We present an efficient protocol for the privacy-preserving, distributed learning of decision-tree classifiers. Our protocol allows a user to construct a classifier on a database h...
— Recent work [12] shows that conventional privacy preserving publishing techniques based on anonymity-groups are susceptible to corruption attacks. In a corruption attack, if th...
Abstract. Rental records contain much sensitive information on individuals, so if abused by the rental service providers, user privacy could be jeopardized. To mitigate this concer...
A new framework of privacy-preserving identity management for distributed e-Health systems is proposed. Utilizing a consumer-centric approach, the healthcare consumer maintains a ...
Abstract. We present protocols for distributed computation of relational intersections and equi-joins such that each site gains no information about the tuples at the other site th...