Efficient Approach for Anonymizing Tree Structured Dataset using Improved Greedy Search Algorithm

In companies and organizations collection of personal information is must. Hence this information collection is increasing day by day. This imposes the serious problem of maintaining the privacy of personal information. Data anonymization techniques presented recently in order to provide security to personal data of users. However such methods suffered from various limitations. Below four are recent research problems in this domain to achieve a) in many practical cases there are strict utility requirements that cannot be met when more powerful guaranties are applied, b) there is often inability to characterize attributes as sensitive or non sensitive, c) the privacy protection law in most countries usually focuses on identity, and d) recent methods uses the greedy algorithm for achieving anonymization large scale tree structured dataset, but greedy algorithm are having limitations.