K Anonymization

K Anonymity Overview

K anonymization is privacy preserving algorithm.

Objective

• k-anonymity objective is to make it difficult to identify individuals in a dataset.

• It ensure there are at least K individuals (or at least k-1 other similar records)

Steps to achieve K Anonymity

• Select value of K

• To achieve k-anonymity, a dataset is first divided into equivalence classes. An equivalence class is a group of records that are indistinguishable from each other.

• If there are less than K record in equivalence class, then data is purturb in such a manner to make them equal. To purturb the data one has to use approaches to generalize data or suppress sensitive info.