  The proliferation of location-based social networks (LBSNs) has provided the
community with an abundant source of information that can be exploited and used
in many different ways. LBSNs offer a number of conveniences to its
participants, such as - but not limited to - a list of places in the vicinity
of a user, recommendations for an area never explored before provided by other
peers, tracking of friends, monetary rewards in the form of special deals from
the venues visited as well as a cheap way of advertisement for the latter.
However, service convenience and security have followed disjoint paths in LBSNs
and users can misuse the offered features. The major threat for the service
providers is that of fake check-ins. Users can easily manipulate the
localization module of the underlying application and declare their presence in
a counterfeit location. The incentives for these behaviors can be both earning
monetary as well as virtual rewards. Therefore, while fake check-ins driven
from the former motive can cause monetary losses, those aiming in virtual
rewards are also harmful. In particular, they can significantly degrade the
services offered from the LBSN providers (such as recommendations) or third
parties using these data (e.g., urban planners). In this paper, we propose and
analyze a honeypot venue-based solution, enhanced with a challenge-response
scheme, that flags users who are generating fake spatial information. We
believe that our work will stimulate further research on this important topic
and will provide new directions with regards to possible solutions.
