摘要 近些年来，随着配备定位功能的移动终端数量迅速增加，基于位置服务（LBS）的应用呈现爆炸式的增长，例如查找最邻近的加油站、一公里范围内的所有餐厅等.在用户享受着这些LBS服务为工作、生活带来方便的同时，许多隐私安全问题也逐渐引起了人们的关注.全面了解基于位置服务中现有的隐私保护工作，有利于研究者把握该领域的研究现状、未来发展方向以及存在的挑战.本文对LBS 隐私保护领域中近些年的发展进行了研究总结，重点介绍了LBS隐私保护领域现有的攻击模型、隐私保护模型、度量模型以及数据集，并对现有攻击模型与隐私保护模型进行分类总结，根据其特点进行对比分析，最后探讨了LBS隐私保护目前存在的问题以及未来的发展方向.Abstract：In recent years, with the rapid increase in the number of GPSenabled mobile devices, locationbased services (LBS) applications grow explosively, such as finding the nearest gas station or restaurants within one kilometer and so on. Users benefit from convenience of LBS. However, many privacy issues draw people's attention gradually. Acomprehensive understanding of existing privacy protection work in the locationbased services is important for researchers to grasp the present research status, the future development directionsand the challenges.We give a deep survey of the recent improvement in LBS，which mainly focus on existing attacking models,privacy protection model, measure model and datasets.What′s more, we classifies the existing attacking model and privacy protection model and made comparisons based on different features. Finally unsolved problems and future development are also discussed.
References
[1]
JUNGLAS I A, WATSON R T. Locationbased services[J]. Communications of the ACM, 2008, 51(3): 6569.
[2]
ZICKUHR K. Locationbased services[J]. Pew Research, 2013：125.
[3]
BARKHUUS L, DEY A K. Locationbased services for mobile telephony: A study of users'' privacy concerns[C]IFIP TC13 International Conference on HumanComputer Interaction. Zurich, Switzerland: DBLP, 2003: 709712.
PINGLEY A, ZHANG N, FU X, et al. Protection of query privacy for continuous location based services[C]INFOCOM, 2011 Proceedings IEEE.\[s.l.\]:IEEE, 2011: 17101718.
[8]
GEDIK B, LIU L. Protecting location privacy with personalized kanonymity: Architecture and algorithms[J]. Mobile Computing, IEEE Transactions on, 2008, 7(1): 118.
[9]
ZHANG C Y, HUANG Y. Cloaking locations for anonymous location based services: A hybrid approach[J]. Geoinformatica,2009,13(2):159182.
[10]
CHOW C Y, MOKBEL M F, AREDF W G. Casper*: Query processing for location services without compromising privacy[J]. ACM Transactions on Database Systems (TODS), 2009, 34(4): 24.
[11]
REBOLLOMONEDERO D, PARRAAMAU J, DIAZ C, et al. On the measurement of privacy as an attacker’s estimation error[J]. International Journal of Information Security, 2013, 12(2): 129149.
[12]
GHINITA G, KALNIS P, KHOSHGOZARAN A, et al. Private queries in location based services: anonymizers are not necessary[C]Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data. New York: ACM, 2008: 121132.
[13]
PALANISAMY B, LIU L. Attackresilient mixzones over road networks: architecture and algorithms[J]. Mobile Computing IEEE Translations on, 2015,14(3):495508.
[14]
CHOW C Y, MOKBEL M F. Enabling private continuous queries for revealed user locations[M]Advances in Spatial and Temporal Databases. Berlin: Springer, 2007: 258275.
[15]
XIAO P, ZHEN X. Survey of location privacypreserving[J]. Journal of Frontiers of Computer Science and Technology, 2007, 1(3): 268281.
[16]
LIU F Y, HUA K A, CAI Y. Query ldiversity in locationbased services[C]Mobile Data Management: Systems, Services and Middleware. Tenth International Conference on IEEE.[s.l.]: IEEE Xplore, 2009: 436442.
DING Y, PEDDINTI S T, ROSS K W. Stalking Beijing from Timbuktu: A generic measurement approach for exploiting locationbased social discovery[C]Proceedings of the 4th ACM Workshop on Security and Privacy in Smartphones and Mobile Devices. New York: ACM, 2014: 7580.
