Efficient Approach for Privacy Preserving Microdata Publishing Using Slicing
Many agencies and organizations are willing to release the data they collected to other parties for research and the formulation of public policies. Data often contains personally identifiable information and therefore releasing such data may result in privacy breaches. Several anonymization techniques, like generalization and Bucketization are designed for privacy preserving microdata publishing. Generalization loses considerable amount of information especially for high dimensional data. Bucketization does not prevent membership disclosure and does not apply for data that do not have a clear separation between quasi-identifying attributes and sensitive attributes.