Trails Learning Project
An individualÕs location-visit pattern, or trail, can be
leveraged to link sensitive data back to identity. We propose
a secure multiparty computation protocol that enables
locations to provably prevent such linkages. The protocol
incorporates a controllable parameter specifying the minimum
number of identities a sensitive piece of data must be
linkable to via its trail.
Bradley Malin and Latanya Sweeney. Composition and Disclosure of Unlinkable Distributed Databases. 22nd IEEE International Conference on Data Engineering, (ICDE). Atlanta, GA, April 2006. (PDF).