Sensitivity Analysis of Personal Location Disclosure

Regular people give away their location data without much knowledge about what can be inferred from it. This paper presents a sensitivity analysis of location disclosure, showing what can be inferred from even just a few place visits. The aim is to highlight how modern inference algorithms can take small location disclosures and create detailed inferences about where else a person is likely to go and what sorts of places they tend to visit. Based on an analysis of over 100,000 people, we show how disclosing just one location point can be used to predict other visits with an AUC of 0.88. We develop another algorithm that shows the types of places a person has an unusually high propensity to visit, and we use this result as part of an economic analysis of delivering targeted advertising. This research serves to raise awareness about what can be inferred from even very small location disclosures, which can in turn inform regular people about their true privacy risks.