Generally, colliding parties who have private data may conduct Privacy-Preserving Data Analysis (PPDA) tasks to learn beneficial data models in a distributed manner. The field of privacy has seen rapid advances in recent years because of the increases in the ability to store data. In particular, recent advances in the data mining field have lead to increased concerns about privacy. While the topic of privacy has been traditionally studied in the context of cryptography and information-hiding, recent emphasis on data mining has lead to renewed interest in the field. In this paper, the authors will introduce the topic of privacy-preserving data mining.