[1] Samarati P, Sweeney L. Generalizing Data to Provide Anonymity When Disclosing Information (Abstract)
[C]. In: Proceedings of the 17th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems，Seattle, Washington, United States. New York: ACM Press,1998:188.

[2] Sweeney L. k-Anonymity: A Model for Protecting Privacy
[J]. International Journal of Uncertainty, Fuzziness and Knowledge-based Systems,2002,10(5):557-570.

[3] Sweeney L. Achieving k-Anonymity Privacy Protection Using Generalization and Suppression
[J]. International Journal of Uncertainty, Fuzziness and Knowledge-based Systems,2002,10(5): 571-588.

[4] Meyerson A, Williams R. On the Complexity of Optimal k-Anonymity
[C]. In: Proceedings of the 23rd ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems. New York: ACM Press, 2004:223-228.

[5] Aggarwal G, Feder T, Kenthapadi K, et al. Achieving Anonymity via Clustering
[C]. In: Proceedings of the 25th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems. New York: ACM Press, 2006:153-162.

[6] Iyengar V S. Transforming Data to Satisfy Privacy Constraints
[C]. In: Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM Press, 2002:279-288.

[7] Wang K, Yu P, Chakraborty S. Bottom-up Generalization: A Data Mining Solution to Privacy Protection
[C]. In: Proceedings of the 4th IEEE International Conference on Data Mining. Washington DC: IEEE Computer Society, 2004:249-256.

[8] Lefevre K, Dewittd J, Ramakrishnan R. Incognito: Efficient Full-Domain k-Anonymity
[C]. In: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data.New York: ACM Press, 2005:49-60.

[9] Fung B, Wang K, Yu P. Top-down Specialization for Information and Privacy Preservation
[C]. In: Proceedings of the 21st IEEE International Conference on Data Engineering. Washington DC: IEEE Computer Society, 2005:205-216.

[10] Bayardo R, Agrawal R. Data Privacy Through Optimal k-Anonymization
[C]. In: Proceedings of the 21st International Conference on Data Engineering. Los Alamitos: IEEE Computer Society, 2005:217-228.

[11] LeFevre K, DeWitt D J, Ramakrishnan R. Mondrian Multidimensional k-Anonymity
[C]. In: Proceedings of the 22nd International Conference on Data Engineering. Los Alamitos: IEEE Computer Society, 2006:25-36.

[12] 杨晓春,刘向宇,王斌,等. 支持多约束的K-匿名化方法
[J]. 软件学报,2006,17(5):1222-1231.

[13] Xu J, Wang W, Pei J, et al. Utility-based Anonymization Using Local Recoding
[C]. In: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM Press, 2006:785-790.

[14] Truta T, Vinay B. Privacy Protection: p-Sensitive k-Anonymity Property
[C]. In: Proceedings of the 22nd International Conference on Data Engineering Workshops. Washington DC: IEEE Computer Society, 2006:94-103.

[15] Wong R C, Li J Y, Fu A W, et al. (a, k)-Anonymity: An Enhanced k-Anonymity Model for Privacy-Preserving Data Publishing
[C]. In: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM Press, 2006:754-759.


[16] Machanavajjhala A, Gehrke J, Kifer D. l-Diversity: Privacy Beyond k-Anonymity
[J]. ACM Transactions on Knowledge Discovery from Data, 2007,1(1):24-35.

[17] Li N H, Li T C. t-Closeness: Privacy Beyond k-Anonymity and l-Diversity
[C]. In: Proceedings of IEEE 23rd International Conference on Data Engineering. Pisctaway, NJ: IEEE, 2007:106-115.

[18] Aggarwal G, Feder T, Kenthapadi T, et al. Achieving Anonymity via Clustering
[C]. In: Proceedings of the Symposium on Principles of Database Systems (PODS). New York: ACM Press, 2006:153-162.

[19] Xu J,Wang W, Pei J, et al. Utility-based Anonymization for Privacy Preservation with Less Information Loss
[J]. ACM SIGKDD Explorations Newsletter,2006,8(2):21-30.

[20] Byun J W, Kamra A, Bertino E, et al. Efficient k-Anonymization Using Clustering Techniques
[C]. In: Proceedings of the 12th International Conference on Database Systems for Advanced Applications，Bangkok, Thailand. Heidelberg Berlin：Springer-Verlag,2007:188-200.

[21] Lin J L, Wei M C. Genetic Algorithm-based Clustering Approach for k-Anonymization
[J]. Expert Systems with Applications, 2009,36(6):9784-9792.

[22] Lu L J, Ye X J. An Improved Weighted-Feature Clustering Algorithm for k-Anonymity
[C]. In: Proceedings of the 5th International Conference on Information Assurance and Security. Washington DC: IEEE Computer Society, 2009:415-419.

[23] 于娟,韩建民,郭腾芳，等. 基于聚类的高效k-匿名化算法
[J]. 计算机研究与发展, 2009,46(z):105-111.

[24] 王智慧,许俭,汪卫，等. 一种基于聚类的数据匿名方法
[J]. 软件学报, 2010,21(4):680-693.

[25] 周水庚,李丰,陶宇飞,等. 面向数据库应用的隐私保护研究综述
[J]. 计算机学报, 2009,32(5):847-861.