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.