Abstract
Privacy preserving data publishing (PPDP) methods a new class of privacy preserving data mining (PPDM) technology, has been developed by the research community working on security and knowledge discovery. It is common to share data between two organizations in many application areas. When data are to be shared between parties, there could be some sensitive patterns which should not be disclosed to the other parties. These methods aims to keep the underlying data useful based on privacy preservation “utility based method based on privacy preservation, and created tremendous opportunities for knowledge- and information-based decision making. Recently, PPDP has received considerable attention in research communities, and many approaches have been proposed for different data publishing scenarios. In this survey, we will systematically summarize and evaluate different approaches to PPDP, study the challenges in practical data publishing, clarify the differences and requirements that distinguish PPDP from other related problems, and propose future research directions.
Key words: Privacy preserving, privacy preserving data publishing, privacy preserving data mining, republishing, security, privacy, decision making, knowledge.
