基于博弈分析的众包交通监测隐私保护机制

何云华; 孙利民; 杨卫东; 李红

doi:10.11999/JEIT150721

基于博弈分析的众包交通监测隐私保护机制

doi: 10.11999/JEIT150721

基金项目:

国家自然科学基金(61472418, 61202099)，中国科学院先导专项基金(XDA06040100)

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- 文章访问数: 1205
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- 被引次数: 0
出版历程
- 收稿日期: 2015-06-15
- 修回日期: 2015-09-17
- 刊出日期: 2016-02-19

Enhancing Privacy Preserving for Crowdsourced Monitoring A Game Theoretic Analysis Based Approach

Funds:

The National Natural Science Foundation of China (61472418, 61202099), The Strategic Priority Research Program of the Chinese Academy of Sciences (XDA06040100)

摘要

摘要: 众包交通监测利用移动终端上传的GPS位置信息实时感知交通状况，具有广阔的应用前景。然而，上传的GPS信息会泄露用户隐私。该文基于博弈论分析用户上传行为，提出隐私保护的优化上传机制。首先建立用户上传行为与路况服务质量和隐私泄露之间的关系，据此构建不完全信息博弈模型，以便分析用户上传行为；然后，根据用户上传博弈纳什均衡，提出用户终端可控的隐私保护优化上传机制。理论分析表明，该文提出的上传机制最大化用户效用，具有激励相容特性；通过真实数据实验验证，上传机制能够提高用户的隐私保护度，以及算法的激励相容特性。
- 众包监测 /
- 位置隐私 /
- 不完全信息博弈 /
- 均衡
Abstract: Crowdsourcing traffic monitoring is a promising application, which exploits ubiquitous mobile devices to upload GPS samples to obtain live road traffic. However, uploading the sensitive location information raises significant privacy issues. By analyzing the upload behavior of mobile users, this paper designs a privacy preserving traffic data collection mechanism. Using the relationships among the traffic service quality, privacy loss and the upload behavior, an incomplete information game is built to analyze the upload behavior of users. Based on the existence and uniqueness of Nash equilibrium in this game, a user-centric privacy preserving traffic data collection mechanism is proposed, which can maximize the utilities of users, and this mechanism has a feature of incentive compatible. Finally, the experimental results on real world traffic data confirm the effectiveness of privacy protecting and the feature of incentive compatible.
- Crowdsourced monitoring /
- Location privacy /
- Incomplete information game /
- Equilibrium

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参考文献(19)

YANG D J, XUE G L, FANG X, et al. Incentive mechanisms for crowdsensing: crowdsourcing with smartphones[J]. IEEE/ACM Transactions on Networking, 2015, 99: 1-13.

GAO S, MA J F, SHI W S, et al. TrPF: A trafectory privacy-preserving framework for participatory sensing[J]. IEEE Transactions on Information Forensics and Security, 2013, 8(6): 874-887.

MOHAN P, PADMANABHAN V N, and RAMJEE R. Nericell: rich monitoring of road and traffic conditions using mobile smartphones[C]. Proceedings of the ACM Conference on Embedded Networked Sensor Systems, North Carolina, 2008: 323-336.

MONTJOYE Y A, HIDALGO C A, VERLEYSEN M, et al. Unique in the crowd: The privacy bounds of human mobility[R]. Nature Science Report, Cambridge, 2013.

CHRIS M, DAVID Y, and NUNG Y. Privacy vulnerability of published anonymous mobility traces[J]. IEEE Transactions on Networking, 2013, 21(3): 720-733.

孙利民, 李红, 王笑寒, 等. 物联网位置隐私保护综述[J]. 软件学报, 2014, 25(s1): 1-10.

SUN Limin, LI Hong, WANG Xiaohan, et al. Survey on the location privacy preservation in the internet of things[J]. Journal of Software, 2014, 25(s1): 1-10.

SHI E, CHAN T H, RIEFFEL E, et al. Privacy-preserving aggregation of time-series data[C]. Proceedings of 18th Network Distributed System Security Symposium, California, 2011: 1-17.

HOH B, GRUTESER M, XIONG H, et al. Achieving guaranteed anonymity in gps traces via uncertainty-aware path cloaking [J]. IEEE Transactions on Mobile Computing, 2010, 9(8): 1089-1107.

PALANISAMY B and LIU L. Attack-resilient mix-zones over road networks: architecture and algorithms[J]. IEEE Transactions on Mobile Computing, 2015, 14(3): 495-508.

LIU X X, ZHAO H, PAN M, et al. Traffic-aware multiple mix zone placement for protecting location privacy[C]. Proceedings of the 31rd Annual IEEE International Conference on Computer Communications, Florida, 2012: 972-980.

HOH B, IWUCHUKWU T, JACOBSON Q, et al. Enhancing privacy and accuracy in probe vehicle based traffic monitoring via virtual trip lines[J]. IEEE Transactions on Mobile Computing, 2012, 11(5): 849-864.

SHOKRI R, THEODORAKOPOULOS G, BOUDEC J L, et al. Quantifying location privacy[C]. Proceedings of IEEE Symposium on Security and Privacy, California, 2011: 247-262.

FREUDIGER J, MANSHAEI M H, HUBAUX J P, et al. Non-cooperative location privacy[J]. IEEE Transactions on Dependable and Secure Computing, 2013, 10(2): 84-98.

葛国栋, 郭云飞, 刘彩霞, 等. 内容中心网络中面向隐私保护的协作缓存策略[J]. 电子与信息学报, 2015, 37(5): 1220-1226. doi: 10.11999/JEIT140874.

GE Guodong, GUO Yunfei, LIU Caixia, et al. A collaborative caching strategy for privacy protection in content centric networking[J]. Journal of Electronics Information Technology, 2015, 37(5): 1220-1226. doi: 10.11999/JEIT- 140874.

黄开枝, 洪颖, 罗文宇, 等. 基于演化博弈机制的物理层安全协作方法[J]. 电子与信息学报, 2015, 37(1): 193-199. doi:10. 11999/JEIT140309.

HUANG Kaizhi, HONG Ying, LUO Wenyu, et al. A method for physical layer security cooperation based on evolutionary game[J]. Journal of Electronics Information Technology, 2015, 37(1): 193-199. doi: 10.11999/JEIT140309.

SHOKRI R, THEODORAKOPOULOS G, TRONCOSO C, et al. Protecting location privacy: Optimal strategy against localization attacks[C]. Proceedings of 19th ACM Conference on Computer and Communications Security, California, 2012: 617-627.

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