4] KACA algorithm to implement k-anonymity for quasi-identifier table.
The Multi Sensitive Bucketization K-Anonymity Clustering Attribute Hierarchy (MSB-KACA) algorithm  has been applied to the sliced data where the MSB is applied to the sensitive attribute in order to implement l-diversity and KACA is applied to the quasi identifier in order to implement k-anonymity.
The basic idea of KACA method which has been applied to the quasi identifier are to group the attributes based on the zip code and then generalize or suppress the value in order to provide privacy of an individual's sensitive information.
By applying MSB KACA algorithm, it satisfies the concept of l-diversity and k-Anonymity.
EMD, Earth Mover distance is calculated for the data set in which the privacy is preserved using MSB KACA algorithm.
Together with the World Bank and a multitude of other donors, the IMF demanded that Kenya "must" legalise the KACA
and also pass an "Ethics and Code of Conduct" bill that had been rejected by parliament last November, on the grounds that it was "poorly drafted" and also "breached the personal right to privacy" and the Economic Crimes Bill.