期刊名称：Lecture Notes in Engineering and Computer Science
印刷版ISSN：2078-0958
电子版ISSN：2078-0966
出版年度：2017
卷号：2227&2228
页码：466-472
出版社：Newswood and International Association of Engineers
摘要：In order to prevent data disclosure in the privacy of individuals, privacy protection technology continues to improve, the S - KACA algorithm can protect the sensitive privacy attributes and make the published data available, but it sets a privacy protection parameter when protecting sensitive privacy information, which results in the low efficiency of the algorithm and does not apply to the large - scale data set. In order to solve this problem, an algorithm called K - Prototypes - S - KACA is proposed, which combin es the e fficient K - Prototypes clustering algorithm with S - KACA algorithm. Firstly, the algorith m divides the microdata set into several slightly larger clusters by clustering algorithm K - Prototypes, and then using S - KACA algorithm anonymizes these microdat a set. Experiments show that the algorithm is similar to S - KACA algorithm in terms of privacy protection and data availability, but the efficiency of the algorithm is greatly improved.
