English

Hatem Rashid Asmaa,Binti Mohd Yasin Norizan

doi:10.5897/ijps11.1795

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.

Highlights

The development of IT and the collection of electronic information by data owners, such as governments, corporations, and individuals, have resulted in higher instances of data sharing
From the findings of the literatures above, there were several gaps in the privacy preserving subject, in the form of: (a) when data are to be shared between parties, there could be some sensitive patterns which should not be disclosed to the other parties’
Many methods have been proposed for privacy preserving in various fields

Summary

INTRODUCTION

The development of IT and the collection of electronic information by data owners, such as governments, corporations, and individuals, have resulted in higher instances of data sharing. PPDP has received considerable attention in research communities, and many approaches have been proposed for different data publishing scenarios (Gkoulalas-Divanis and Loukides, 2011). A task of the utmost importance is to develop methods and tools for publishing data in a more hostile environment, so that the published data remains practically useful while individual privacy is preserved (Fung et al, 2010). PPDP provides methods and tools for publishing useful information while preserving data privacy (Chen et al., 2012; Fung et al, 2010). Algorithms a new class of data mining methods, has been developed by the research community working on security and knowledge discovery (Bertino et al, 2005a; Fung et al, 2010)

Aim

RESULTS AND DISCUSSION

CONCLUSION