Cryptographically private support vector machines

Sven Laur, Helger Lipmaa, Taneli Mielikäinen
2006 Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '06  
We study the problem of private classification using kernel methods. More specifically, we propose private protocols implementing the Kernel Adatron and Kernel Perceptron learning algorithms, give private classification protocols and private polynomial kernel computation protocols. The new protocols return their outputs-either the kernel value, the classifier or the classificationsin encrypted form so that they can be decrypted only by a common agreement by the protocol participants. We also
more » ... w how to use the encrypted classifications to privately estimate many properties of the data and the classifier. The new SVM classifiers are the first to be proven private according to the standard cryptographic definitions.
doi:10.1145/1150402.1150477 dblp:conf/kdd/LaurLM06 fatcat:bb5pdymn4ff7leqx2hm3unz2f4