[19]
BERESFORD A R, STAJANO F. Location privacy in pervasive computing[J]. IEEE Pervasive computing, 2003, 2(1): 4655.
[20]
PAN X, MENG X, XU J. Distortionbased anonymity for continuous queries in locationbased mobile services[C]Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. New York: ACM, 2009: 256265.
[21]
MACHANAVAJJHALA A, KIFER D, GEHRKE J, et al. lDiversity: Privacy beyond kanonymity[J]. ACM Transactions on Knowledge Discovery from Data (TKDD), 2007, 1(1): 3.
[22]
XU T, CAI Y. Exploring historical location data for anonymity preservation in locationbased services[C]INFOCOM 2008. The 27th Conference on Computer Communications. IEEE.[s.l.]:IEEE, 2008.
[23]
XU T, CAI Y. Location anonymity in continuous locationbased services[C]Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems. New York: ACM, 2007: 39.
[24]
GHINITA G, KALNIS P, SKIADOPOULOS S. PRIVE: anonymous locationbased queries in distributed mobile systems[C]Proceedings of the 16th international conference on World Wide Web. New York: ACM, 2007: 371380.
[25]
CHE Y, CHIEW K, HONG X, et al. SALS: semanticsaware location sharing based on cloaking zone in mobile social networks[C]Proceedings of the First ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems. New York: ACM, 2012: 4956.
[26]
BUTTYAN L, HOLCZER T, VAJDA I. On the effectiveness of changing pseudonyms to provide location privacy in VANETs[M]Security and Privacy in Adhoc and Sensor Networks. Berlin: Springer, 2007: 129141.
[27]
PALANISAMY B, LIU L. Mobimix: Protecting location privacy with mixzones over road networks[C]Proceedings of the 27th International Conference on Data Engineering. Hannover,Germany: IEEE, 2011: 494505.
[28]
PALANISAMY B, LIU L. Effective mixzone anonymization techniques for mobile travelers[J]. GeoInformatica, 2014, 18(1): 135164.
[29]
NIU B, LI Q, ZHU X, et al. Achieving kanonymity in privacyaware locationbased services[C]IEEE INFOCOM 2014IEEE Conference on Computer Communications. [s.l.]: IEEE, 2014: 754762.
[30]
LU H, JENSEN C S, YIU M L. Pad: Privacyarea aware, dummybased location privacy in mobile services[C]Proceedings of the Seventh ACM International Workshop on Data Engineering for Wireless and Mobile Access.New York: ACM, 2008: 1623.
[31]
YIU M L, JENSEN C S, MOLLER J, et al. Design and analysis of a ranking approach to private locationbased services[J]. ACM Transactions on Database Systems (TODS), 2011, 36(2): 10.
[32]
SHOKRI R, THEODORAKOPOULOS G, LE BOUDEC J Y, et al. Quantifying location privacy[C]Security and Privacy (SP), IEEE Symposium on.[s.l.]:IEEE, 2011: 247262.
[33]
PAN X, XU J, MENG X. Protecting location privacy against locationdependent attacks in mobile services[J]. Knowledge and Data Engineering, IEEE Transactions on, 2012, 24(8): 15061519.
[34]
XUE A Y, ZHANG R, ZHENG Y, et al. Destination prediction by subtrajectory synthesis and privacy protection against such prediction[C]Data Engineering (ICDE), 2013 IEEE 29th International Conference on.[s.l.]:IEEE, 2013: 254265.
[35]
GRUTESER M, GRUNWALD D. Anonymous usage of locationbased services through spatial and temporal cloaking[C]Proceedings of the 1st Iinternational Conference on Mobile Systems, Applications and Services. New York: ACM, 2003: 3142.
[36]
MOKBEL M F, CHOW C Y, AREF W G. The new Casper: Query processing for location services without compromising privacy[C]Proc. of the 32nd Int’l Conf. on Very Large Data Bases. Seoul: VLDB Endowment, 2006:763774.
