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The exposure of location data constitutes a significant privacy risk to usersas it can lead to de-anonymization, the inference of sensitive information, andeven physical threats. In this paper we present LPAuditor, a tool that conductsa comprehensive evaluation of the privacy loss caused by publicly availablelocation metadata. First, we demonstrate how our system can pinpoint users' keylocations at an unprecedented granularity by identifying their actual postaladdresses. Our experimental evaluation on Twitter data highlights theeffectiveness of our techniques which outperform prior approaches by18.9%-91.6% for homes and 8.7%-21.8% for workplaces. Next we present a novelexploration of automated private information inference that uncovers"sensitive" locations that users have visited (pertaining to health, religion,and sex/nightlife). We find that location metadata can provide additionalcontext to tweets and thus lead to the exposure of private information thatmight not match the users' intentions.  We further explore the mismatch between user actions and information exposureand find that older versions of the official Twitter apps follow aprivacy-invasive policy of including precise GPS coordinates in the metadata oftweets that users have geotagged at a coarse-grained level (e.g., city). Theimplications of this exposure are further exacerbated by our finding that usersare considerably privacy-cautious in regards to exposing precise location data.When users can explicitly select what location data is published, there is a94.6% reduction in tweets with GPS coordinates. As part of current efforts togive users more control over their data, LPAuditor can be adopted by majorservices and offered as an auditing tool that informs users about sensitiveinformation they (indirectly) expose through location metadata.

Please Forget Where I Was Last Summer: The Privacy Risks of Public Location (Meta)Data