Implementation of Privacy Algorithm for Data Publishing

With numerous organizations collecting customer data there exists a possibility of data sharing for exploring interesting data about behavior of customers. This leads to identification of customers which can be treated as a privacy threat according to directives. These acts insist that anonymity should be guaranteed if the customers wish so. A customer data normally contains attributes like SSN name, age, postal code, date of birth and gender. This data enables identification of the individuals even though information like SSN and Name suppressed. This was first identified. The solution proposed k-anonymity property to be applied to the data before release. Subsequently several solutions were published. Most of them addressed issues related to preserving privacy of individuals related to a single organization. This paper discusses an approach to protect privacy when anonymized data of two or more organizations is integrated.