A check-in shielding scheme against acquaintance inference in location-based social networks

Bo Heng Chen, Cheng Te Li, Kun Ta Chuang

Research output: Contribution to journalArticle

Abstract

Location-based social services such as Foursquare and Facebook Place allow users to perform check-ins at places and interact with each other in geography (e.g. check-in together). While existing studies have exhibited that the adversary can accurately infer social ties based on check-in data, the traditional check-in mechanism cannot protect the acquaintance privacy of users. In this work, therefore, we propose a novel shielding check-in system, whose goal is to guide users to check-in at secure places. We accordingly propose a novel research problem, Check-in Shielding against Acquaintance Inference (CSAI), which aims at recommending a list of secure places when users intend to check-ins so that the potential that the adversary correctly identifies the friends of users can be significantly reduced. We develop the Check-in Shielding Scheme (CSS) framework to solve the CSAI problem. CSS consists of two steps, namely estimating the social strength between users and generating a list of secure places. Experiments conducted on Foursquare and Gowalla check-in datasets show that CSS is able to not only outperform several competing methods under various scenario settings, but also lead to the check-in distance preserving and ensure the usability of the new check-in data in Point-of-Interest (POI) recommendation.

Original languageEnglish
Pages (from-to)2321-2354
Number of pages34
JournalWorld Wide Web
Volume22
Issue number6
DOIs
Publication statusPublished - 2019 Nov 1

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All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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