Check2: A Framework for Fake Check-in Detection

Abstract

Location-based social networks (LBSNs) have increased rapidly over the past several years due to the proliferation of mobile devices. As people continue to use their phones everywhere and all the time - even while they shop and dine, a lot of LBSN services such as Foursquare (https://foursquare.com/), Facebook place (https://www.facebook.com/places/) have been introduced. These LBSNs provide new types of services that are location based for social network users. LBSNs integrate the functionalities of both location services and social networks. Consequently, this empowers people to use location data with online social networks in several ways including: location recommendation, mobile-advertising, etc. Mainly, LBSN is widely used in sharing location between users. In addition, LBSNs make use of the notion of “check-in” to enable users to share their location with other users. To attract more users, LBSN service providers offer rewards to users who check-in at a certain place, however, this caused some users (i.e. attackers) to cheat regarding their true locations in order to get either monetary or virtual rewards. Nevertheless, fake check-ins can cause monetary losses to service providers. In this paper, we propose a novel framework for analyzing users’ check-ins and detecting fake check-ins.