Abstract: Temporal data have importance in a variety of fields, such as biomedicine, geographical data processing, financial data forecasting and Internet site usage monitoring. Temporal data mining deals with the extracting of useful information from temporal data, where the definition of useful depends on the application. The most common type of temporal data is time series data, which consist of real values sampled at regular time intervals. Temporal Data Mining is a rapidly evolving area of research that is at the intersection of several disciplines, including statistics, temporal pattern recognition, temporal databases, optimization, and visualization, high performance computing, and parallel computing. This paper is first intended to serve as an overview of the temporal data mining and provide an algorithm to achieve privacy in temporal mining.