A New Privacy Preserving Measure: p-Sensitive, t-Closeness

Preserving a sensitive data has become a great challenge in the area of research under data privacy. There are popular approaches such as k-anonymity, t-closeness [1] and l-diversity which are effective measures for preserving privacy. These techniques lead to solving many of the privacy issues. But all these measures suffer from one or the other types of attacks. To minimize these attacks, a new measure called p-sensitive, t-closeness is introduced. This measure will preserve the sensitive data by distributing different values of sensitive attribute according to t-closeness approach by introducing p-sensitivity, by minimizing attacks and improving the efficiency and utility of the data. This technique is termed as p-sensitive, t-closeness which satisfy p-sensitivity and t-closeness for a table by relaxing the threshold value t, so that; it will satisfy the p sensitivity to overcome many of limitations of previous approaches.