《计算机应用研究》|Application Research of Computers

隐私保护数据挖掘研究进展

Research advances on privacy-preserving data mining

免费全文下载 (已被下载 次)  
获取PDF全文
作者 张海涛,黄慧慧,徐亮,高莎莎
机构 南京邮电大学 地理与生物信息学院,南京 210003
统计 摘要被查看 次,已被下载
文章编号 1001-3695(2013)12-3529-07
DOI 10.3969/j.issn.1001-3695.2013.12.003
摘要 近年来隐私保护数据挖掘已经成为数据挖掘的研究热点, 并取得了丰富的研究成果。但是, 随着移动通信、嵌入式、定位等技术的发展与物联网、位置服务、基于位置的社交网络等应用的出现, 具有个人隐私的信息内容更加丰富, 利用数据挖掘工具对数据进行综合分析更容易侵犯个人隐私。针对新的应用需求, 对隐私保护数据挖掘方法进行深入研究具有重要的现实意义。在分析现有的隐私保护数据挖掘方法分类与技术特点的基础上, 提出现有方法并应用于新型分布式系统架构应用系统、高维数据及时空数据等领域存在的挑战性问题, 并指出了今后研究的方向。
关键词 隐私保护数据挖掘;新型分布式系统;高维数据;时空数据
基金项目 国家自然科学基金资助项目(41201465)
江苏省自然科学基金资助项目(BK2012439)
2010年江苏政府留学奖学金资助项目
本文URL http://www.arocmag.com/article/01-2013-12-003.html
英文标题 Research advances on privacy-preserving data mining
作者英文名 ZHANG Hai-tao, HUANG Hui-hui, XU Liang, GAO Sha-sha
机构英文名 College of Geographic & Biologic Information, Nanjing University of Posts & Telecommunications, Nanjing 210003, China
英文摘要 In recent years, the privacy-preserving data mining has become a hotspot in data mining. However, with the development of technologies (mobile communication, embedded and positioning technologies, etc), the emerging applications(the Internet of things, location-based services, social network based on location, etc) result in accumulation of abundant personal privacy information, which will easily lead to the violence of personal privacy. Therefore, it is significant to study the privacy-preserving data mining methods to meet the demands of new appplications. In view of the analyzing the characteristics and catalogs of existing privacy-preserving data mining methods, this paper proposed their challenges from the field of new distributed system, high dimensional data and spatio-temporal data, etc, as well as indicatef the future research directions.
英文关键词 privacy-preserving data mining; new distributed system; high dimensional data; spatio-tempral data
参考文献 查看稿件参考文献
  [1] HAN Jia-wei, KAMBER M. Data mining:concepts and techniques[M] . 2nd ed. San Francisco:Morgan Kaufmann Publishers, 2006.
[2] CLIFTON C, KANTARCIOUGLU M, VAIDYA J. Defining privacy for data mining[C] //Proc of National Science Foundation Workshop on Next Generation Data Mining. 2002:126-133.
[3] VERYKIOS V S, BERTINO E, FOVINO I N, et al. State-of-the-art in privacy persevering data mining[J] . ACM SIGMOD Record, 2004, 33(1):50-57.
[4] 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):847-858.
[5] BONCHI F, FERRARI E. Privacy-aware knowledge discovery novel application and new techniques[M] . Boca Raton:CRC Press, 2011.
[6] YAO A C. How to generate and exchange secrets[C] // Proc of the 27th IEEE Symposium on Foundations of Computer Science. Washington DC:IEEE Computer Society, 1986:162-167.
[7] CLIFTON C, KANTARCIOGLU M, VAIDYA J, et al. Tools for privacy preserving distributed data mining[J] . ACM SIGKDD Explorations, 2002, 4(2):28-34.
[8] 刘英华, 杨炳儒, 马楠, 等. 分布式隐私保护数据挖掘研究[J] . 计算机应用研究, 2011, 28(10):3606-3610.
[9] KANTARCIOGLU M, CLIFTON C. Privacy-preserving distributed mining of association rules on horizontally partitioned data[J] . IEEE Trans on Knowledge and Data Engineering, 2004, 16(9):1026-1037.
[10] CHEUNG D W, HAN Jia-wei, NG V T, et al. A fast distributed algorithm for mining association rules[C] //Proc of the 4th International Conference on Parallel and Distributed Information Systems. 1996:31-44.
[11] VAIDYA J, CLIFTON C. Privacy preserving association rules mining in vertically partitioned data[C] //Proc of the 8th ACM SIGMOD International Conference on Knowledge Discovery and Data Mining. New York:ACM Press, 2002:639-644.
[12] 汪晓刚, 惠蕙, 孙志挥. 基于共享的隐私保护关联规则挖掘[J] . 软件导刊, 2009, 9(8):150-153.
[13] VAIDYA J, CLIFTON C. Privacy-preserving K-means clustering over vertically partitioned data[C] //Proc of the 9th ACM SIGMOD International Conference on Knowledge Discovery and Data Mining. New York:ACM Press, 2003:206-215.
