期刊文献+

数据发布匿名技术进展 被引量:19

Advancement of anonymity technique for data publishing
在线阅读 下载PDF
导出
摘要 随着计算机技术和网络技术的快速发展,以数据挖掘与分析为目的的数据发布实现了信息的高度共享,但也因此造成数据中包含的大量敏感隐私信息的泄漏风险.匿名技术是解决数据发布中的隐私泄露问题的主要方法.首先简要介绍数据发布隐私保护中的数据匿名化处理场景;其次分别对处理单敏感、多敏感属性的静态数据发布、增量数据发布、数据流发布、轨迹数据发布的匿名模型进行归纳,总结匿名模型对不同的攻击形式如链接攻击、同质攻击、背景知识攻击等的抵御能力;接着分析比较了泛化、抑制、聚类、微聚集、分解、置换等匿名化方法;然后讨论了匿名技术在数据聚合、位置服务、社交网络等领域的发展;最后总结并指明下一步的研究方向. With the rapid development of computer and network technology, data publishing achieves well-sharing of information for the purpose of data mining and analyzing, whille it may cause the leakage risk of a great amount of sensitive privacy information in the data. Anonymity technology is the main method to realize privacy preservation in data publishing. The research progress of anonymity technology in data publishing was summed up. The scenario of data anonymization was introduced briefly. The anonymization models were summarized, which were respectively used to deal with static data publishing of single sensitive attribute and multidimensional ones, incremental data publishing, streaming data publishing and trajectory data publishing. The anonymization model abilities to resist linking attack, homogeneity attack and background knowledge attack were analyzed. The anonymization methods of generalization, suppression, clustering, microaggregation, anatomy and permutation were analyzed and compared. The applications of anonymity techniques for privacy preservation in the fields of data mashup, location based services and social network were discussed. The future research of anonymity technology for data publishing was proposed.
出处 《江苏大学学报(自然科学版)》 EI CAS CSCD 北大核心 2016年第5期562-571,共10页 Journal of Jiangsu University:Natural Science Edition
基金 国家自然科学基金资助项目(61472001) 江苏省重点研发计划项目(BE2015136) 镇江市工业支撑计划项目(GY2013030)
关键词 数据发布 隐私保护 匿名化 K-匿名 轨迹数据 data publishing privacy preserving anonymization k-anonymity trajectory data
作者简介 刘湘雯(197-),女,江苏宜兴人,讲师(Huxw@ujs.edu.cn),主要从事数据安全、隐私保护研究.王良民(1977-),男,安徽潜山人,教授,博士生导师(waglm@ujs.edu.cn),主要从事密码学与安全协议、物联网安全、大数据安全研究.
  • 相关文献

参考文献16

二级参考文献182

  • 1潘晓,肖珍,孟小峰.位置隐私研究综述[J].计算机科学与探索,2007,1(3):268-281. 被引量:65
  • 2杨晓春,刘向宇,王斌,于戈.支持多约束的K-匿名化方法[J].软件学报,2006,17(5):1222-1231. 被引量:60
  • 3王菁,张焕杰,杨寿保,高鹰.利用集合差异度实现基于内容聚类的P2P搜索模型[J].中国科学院研究生院学报,2007,24(2):241-247. 被引量:2
  • 4彭京,唐常杰,程温泉,石葆梅,乔少杰.一种基于层次距离计算的聚类算法[J].计算机学报,2007,30(5):786-795. 被引量:11
  • 5Mokbel M F. Privacy in location-based services: Start-of- the-art and research directions//Proceedings of the Interna tional Conference on Mobile Data Management ( MDM ' 07). Mannheim, Germany, 2007:228.
  • 6Solanas A, Domingo-Ferrer J, Martinez-Balleste A. Location privacy in location-based services: Beyond TTP-based schemes//Proceedings of the International Workshop on PiLBA. Malaga, Spain, 2008, 397.
  • 7Gruteser M, Grunwal D. Anonymous usage of location-based services through spatial and temporal cloaking//Proeeedings of the International Conference on Mobile Systems, Applications, and Services(MobiSys'03). New York, USA, 2003..163-168.
  • 8Gedik B, Liu L. A customizable k-anonymity model for protecting location privacy//Proceedings of the IEEE Interna tional Con{erence on Distributed Computing Systems (ICDCS'05). Columbus, Ohio, USA, 2005:620-629.
  • 9Mokbel M F, Chow C Y, Aref W G. The new casper: Query processing for location services without compromising privacy//Proceedings of the International Conference on Very Large Data Bases (VLDB'06). New York, USA, 2006: 763-774.
  • 10Xiao Z, Meng X, Xu J. Quality-aware privacy protection for location-based services//Proceedings of the International Conference on Database Systems for Advanced Applications (DASFAA'07). Bangkok, Thailand, 2007: 434 446.

共引文献199

同被引文献263

引证文献19

二级引证文献131

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部