On Randomization, Public Information and the Curse of Dimensionality
- Charu C. Aggarwal
- 2007 IEEE 23rd International Conference on Data…
AbstractPrivacy is the main concerning in now a days. In this paper we concentrated on distance measures applied to ensure the privacy of the individual sensitive information.Protecting data privacy is an important problem in data distribution. Distance measure 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 distance measure techniques for privacy preserving. We discuss the distance measure models, the major implementation ways and the strategies of distance measure algorithms, and analyze their advantage and disadvantage. Then we give a simple review of the work accomplished. Finally, we conclude further research directions of distance measure techniques by analyzing the existing work.