A Survey on Privacy Preservation in Data Publishing?

Privacy preservation is the most concentrated issue in data publishing, as the sensitive information should not be leaked. For this sake, several techniques such as generalization, bucketization are proposed, in order to deal with privacy preservation. However, generalization fails on high dimensional data because of dimensionality and it causes information loss due to uniform distribution. On the other hand, bucketization cannot achieve membership disclosure. All the above mentioned shortcomings are overcome by a technique named slicing. Slicing can handle high dimensional data too. It is proposed that slicing can be clubbed with the algorithm in order to increase the data utility and privacy.