Privacy compromises are inherent Data Mining due to the exploration process that looks for novel patterns which might reveal individual information. With the new privacy laws, the need to address privacy concerns in Data Mining has pushed this field to be at the forefront of research.

This talk attempts to cover the various techniques that were proposed to prevent compromizing privacy when carrying out data mining exercises. While these techniques have no standard definition of privacy, they do solve some part of the puzzle. We will highlight the differences between those techniques as well as the challenges that are yet to be addressed including the quantification of privacy.