Research on Privacy-Preserving Two-Party Collaborative Filtering Recommendation
Gansen Zhao · Dianzi xuebao · 2009
Privacy-preserving collaborative filtering aims at protecting participating parties' privacy while providing high-quality recommendations efficiently.In the case of the number of the participating parties is greater than 2,a protocol,employing commutative encryption as its major privacy-preserving technique,has been devised to address the issue of rating a specific item in scenarios with distributed data storage,which is a key challenge in privacy-preserving collaborative filtering recommendation in that scenarios.However,the protocol does not work when the number of the participating parties is exactly 2.Employing secure comparison and secure dot product as its fundamental security infrastructure,we design a privacy-preserving two-party collaborative computing protocol to address the challenge.This protocol produces the same results as the traditional memory-based collaborative filtering recommender systems.Based on secure multi-party computation theory and simulation paradigm,the protocol's security is proved.The protocol's computation complexity and communication cost are examined as well.