International Journal of Computer & Organization Trends(IJCOT)
Today, most enterprises are actively collecting and storing data in large databases. Many of them have recognized the potential value of these data as an information source for making business decisions. Privacy-Preserving Data Publishing (PPDP) provides methods and tools for publishing useful information while preserving data privacy. In this paper, a brief yet systematic review of several anonymization techniques such as generalization and bucketization, have been designed for privacy preserving micro data publishing. Recent paper has shown that generalization loses considerable amount of information, especially for high-dimensional data.