Abstract: Privacy protection is an important issue in data mining. Adding noise to the data can protect the privacy to some extent. However, the accuracy of the result is reduced due to the noisy mask. This paper proposes an efficient distributed privacy preserving framework based on rational cryptography. In the framework, it is assumed that each party is rational, rather than malicious or honest, which is the usual setting in cryptography. Based on this assumption, we show that many data mining functions can be realized efficiently in a distributed way with a semi-honest third party.

Key words: rational cryptography, data mining, privacy preserving, secure multi-party computation