A Survey on Privacy Measurement and Enhancement Models

Census data and medical data are referred as micro data. Data publish schemes are used to provide private data for analysis. Privacy preservation is used to protect private data values. Anonymity is considered in the privacy preservation process. Individual identity and private data values are protected with privacy preservation models. Sensitive attribute values are hided in the privacy preservation process. Statistical and Anonymization techniques are used for privacy preservation. Generalization and suppression protocols are used for the privacy. The privacy preservation process is applied on data and information in various types of applications. The survey is conducted on five different categories. They are Privacy for Personalized Mobile Applications, Privacy using Post Randomization via Information Theory, Utility-Privacy Tradeoff in Databases, Distance-Aware Privacy-Preserving Record Linkage and Cross-Bucket Generalization for Information Privacy. Privacy measurement models are applied to guarantee the privacy for user required levels. Data publishing methods are build with privacy measurement and enhancement models.