Survey of Anonymity Techniques for Privacy Preserving

The advancement of information technologies has enabled various organizations (e.g., census agencies, hospitals) to collect large volumes of sensitive personal data (e.g., census data, medical records). Data in its original form, however, typically contains sensitive information about individuals, and publishing such data will violate individual privacy. Protecting data privacy is an important problem in micro data distribution. Recently, there are various methods and techniques which have been created for providing privacy to the process of data mining. Anonymity techniques typically aim to protect individual privacy, with minimal impact on the quality of the released data. In this paper we provide an overview of anonymity techniques for privacy preserving. We discuss the anonymity models, the major implementation ways and the strategies of anonymity algorithms, and analyze their advantage and disadvantage. Then we give a simple review of the work accomplished. Finally, we conclude further research directions of anonymity techniques by analyzing the existing work.