A Brief Survey on Anonymization Techniques for Privacy Preserving Publishing of Social Network Data
Nowadays, partly driven by many Web 2.0 applications, more and more social network data has been made publicly available and analyzed in one way or another. Privacy preserving publishing of social network data becomes a more and more important concern. In this paper, the authors present a brief yet systematic review of the existing anonymization techniques for privacy preserving publishing of social network data. They identify the new challenges in privacy preserving publishing of social network data comparing to the extensively studied relational case, and examine the possible problem formulation in three important dimensions: privacy, background knowledge and data utility.