Enhanced Slicing+: A New Privacy Preserving Micro-data Publishing Technique

Abstract

According to studies, frequent and easily availability of data has made privacy preserving micro-data publishing a major issue. Any record in its native form is considered sensitive. These records must be kept secure from the threat as if the records are made freely available there are chances of privacy breach. The term micro-data is defined as data which contains complete information of an entity such as name, gender, salary, address etc. In this paper, a new technique is proposed i.e. Enhanced Slicing+ which ensures the privacy of data of an individual and reduces the risk of identification. In this paper concept of l-diversity and k-anonymity are used in order to achieve this. A privacy preserving technique is considered essential because it maintains the trade-off between utility and as well as privacy of individual’s records. The proposed technique is found to be less reliable to attack and preserves the privacy of an individual and it also contribute towards preserving privacy of records/data having various sensitive attributes, lesser information loss and better utility of data.