Data Slicing Technique to Privacy Preserving and Data Publishing
Many techniques have been designed for privacy preserving and micro data publishing, such as generalization and bucketization. Several works showed that generalization loses some amount of information especially for high dimensional data. So it's not efficient for high dimensional data. In case of Bucketization, it does not prevents membership disclosure and also does not applicable for data that do not have a clear separation between Quasi-identifying attributes and sensitive attributes. In this paper, the authors presenting an innovative technique called data slicing which partitions the data.