Privacy Preserving Pattern Classification
Shai Avidan, Ariel Elbaz, Tal Malkin · 2008
We give efficient and practical protocols for privacy preserving pattern classification that allow a client to have his data classified by a server, without revealing information to either party, other than the classification result. We illustrate the advantages of such a framework on several real-world scenarios and give secure protocols for several classifiers.