The short course will introduce basic and advanced concepts of statistical disclosure control, privacy and confidentiality. The topics covered include: introduction to statistical disclosure control, disclosure risk scenarios and types of disclosure risks; measuring disclosure risk for traditional outputs: microdata and tabular data; common statistical disclosure control methods and their impact on data quality and utility. In addition, we introduce a new definition for confidentiality protection called differential privacy which was developed by computer scientists. Differential privacy is a mathematical rigorous definition of a perturbation mechanism that provides formal and quantifiable guarantees of confidentiality. We discuss how differential privacy can be used in the statistical disclosure control tool-kit at statistical agencies as they move towards more advanced, open and flexible modes of data dissemination.