基于贝叶斯网络的路网位置匿名区域估计

doi:10.13229/j.cnki.jdxbgxb201402028

吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (2): 454-458.doi: 10.13229/j.cnki.jdxbgxb201402028

基于贝叶斯网络的路网位置匿名区域估计

蔡朝晖^1,2, 张健沛¹, 杨静¹

1. 哈尔滨工程大学计算机科学与技术学院, 哈尔滨 150001;
2. 大庆师范学院计算机科学与信息技术学院, 黑龙江大庆 163712

收稿日期:2013-03-20 出版日期:2014-02-01 发布日期:2014-02-01
通讯作者: 张健沛（1956- ），男，教授，博士生导师.研究方向：数据挖掘，社会网络.E-mail：zhangjianpei@hrbeu.edu.cn E-mail:zhangjianpei@hrbeu.edu.cn
作者简介:蔡朝晖（1968- ），女，副教授，博士研究生.研究方向：数据挖掘，隐私保护.E-mail：dq_caizhaohui@163.com
基金资助:
国家自然科学基金项目（61073041，61073043，61202274，61370083）；高等学校博士学科点专项科研基金项目（20112304110011，20122304110012）.

Anonymous area estimation method of path data based on Bayesian network

CAI Zhao-hui^1,2, ZHANG Jian-pei¹, YANG Jing¹

1. College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China;
2. College of Computer Science and Information Technology, Daqing Normal University, Daqing 163712, China

Received:2013-03-20 Online:2014-02-01 Published:2014-02-01

摘要/Abstract

摘要：

基于道路网络模型，结合路网数据，通过贝叶斯网络证据相关推理的概率计算，并利用最大似然理论确定最小匿名区域估计，提出了一种基于贝叶斯网络的路网位置匿名区域估计方法。仿真实验结果表明，该方法可为基于位置服务中的隐私保护提供适时、适度的匿名区域建议，提高了匿名时间和匿名精度，从而从整体上提高服务质量。该方法还可以利用已知路网数据，进行客观推理，为个性化匿名需求提供合理建议，解决了移动用户查询中较多的不确定性问题。

关键词: 人工智能, 位置隐私保护, 查询敏感度, 贝叶斯网络推理, 个性化隐私需求, 最小匿名区域估计

Abstract:

In this paper, an anonymous area estimation method of path data based on Bayesian network is proposed. This method is based on the path network model, combined with road network data, and the maximum likelihood theory is used to determine the minimum anonymous region estimation. Simulation results show that the proposed anonymous area estimation method can provide timely and proper anonymous region suggestion for the privacy protection based on the position service, thus, the service quality in terms of anonymous time and precision. The proposed method also makes use of the known path data for objective reasoning and providing reasonable suggestion to individuation anonymous demands, which solves the major uncertainty problems in the mobile user queries.

Key words: artificial intelligence, location privacy protection, query sensitivity, Bayesian network, personal privacy requirements, anonymous area estimation

中图分类号:

TP309

蔡朝晖, 张健沛, 杨静. 基于贝叶斯网络的路网位置匿名区域估计[J]. 吉林大学学报(工学版), 2014, 44(2): 454-458.

CAI Zhao-hui, ZHANG Jian-pei, YANG Jing. Anonymous area estimation method of path data based on Bayesian network[J]. 吉林大学学报(工学版), 2014, 44(2): 454-458.

参考文献

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基于贝叶斯网络的路网位置匿名区域估计

Anonymous area estimation method of path data based on Bayesian network

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