Geolocation of Data in the Cloud

We introduce and analyze a general framework for authen-tically binding data to a location while providing strong assurances against cloud storage providers that (either ac-cidentally or maliciously) attempt to re-locate cloud data. We then evaluate a preliminary solution in this framework that combines constraint-based host geolocation with proofs of data possession, called constraint-based data geolocation (CBDG). We evaluate CBDG using a combination of ex-periments with PlanetLab and real cloud storage services, demonstrating that we can bind fetched data to the loca-tion originally hosting it with high precision. We geolocate data hosted on the majority of our PlanetLab targets to re-gions no larger than 118,000 km2, and we geolocate data hosted on Amazon S3 to an area no larger than 12,000 km2, suciently small to identify the state or service region