A Taxonomy of Syntactic Privacy Notions for Continuous Data Publishing

Continuous data publishing aims to anonymise the next publication of changing microdata while preserving privacy. The microdata can change between publications via additions, deletions, insertions, and updates. There are numerous proposals for different database types, adversaries, attacks, and notions. However, many anonymization algorithms include notions of privacy and adversarial models that are specific to the context, with their own terminology and notation. Unfortunately, these proposals are difficult to generalize or translate them to other contexts complicating their understanding and comparison. To address these issues, we propose a taxonomy of anonymization technologies, compare existing solutions, and develop a unifying framework that not only harmonizes concepts and terminology but also notation and nomenclature. We analyze the current state of the art and recent advances in the literature. The analysis enables us to understand the significance and appropriateness of the various proposals in achieving privacy.