Publishing data for analysis from a microdata table containing sensitive attributes, while maintaining individual privacy, is a problem of increasing significance today. The k-anonymity model was proposed for privacy preserving data publication. While focusing on identity disclosure, k-anonymity model fails to protect attribute disclosure to some extent. Many efforts are made to enhance the kan...

-Knowledge discovery is the most discussed topic now a day. Data which is collected from various resources are processed through various stages and the output of this process is the knowledge which is previously hidden. Basically data mining is a technique whose outputs are previously unknown and potentially useful information from data. There are several challenges of data mining are scalabili...

The emerging public awareness and government regulations of data privacy motivate new paradigms collecting analyzing that are transparent acceptable to owners. We present a concept corresponding formats, mechanisms, theories for privatizing during collection. privacy, named Interval Privacy, enforces the raw conditional distribution on privatized be same as its unconditional over nontrivial sup...

The vast amount of data being collected about individuals has brought new challenges in protecting their privacy when this data is disseminated. As a result, Privacy-Preserving Data Publishing has become an active research area, in which multiple anonymization algorithms have been proposed. However, given the large number of algorithms available and limited information regarding their performan...

Data mining is the process of extracting interesting patterns or knowledge from huge amount of data. In recent years, there has been a tremendous growth in the amount of personal data that can be collected and analyzed by the organizations. Organizations such as credit card companies, real estate companies and hospitals collect and hold large volumes of data for their research purposes. E. g. N...

Privacy-preserving data publication for data mining is to protect sensitive information of individuals in published data while the distortion to the data is minimized. Recently, it is shown that (α, k)anonymity is a feasible technique when we are given some sensitive attribute(s) and quasi-identifier attributes. In previous work, generalization of the given data table has been used for the anon...