基于位置混淆的轨迹隐私保护方法

doi:10.11959/j.issn.1000-436x.2018119

通信学报 ›› 2018, Vol. 39 ›› Issue (7): 81-91.doi: 10.11959/j.issn.1000-436x.2018119

基于位置混淆的轨迹隐私保护方法

张少波¹,刘琴²,王国军³()

¹ 湖南科技大学计算机科学与工程学院，湖南湘潭 411201
² 湖南大学信息科学与工程学院，湖南长沙 410082
³ 广州大学计算机科学与教育软件学院，广东广州 510006

修回日期:2018-05-11 出版日期:2018-07-01 发布日期:2018-08-08
作者简介:张少波（1979-），男，湖南邵东人，博士，湖南科技大学讲师，主要研究方向为移动社交网络、隐私保护、云计算安全、大数据安全和隐私等。|刘琴（1982-），女，湖南长沙人，博士，湖南大学副教授，主要研究方向为云计算安全、大数据安全与隐私保护等。|王国军（1970-），男，湖南长沙人，广州大学博士生导师、广东省珠江学者特聘教授，主要研究方向为信息安全、可信计算、大数据安全和隐私保护等。
基金资助:
国家自然科学基金资助项目(61632009);国家自然科学基金资助项目(61472451);国家自然科学基金资助项目(61402161);国家自然科学基金资助项目(61772194);湖南省自然科学基金资助项目(2016JJ3046);广东省自然科学基金资助项目(2017A030308006);广东省高等教育高层次人才基金资助项目(2016ZJ01)

Trajectory privacy protection method based on location obfuscation

Shaobo ZHANG¹,Qin LIU²,Guojun WANG³()

¹ School of Computer Science and Engineering,Hunan University of Science and Technology,Xiangtan 411201,China
² College of Computer Science and Electronic Engineering,Hunan University,Changsha 410082,China
³ School of Computer Science and Educational Software,Guangzhou University,Guangzhou 510006,China

Revised:2018-05-11 Online:2018-07-01 Published:2018-08-08
Supported by:
The National Natural Science Foundation of China(61632009);The National Natural Science Foundation of China(61472451);The National Natural Science Foundation of China(61402161);The National Natural Science Foundation of China(61772194);The Natural Science Foundation of Hunan Province(2016JJ3046);The Natural Science Foundation of Guangdong Province(2017A030308006);The High Level Talents Program of Higher Education in Guangdong Province(2016ZJ01)

摘要/Abstract

摘要：

在用户连续查询过程中，针对第三方匿名器结构中K匿名难以保证用户隐私的问题，提出一种基于位置混淆的轨迹隐私保护方法。首先通过位置预测机制和假位置选择机制获得(G-1)个查询混淆位置，然后将其与用户真实查询位置一起发送到不同匿名器形成匿名域后，再发送到LBS服务器进行查询，最后将获得的查询结果经不同匿名器返回给用户。该方法通过位置混淆来混淆用户的真实查询位置，使攻击者从单匿名器和LBS服务器不能推断出用户的真实轨迹，加强了对用户轨迹的隐私保护，也解决了单匿名器的性能瓶颈问题。安全分析表明了该方法的安全性，实验结果表明，该方法能减少用户与LBS服务器的交互次数以及单匿名器的开销。

关键词: 轨迹隐私, 位置混淆, 位置预测, 假位置, 匿名器

Abstract:

In the process of continuous queries,a method of trajectory privacy protection based on location obfuscation was proposed to solve the problem that K-anonymity was difficult to guarantee user privacy in third party architectrue.Firstly,the (G-1) query obfuscation locations through the location prediction was obtained and the dummy location selection mechanism,and then sent them together with the user’s real query location to different anonymizers to form cloaking regions and sent them to the LBS server for queries,and the query results were returned to the user by different anonymizers.In this method,the user’s real query location was confused by the location obfuscation,and the attacker couldn’t deduce the user’s trajectory from a single anonymizer or the LBS server.The method can enhance the privacy of the user’s trajectory and can effectively solve the performance bottleneck in the single anonymizer structure.Security analysis shows the security of the proposed approach,and experiments show this method can reduce the number of interactions between the user and the LBS server and the overhead of the single anonymizer.

Key words: trajectory privacy, location obfuscation, location prediction, dummy location, anonymizer

中图分类号:

TP393

张少波,刘琴,王国军. 基于位置混淆的轨迹隐私保护方法[J]. 通信学报, 2018, 39(7): 81-91.

Shaobo ZHANG,Qin LIU,Guojun WANG. Trajectory privacy protection method based on location obfuscation[J]. Journal on Communications, 2018, 39(7): 81-91.

图/表 11

图1

表1

TPLO方法中的符号定义及描述"

符号	描述
E、En	非对称和对称加密函数
k_i	用户生成的第i个随机密钥
Q	用户的查询内容
(x_i,y_i)	第i个查询位置坐标值
K	匿名度
G	用户每次查询包含的查询位置数目
g	用户轨迹上预测的查询位置数目
R	查询范围半径
CR _i	匿名域
Re _i	用户查询兴趣点的集合
$M S G_{A_{j}}^{U_{i}}$	用户第i个位置向第 j个匿名器发送的查询信息
$M S G_{S}^{A_{j}}$	第 j个匿名器转发查询信息给LBS服务器
$M S G_{A_{j}}^{S}$	LBS服务器返回结果给第 j个匿名器
$M S G_{U}^{A_{j}}$	第 j个匿名器转发查询结果给用户

表1

图2

图3

图4

表2

表3

图5

图6

图7

图8

参考文献 21

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参数	取值
用户数m/个	10 000
兴趣点数POI/个	10 000
匿名器数N/个	100
匿名度K/个	10~100
每次查询位置数G/个	10~100
查询半径R/km	0.5~1.5

连续查询次数	? =2	? =3	? =4	? =5	? =6	? =7	? =8	? =9	? =10
1	1	1	1	1	1	1	1	1	1
2	1	1	1	1	1	1	1	1	1
3	1	1	1	1	1	2	2	2	2
4	1	1	1	1	2	2	2	2	2
5	1	1	1	2	2	3	3	3	3
6	1	1	2	2	2	3	3	3	3
7	1	2	2	2	3	4	4	4	4
8	1	2	2	2	3	4	4	4	4
9	1	2	2	3	3	5	5	5	5
10	1	2	2	3	4	5	5	5	5

基于位置混淆的轨迹隐私保护方法

Trajectory privacy protection method based on location obfuscation

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