Analyzing semantic locations cloaking techniques in a probabilistic grid-based map

The protection of semantic positions, for instance that an individual is inside a hospital, is a challenging privacy issue. For example, it can be shown that popular protection mechanisms, like location cloaking, can be easily defeated when certain mobility patterns are known, e.g., certain places are more or less popular than other places. To prevent this kind of attack, novel semantic location cloaking heuristics are being investigated. These methods are built on the knowledge of population distribution and sensitive locations. In this demonstration, we present SAWL (Semantics-aware Location cloaking), a tool supporting the comparison of semantic location cloaking methods over real and synthetic spatial scenarios.