Privacy Preserving Method Based on Location Service in Personalized Search

Qiang ZHANG; Guojun WANG

doi:10.11999/JEIT171137

Volume 40 Issue 8

Aug. 2018

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(8): 1998-2005

Qiang ZHANG, Guojun WANG. Privacy Preserving Method Based on Location Service in Personalized Search[J]. Journal of Electronics & Information Technology, 2018, 40(8): 1998-2005. doi: 10.11999/JEIT171137

Citation:

Qiang ZHANG, Guojun WANG. Privacy Preserving Method Based on Location Service in Personalized Search[J]. Journal of Electronics & Information Technology, 2018, 40(8): 1998-2005. doi: 10.11999/JEIT171137

Citation:

PDF( 1895 KB)

Privacy Preserving Method Based on Location Service in Personalized Search

doi: 10.11999/JEIT171137

Qiang ZHANG¹,
Guojun WANG^{2
,
,}

1.
School of Information Science and Engineering, Central South University, Changsha 410083, China
2.
School of Computer Science and Educational Software, Guangzhou University, Guangzhou 510006, China

Funds: The National Natural Science Foundation of China (61632009, 61472451), The Guangdong Provincial Natural Science Foundation (2017A030308006), The High-Level Talents Program of Higher Education in Guangdong Province (2016ZJ01), The Fundamental Research Funds for the Central Universities of Central South University (2017zzts141)

Received Date: 2017-12-04
Rev Recd Date: 2018-04-20

Available Online: 2018-06-07

Publish Date: 2018-08-01

Abstract

Abstract

For personalized search based on location service, the trusted third-party server and peer node are used as the main method for privacy preserving. However, entirely trusted third-party server or peer node does not exist in real life. In order to address this problem, a method of privacy preserving on the location of mobile users is proposed when using personalized search. The method is used to convert the user’s location information into distance information and generate the user model according to the user’s query type, forming a query matrix with user location information, then the matrix is used to encrypt the user’s query and conceal the user information in the query matrix. Finally, according to the calculation of the security inner product, the K file with the highest relevance score is returned to the user. It is evident from the security analysis that the proposed method can effectively protect the user’s query privacy and location privacy. The analysis and experimental results show that the proposed method can greatly shorten the time of index construction and reduce the communication overhead. While providing users with location based personalized search results, the method is able to remedy the defects of small-screen mobile devices.
- Privacy preserving,
- Personalized search,
- Location conversion,
- Security inner product

FullText(HTML)

References(18)

References

LU Rongxing, LIN Xiaodong, LIANG Xiaohui, et al.. A dynamic privacy-preserving key management scheme for location-based services in VANETs[J]. IEEE Transactions on Intelligent Transportation Systems, 2012, 13(1): 127–139. DOI: 10.1109/TITS.2011.2164068.

YU Rong, KANG Jiawen, HUANG Xumin, et al.. MixGroup: Accumulative pseudonym exchanging for location privacy enhancement in vehicular social networks[J]. IEEE Transactions on Dependable and Secure Computing, 2016, 13(1): 93–105. DOI: 10.1109/TDSC.2015.2399291.

张少波, 刘琴, 王国军. 基于网格标识匹配的位置隐私保护方法[J]. 电子与信息学报, 2016, 38(9): 2173–2179. DOI: 10.11999/JEIT160350.

ZHANG Shaobo, LIU Qin, and WANG Guojun. The method of location privacy protection based on grid identifier matching[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2173–2179. DOI: 10.11999/JEIT160350.

DU Qing, XIE Haoran, CAI Yi, et al.. Folksonomy-based personalized search by hybrid user profiles in multiple levels[J]. Neurocomputing, 2016, 204(C): 142–152. DOI: 10.1016/j.neucom.2015.10.135.

ZHOU Dong, WU Xuan, ZHAO Wenyu, et al.. Query expansion with enriched user profiles for personalized search utilizing folksonomy data[J]. IEEE Transactions on Knowledge & Data Engineering, 2017, 29(7): 1536–1548. DOI: 10.1109/TKDE.2017.2668419.

PENG Tao, LIU Qin, and WANG Guojun. Enhanced location privacy preserving scheme in location-based services [J]. IEEE Systems Journal, 2017, 11(1): 219–230. DOI: 10.1109/JSYST.2014.2354235.

PAN Xiao, XU Jianliang, and MENG Xiaofeng. Protecting location privacy against location-dependent attacks in mobile services[J]. IEEE Transactions on Knowledge & Data Engineering, 2012, 24(8): 1506–1519. DOI: 10.1109/TKDE.2011.105.

HWANG R H, HSUEH Y L, and CHUNG H W. A novel time-obfuscated algorithm for trajectory privacy protection [J]. IEEE Transactions on Services Computing, 2014, 7(2): 126–139. DOI: 10.1109/TSC.2013.55.

NIU Ben, LI Qinghua, ZHU Xiaoyan, et al.. Enhancing privacy through caching in location-based services[C]. Proceedings of the IEEE Conference on Computer Communications (INFOCOM). Hong Kong, China, 2015: 1017–1025.

CHOR B, GOLDREICH O, KUSHILEVITZ E, et al.. Private information retrieval[C]. Proceedings of the 36th Annual Symposium on Foundations of Computer Science, Washington, USA, 1995: 41–50.

LI Xiangyang and JUNG T. Search me if you can: Privacy-preserving location query service[C]. Proceedings of the IEEE International Conference on Computer Communications (INFOCOM). Turin, Italy, 2013: 2760–2768.

FU Zhangjie, REN Kui, SHU Jiangang, et al.. Enabling personalized search over encrypted outsourced data with efficiency improvement[J]. IEEE Transactions on Parallel & Distributed Systems, 2016, 27(9): 2546–2559. DOI: 10.1109/TPDS.2015.2506573.

ZHAO Feng, YAN Fengwei, JIN Hai, et al.. Personalized mobile searching approach based on combining content-based filtering and collaborative filtering[J]. IEEE Systems Journal, 2017, 11(1): 324–332. DOI: 10.1109/JSYST.2015.2472996.

LEUNG W T, LEE D L, and LEE W C. PMSE: A personalized mobile search engine[J]. IEEE Transactions on Knowledge & Data Engineering, 2013, 25(4): 820–834. DOI: 10.1109/TKDE.2012.23.

WONG Waikit, CHEUNG W L, KAO Ben, et al. Secure kNN computation on encrypted databases[C]. ACM SIGMOD International Conference on Management of Data. ACM, Providence, USA, 2009: 139–152.

罗恩韬, 王国军. 移动社交网络中一种朋友发现的隐私安全保护策略[J]. 电子与信息学报, 2016, 38(9): 2165–2172. DOI: 10.11999/JEIT151479.

LUO Entao and WANG Guojun. A novel friends matching privacy preserving strategy in mobile social networks[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2165–2172. DOI: 10.11999/JEIT151479.

ZHANG Qiang, LIU Qin, and WANG Guojun. A privacy-preserving hybrid cooperative searching scheme over outsourced cloud data[C]. Security, Privacy, and Anonymity in Computation, Communication, and Storage. Zhangjiajie, China, 2016: 265–278.

CAO Ning, WANG Cong, LI Ming, et al.. Privacy-preserving multi-keyword ranked search over encrypted cloud data[J]. IEEE Transactions on Parallel and Distributed Systems, 2014, 25(1): 222–233. DOI: 10.1109/TPDS.2013.45.

Relative Articles

Supplements(0)

Cited By

Proportional views