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Document type :
Communication dans un congrès avec actes
DOI :
10.1007/978-3-030-22496-7_8
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] refId
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' ...
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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
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