ZHOU C, MA C, YANG S, et al. A Location Privacy Preserving Method Based on Sensitive Diversity for LBS[M]Network and Parallel Computing. Berlin: Springer, 2014: 409422.
[39]
CICEK A E, NERGIZ M E, SAYGIN Y. Ensuring location diversity in privacypreserving spatiotemporal data publishing[J]. The VLDB Journal, 2014, 23(4): 609625.
[40]
ASSAM R, HASSANI M, SEIDL T. Differential private trajectory protection of moving objects[C]Proceedings of the Third ACM SIGSPATIAL International Workshop on GeoStreaming. New York: ACM, 2012: 6877.
[41]
CHEN R, FUNG B, DESAI B C, et al. Differentially private transit data publication: a case study on the montreal transportation system[C]Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining. New York: ACM, 2012: 213221.
[42]
PAPADOPOULOS S, BAKIRAS S, PAPADIAS D. pCloud: A Distributed System for Practical PIR[J]. IEEE Trans Dependable Sec Comput, 2012, 9(1): 115127.
[43]
SCHLEGEL R, CHOW C Y, HUANG Q, et al. UserDefined Privacy Grid System for Continuous LocationBased Services[J]. Mobile Computing, IEEE Transactions on, 2015, 14(10): 21582172.
[44]
LU R, LIN X, SHI Z, et al. PLAM: A privacypreserving framework for localarea mobile social networks[C]IEEE INFOCOM 2014IEEE Conference on Computer Communications.[s.l.]:IEEE, 2014: 763771.
[45]
KHOSHGOZARAN A, SHIRANIMEHR H, SHAHABI C. Blind evaluation of location based queries using space transformation to preserve location privacy[J]. GeoInformatica, 2013, 17(4): 599634.
[46]
VICENTE C R, KIRKPATRICK M, GHINITA G, et al. Towards locationbased access control in healthcare emergency response[C]Proceedings of the 2nd SIGSPATIAL ACM GIS 2009 International Workshop on Security and Privacy in GIS and LBS. New York:ACM, 2009: 2226.
[47]
ZHANG Y, CHEN K, LIAN Y. A pathbased access control method for location obfuscation in mobile environment[C]Electrical and Electronics Engineering (EEESYM), IEEE Symposium on.[s.l.]:IEEE, 2012: 570573.
[48]
SERJANTOV A, DANEZIS G. Towards an information theoretic metric for anonymity[C]Proceedings of the Workshop on Privacy Enhancing Technologies. Berlin: Springer, 2003: 4153.
[49]
XU J, TANG X, HU H, et al. Privacyconscious locationbased queries in mobile environments[J]. Parallel and Distributed Systems, IEEE Transactions on, 2010, 21(3): 313326.
[50]
SWEENEY L. kanonymity: A model for protecting privacy[J]. International Journal of Uncertainty, Fuzziness and KnowledgeBased Systems, 2002, 10(05): 557570.
[51]
XIAO Z, XU J, MENG X. pSensitivity: A semantic privacyprotection model for locationbased services[C]Mobile Data Management Workshops, 2008. MDMW 2008. Ninth International Conference on IEEE. [s.l.]: IEEE, 2008: 4754.
[52]
YANG N, CAO Y, LIU Q, et al. A novel personalized TTPfree location privacy preserving method[J]. International Journal of Security and Its Applications, 2014, 8(2): 387398.
[53]
ZHANG X, XIA Y, BAE H Y, et al. A novel location privacy preservation method for moving object[J]. International Journal of Security and Its Applications, 2015, 9(2): 112.
[54]
SHOKRI R, THEODORAKOPOULOS G, DANEZIS G, et al. Quantifying location privacy: The case of sporadic location exposure[C]Privacy Enhancing Technologies. Berlin: Springer, 2011: 5776.
[55]
BRINKHOFF T. A framework for generating networkbased moving objects[J]. Geoinformatica, 2002, 6(2): 153180.
[56]
YAO L, LIN C, LIU G, et al. Location anonymity based on fake queries in continuous locationbased services[C]Availability, Reliability and Security (ARES), 2012 Seventh International Conference on IEEE.[s.l.]:IEEE, 2012: 375382.