[14] JAGANNATHAN G, WRIGHT R N. Privacy preserving distributed K-means clustering over arbitrarily partitioned data[C] //Proc of the 11th ACM SIGMOD International Conference on Knowledge Discovery and Data Mining. New York:ACM Press, 2005:593-599.
[15] DU Wen-liang, ZHAN Zhi-jun. Building decision tree classifier on private data[C] //Proc of IEEE International Conference on Privacy, Security and Data Mining. 2002:1-8.
[16] XIAO Ming-jun, HUANG Liu-sheng, LUO Yong-long, et al. Privacy preserving ID3 algorithm over horizontally partitioned data[C] //Proc of the 6th International Conference on Parallel and Distributed Computing, Applications and Technologies. 2005:239-243.
[17] XIAO Ming-jun, HAN Kai, HUANG Liu-sheng, et al. Privacy preserving C4. 5 algorithm over horizontally partitioned data[C] // Proc of the 5th International Conference on Grid and Cooperative Computing. Washington DC:IEEE Computer Society, 2006:78-85.
[18] 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. 2002:151-158.
[19] AGRAWAL R, SRIKANT R. Privacy preserving data mining[J] . ACM SIGMOD Record, 2000, 29(2):439-450.
[20] AGGARWAL C C, YU P S. Privacy-preserving data mining:models and algorithms [M] . New York:Springer-Verlag, 2008.
[21] 魏晓辉. 敏感规则隐藏算法的研究[D] . 哈尔滨:哈尔滨工程大学, 2010.
[22] ZHANG Nan, ZHAO Wei. Distributed privacy preserving information sharing[C] //Proc of the 31st International Conference on Very Large Data Bases (VLDB). 2005:889-900.
[23] MACHANAVAJJHALA A, GEHRKE J, KIFER D, et al. l-diversity:privacy beyond k-anonymity[C] //Proc of the 22nd International Conference on Data Engineering. 2006:24-35.
[24] AGRAWAL D, AGGARWAL C C. On the design and quantification of privacy preserving data mining algorithms[C] //Proc of the 20th ACM Symposium on Principles of Database Systems. New York:ACM Press, 2001:247- 255.
[25] AGGARWAL C C, YU P S. A condensation approach to privacy preserving data mining[C] //Proc of the 9th International Conference on Extending Database Technology. Berlin:Springer-Verlag, 2004:183-199.
[26] SIMPSONAND J A, WEINER E S C. Oxford English dictionary[M] . 2nd ed. [S. l. ] :Clarendon Press, 1989.
[27] PFITZMANN A, KOEHNTOPP M. Anonymity, unobservability, and pseudonymity:a proposal for terminology[C] //Proc of International Workshop on Design Issues in Anonymity and Unobservability. Berlin:Springer-Verlag, 2000:1-9.
[28] SWEENEY L. k-anonymity:a model for protecting privacy[J] . International Journal on Uncertainty, Fuzziness and Knowledge-based Systems, 2002, 10(5):557-570.
[29] LI Ning-hui, LI Tian-cheng, VENKATA-SUBRAMANIAN S. t-closeness:privacy beyond k-anonymity and l-diversity [C] //Proc of the 23rd International Conference on Data Engineering. New York:ACM Press, 2007:106-115.
[30] SWEENEY L. Achieving k-anonymity privacy protection using generalization and suppression[J] . International Journal on Uncertainty, 2002, 10(5):571-588.
[31] LeFEVRE K, DeWITT D J, RAMAKRISHNAN R. Incognito:efficient full domain k-anonymity[C] //Proc of ACM SIGMOD Conference on Management of Data. New York:ACM Press, 2005:49-60.
[32] FUNG B C M, WANG Ke, YU P S. Anonymizing classification data for privacy preservation[J] . IEEE Trans on Knowledge and Data Engineering, 2007, 19(5):711-725.
[33] WANG Ke, YU P S, CHAKRABORTY S. Bottom-up generalization:A data mining solution to privacy protection[C] //Proc of the 4th IEEE International Conference on Data Mining. Washington DC:IEEE Computer Society, 2004:249-256.
[34] 钱萍, 吴蒙. 物联网隐私保护研究与方法综述[J] . 计算机应用研究, 2013, 30(1):13-20.
[35] 贾金营, 张凤荔. 位置隐私保护技术综述[J] . 计算机应用研究, 2013, 30(3):641-646.
[36] 谈嵘, 顾君忠, 林欣, 等. 基于用户隐私保护的区域多对象聚集问题[J] . 计算机应用, 2011, 31(9):2389-2394.
[37] 杨煜尧, 赵方, 罗海勇, 等. 一种基于地理位置信息的移动互联网社交模型[J] . 计算机研究与发展, 2011, 48(S1):307-313.
[38] LI Na, ZHANG Nan, DAS S K, et al. Privacy preservation in wireless sensor networks:a state-of-the-art survey[J] . Ad hoc Networks, 2009, 7(8):1501-1514.
[39] CHOW C Y, MOKBEL M F, LIU Xuan. A peer-to-peer spatial cloaking algorithm for anonymous location-based services[C] //Pro of the 14th ACM International Symposium on Advances in Geographic Information Systems. New York:ACM Press, 2006:171-178.
