A robust reputation-based location-privacy recommender system using opportunistic networks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Location-sharing services have grown in use commensurately with the increasing popularity of smart phones. As location data can be sensitive, it is important to preserve people’s privacy while using such services, and so location-privacy recommender systems have been proposed to help people configure their privacy settings.These recommenders collect and store people’s data in a centralised system, but these themselves can introduce new privacy threats and concerns.In this paper, we propose a decentralised location-privacy recommender system based on opportunistic networks. We evaluate our system using real-world location-privacy traces, and introduce a reputation scheme based on encounter frequencies to mitigate the potential effects of shilling attacks by malicious users. Experimental results show that, after receiving adequate data, our decentralised recommender system’s performance is close to the performance of traditional centralised recommender systems (3% difference in accuracy and 1% difference in leaks). Meanwhile, our reputation scheme significantly mitigates the effect of malicious users’input (from 55% to 8% success) and makes it increasingly expensive to conduct such attacks.
Original languageEnglish
Title of host publicationProceedings of The 8th EAI International Conference on Mobile Computing, Applications and Services
PublisherACM
DOIs
Publication statusPublished - 1 Dec 2016
Event8th EAI International Conference on Mobile Computing, Applications and Services - DoubleTree by Hilton Hotel - Cambridge City Centre, Cambridge, United Kingdom
Duration: 30 Nov 20161 Dec 2016
Conference number: 8
http://mobicase.org/2016/show/home

Conference

Conference8th EAI International Conference on Mobile Computing, Applications and Services
Abbreviated titleMobiCASE
Country/TerritoryUnited Kingdom
CityCambridge
Period30/11/161/12/16
Internet address

Keywords

  • Location-based services
  • Privacy
  • Recommender systems
  • Opportunistic networks
  • Security
  • Shilling attack

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