Dynamic k-Anonymity security protecting technique for restricting information mining

Abstract

Dynamic k-Anonymity is a security protecting technique for restricting exposure of private in
arrangement in information mining. The procedure of anonymizing a database table ordinarily includes summing up
table passages and, thusly, it causes loss of pertinent data. This motivates the scan for anonymization calculations that
accomplish the required level of anonymization while causing an insignificant loss of data. The issue of k-anonymization
with negligible loss of data is NP-hard. We introduce a viable estimation calculation that empowers tackling the kanonymization issue with an estimate certification of O(ln k).