A novel algorithm of personalized-granular k-anonymity

In the existing anonymous privacy protection technology, there is a shortage of personalized privacy protection support for sensitive attributes before data publishing and sharing. In order to achieve more reasonable personalized privacy preservation and improve the precision of privacy preservation, this paper reviewed the latest researches in granular computing theory, rough set theory and k-anonymity theory, and presented a novel algorithm of personalized-granular k-anonymity based on the personalized decision degree of privacy preservation, in view of different personalized granularity decision selectivity of privacy preservation in E-business. It has been experimentally proved that the novel algorithm can achieve privacy preservation with more reasonable personalization, and its accuracy of privacy preservation is superior to p-sensitive k-anonymity algorithm.