Computer Science ›› 2016, Vol. 43 ›› Issue (12): 195-199.doi: 10.11896/j.issn.1002-137X.2016.12.035

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Sequential Pattern Mining Based on Privacy Preserving

FANG Wei-wei, XIE Wei, HUANG Hong-bo and XIA Hong-ke   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Privacy-preserving is one of the most important topics in data mining.Its’ main aim is realizing mining task in the context of uncovering original data information.In this paper,aiming to solve privacy-preserving sequential pattern mining problem, we proposed new concepts about item’s Boolean set relationship,and designed data perturbation method based on random set and random function,which can obtain the support of original sequential database.Theore-tical analysis and experiment results demonstrate that this method can achieve good performance in terms of privacy preserving,mining quality and efficiency.

Key words: Sequential pattern,Data mining,Privacy preserving,Data perturbation

[1] Agrawal R,Srikant R.Mining Sequential patterns[C]∥Proceeding of the 11th International Conference on Data Enginee-ring.Los Alamitos,CA:IEEE Computer Society Press,1995:3-14
[2] Srikant R,Agrawal R.Mining sequential patterns:Generaliza-tions and Performance Improvements[C]∥Proceeding of the 5th International Conference on Extending Database Technology.Berlin:Springer-Verlag.1996:3-17
[3] Han J,Pei J,et al.FreeSpan:Frequent Pattern-projected Sequ-ential Pattern Mining[C]∥Proceeding of the 6th International Conference on Knowledge Discovery and Data Mining.New York:ACM Press,2000:335-359
[4] Pei J,Han J,et al.PrefixSpan:Mining Sequential Patterns Effectively by Prefix Protected Pattern Growth[C]∥Proceeding of the 17th International Conference on Data Engineering.Los Alamitos,CA:IEEE Computer Society Press.2001:215-224
[5] Guralnik V,Garg N,Karypis G.Parallel Tree Projection Algorithm for Sequence Mining[C]∥LNCS2150.2001:310-320
[6] Agrawal R,Srikant R.Privacy-preserving data mining [C]∥Pro-ceedings of the 2000 ACM SIGMOD International Conference on Management of Data.Dallas,Texas,United States:ACM,2000:439-450
[7] Rizvi S J,Haritsa J R.Maintaining data privacy in associationrule mining[C]∥Proceedings of the 28th International Confe-rence on Very Large Databases (VLD).Hong Kong,China,2002:682-693
[8] Saygin Y,Verykios V S,Elmagarmid A K.Privacy preserving association rule mining[C]∥Proc.of the 12th International Workshop on Research Issues in Data Engineering (RIDE).San Jose,USA,2002:151-158
[9] Vaidya J.Clifton C1 Privacy preserving association rule mining in vertically partitioned data1[C]∥the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mi-ning.2002:639-644
[10] Wu Ying-jie,Tang Qing-ming,Ni Wei-wei,et al.Private Preserving Data Publishing Based on Clustering[J].Computer Research and Development,2013,50(3):578-593(in Chinese) 吴英杰,唐庆明,倪巍伟,等.基于聚类杂交的隐私保护轨迹数据发布算法[J].计算机研究与发展,2013,0(3):578-593
[11] Li Yang,Hao Zhi-feng.Private Preserving K-means Clustering Methods Research[J].Computer Science,2013,3(1):39-45(in Chinese) 李杨,郝志峰.差分隐私保护k-means聚类方法研究[J].计算机科学,2013,3(1):39-45
[12] Fang Wei-wei,Yang Bing-ru,Xia Hong-ke.Private Preserving Clustering Model Based on SMC[J].System Engineering and Electric Technology,2012,34(7):567-578(in Chinese) 方炜炜,杨炳儒,夏红科.基于SMC的隐私保护聚类模型[J].系统工程与电子技术,2012,34(7):567-578
[13] Xiong Ping,Zhu Tian-qing.One Private Preserving Algorithm Based on Decision Tree[J].Computer Application Research,2014,1(10):354-360(in Chinese) 熊平,朱天清.一种面向决策树构建的差分隐私保护算法[J].计算机应用研究,2014,31(10):354-360
[14] Zhang Cheng-xue.Private Preserving Algorithm Based on Data Victoria Distributian[J].Shandong Technology University Paper,2011,30(2):30-38(in Chinese) 张成学.数据垂直分布的线性规划的隐私保护算法[J].山东科技大学,2011,30(2):30-38

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