Jing Y,Chao W,Zhang J P.Micro-aggregation algorithm based on sensitive attribute entropy[J].Tien Tzu Hsueh Pao/Acta Electronica Sinica,2014,42(7):1327-1337.
[2]
Cheng L,Cheng S,Jiang F.ADKAM:A-diversity Kanonymity model via microaggregation[C]//Information Security Practice and Experience,2015:533-547.
[3]
Sun Xiaoxun.A family of enhanced(L,α)-diversity models for privacy preserving data publishing[J].Future Generation Computer Systems,2011,27(3):348-356.
[4]
Soria-Comas J,Domingo-Ferrer J.Probabilistic K-anonymity through microaggregation and data swapping[C]//IEEE International Conference on Fuzzy Systems,2012:1-8.
[5]
Xu X,Numao M.An efficient generalized clustering method for achieving K-anonymization[C]//International Symposium on Computing&NETWORKING,IEEE,2015:499-502.
[6]
Aghdamm M R S,Sonehara N.Efficient local recoding anonymization for datasets without attribute hierarchical structure[C]//International Conference on Cyber Security,2013.
[7]
Yu L,Yang Q.An efficient local-recoding K-anonymization algorithm based on clusterin[M].Transactions on Edutainment XI,2015.
[8]
唐印浒,钟诚.基于变长聚类的多敏感属性概率K-匿名算法[J].计算机工程与设计,2014,(8):2660-2665.Tang Yinhu,Zhong Cheng.K-anonymity algorithm of multi-sensitive attribute probabilistic based on variablelength clustering[J].Computer Engineering and Design,2014,(8):2660-2665.
[9]
Sharma V.Methods for privacy protection using K-anonymity[C]//Optimization,Reliabilty,and Information Technology(ICROIT),2014International Conference on,IEEE,2014:149-152.
[10]
Hajkacem M A B,N’Cir C E B,Essoussi N.Parallel K-prototypes for clustering big data[C]//Computational Collective Intelligence.Springer International Publishing,2015.