This thesis studies the features and performance of privacy-preserving distributed data mining protocols published as journal articles and conference proceedings from 1999 to 2009. It examines the topics and settings of various privacy-preserving distributed data mining protocols. This thesis aims to provide a framework for classifying privacy-preserving distributed data mining protocols and compare the performance of different protocols based on the outcome of the classification scheme.