Title :
Privacy Preserving Pattern Classification
Author :
Avidan, Shai ; Elbaz, Ariel ; Malkin, Tal
Abstract :
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.
Keywords :
cryptographic protocols; pattern classification; cryptographic protocols; privacy preserving pattern classification; secure dot product; Blood; Circuits; Cryptographic protocols; Cryptography; Data privacy; Event detection; Gunshot detection systems; Pattern classification; Surveillance; US Government;
Conference_Titel :
Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-1765-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2008.4712097
