Research on K-Anonymity Algorithm in Privacy Protection

Nowadays, people pay great attention to the privacy protection, therefore the technology of anonymization has been widely used.However, most of current methods strictly depend on the predefined ordering relation on the generalization layer or attribute domain, making the anonymous result is a high degree of information loss, thereby reducing the availability of data.In order to solve the problem, we propose a K-Members Clustering Algorithm to reduce the information loss, and improve the performance of k-anonymity in privacy protection.