Survey of Anonymity Techniques for Privacy Preserving
Luo Yongcheng, Jiajin Le, Jian Wang · 2011
Protecting data privacy is an important problem in microdata distribution. Anonymity techniques typically aim to protect individual privacy, with minimal impact on the quality of the released data. Recently, a few of models are introduced to ensure the privacy protecting and/or to reduce the information loss as much as possible. That is, they further improve the flexibility of the anonymous strategy to make it more close to reality, and then to meet the diverse needs of the people. Various proposals and algorithms have been designed for them at the same time. 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.