[40] 孟小峰, 慈祥. 大数据管理:概念、技术与挑战[J] . 计算机研究与发展, 2013, 50(1):146-169.
[41] TERROVITIS M, MAMOULIS N, KALNIS P. Privacy preservation in the Publicatin of spare multidimensional data[M] . London:Taylor and Francis Group, 2011:35-56.
[42] NERGIZ M E, CLIFTON C, ERGIZ A E. Multirelational k-anonymity[C] //Proc of the 23rd IEEE International Conferenc on Data Engineering. 2007:1417-1421.
[43] GHINITA G, TAO Yu-fei, KALNIS P. On the anonymization of spare high-dimensional data[C] //Proc of the 24th International Conference on Data Engineering. 2008:715-724.
[44] ALI S, TORABI T, ALI H. Location aware business process deployment[C] //Proc of International Conference on Computational Science and Its Applications. Berlin:Springer-Verlag, 2006:217-225.
[45] BALDAUF M, DUSTDAR S, ROSENBERG F. A survey on context-aware systems[J] . International Journal of Ad hoc Ubiquitous Computing, 2007, 2(4):263-277.
[46] 赵文斌, 张登荣. 移动计算环境中的地理信息系统[J] . 地理与地理信息科学, 2003, 19(2):19-23.
[47] 张海涛, 闾国年, 张书亮, 等. 移动GIS中GML数据压缩技术研究[J] . 地理与地理信息科学, 2008, 24(5):21-24.
[48] 彭志宇, 李善平. 移动环境下LBS位置隐私保护[J] . 电子与信息学报, 2011, 33(5):1211-1216.
[49] KULIK L. Privacy for real-time location-based services[J] . SIGSPATIAL Special, 2009, 1(2):9-14.
[50] HOH B, GRUTESER M, XIONG Hui, et al. Enhancing security and privacy in traffic-monitoring systems[J] . IEEE Pervasive Computing, 2006, 5(4):38-46.
[51] KIDO H, YANAGISAWA Y, SATOH T. Protection of location privacy using dummies for location-based services[C] //Proc of the 21st International Data Engineering Workshops. Washington DC:IEEE Computer Society, 2005.
[52] UM J H, KIM H D, CHANG J W. An advanced cloaking algorithm using hilbert curves for anonymous location based service[C] //Proc of the 2nd International Conference on Social Computing. Washington DC:IEEE Computer Society, 2010:1093-1098.
[53] SHANG Ning, GHINITA G, ZHOU Yong-bin, et al. Controlling data disclosure in computational PIR protocols[C] //Proc of the 5th ACM Symposium on Information, Computer and Communications Security, 2010:310-313.
[54] GRUTESER M, GRUNWALD D. Anonymous usage of location-based services trough spatial and tmporal cloaking[C] //Proc of the 1st International Conference on Mobile Systems, Applications and Sevices. New York:ACM Press, 2003:31-42.
[55] KRUMM J. A survey of computational location privacy[J] . Personal and Ubiquitous Computing, 2009, 13(6):391-399.
[56] GEDIK B, LIU Ling. Location pivacy in mobile systems:a personalized anonymization model[C] //Proc of the 25th International Conference on Distributed Computing Systems. Washington DC:IEEE Computer Society, 2005:620-629.
[57] XU T, CAI Ying. Feeling-based location privacy protection for location-based services[C] //Proc of the 16th ACM Conference on Computer and Communications Security. New York:ACM Pres, 2009:348-357.
[58] CHOW C Y, MOKBEL M F, AREF W G. Query processing for location services without compromising privacy[J] . ACM Trans on Database Systems, 2009, 34(4):1-45.
[59] KU W S, ZIMMERMANN R, PENG W C, et al. Privacy protected query processing on spatial networks[C] //Proc of the 23rd International Data Engineering Workshops. Washington DC:IEEE Computer Society, 2007:215-220.
[60] CHOW C Y, MOKBEL M F. Enabling private continuous queries for revealed user locations[C] //Proc of the 10th International Conference on Advances in Spatial and Temporal Databases. Berlin:Springer-Verlag, 2007:258-275.
[61] 林欣, 李善平, 杨朝晖. LBS中连续查询攻击算法及匿名性度量[J] . 软件学报, 2009, 20(4):1058-1068.
[62] PAN Xiao, MENG Xiao-feng, XU Jian-liang. Distortion-based anony-mity for continuous queries in location-based mobile services[C] //Proc of the 17th ACM International Conference on Advances in Geographic Information Systems. New York:ACM Press, 2009:256-265.
[63] 刘大有, 陈慧灵, 齐红, 等. 时空数据挖掘研究进展[J] . 计算机研究与发展, 2013, 50(2):225-239.
[64] 李军怀, 高苗, 陈晓明, 等. 时空特性约束下的数据挖掘隐私保护方法[J] . 计算机工程与应用, 2008, 44(9):139-142.
收稿日期
修回日期
页码 3529-3535
中图分类号 TP208
文献标志码 A