计算机科学 ›› 2017, Vol. 44 ›› Issue (Z6): 336-341.doi: 10.11896/j.issn.1002-137X.2017.6A.077

• 信息安全 • 上一篇    下一篇

基于差分隐私的LBS群组最近邻查询

马银方,张琳   

  1. 南京邮电大学计算机学院 南京210003,南京邮电大学计算机学院 南京210003
  • 出版日期:2017-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金(61402241),江苏省科技支撑计划(BE2014718)资助

LBS Group Nearest Neighbor Query Method Based on Differential Privacy

MA Yin-fang and ZHANG Lin   

  • Online:2017-12-01 Published:2018-12-01

摘要: 针对当前基于位置服务(LBS)的群组最近邻查询中出现的隐私保护问题,提出了一种新的基于差分隐私保护的LBS群组最近邻查询方法,该方法满足了差分隐私性质并引入了“区域不可区分”这一新的理念。基于分类及聚类给出了LBS群组构建方法并提供了群组隐私预算分配机制。提出了LBS群组用户位置扰乱算法(GPOL),将群组最近邻查询转换为群组质心的最近邻查询,并将其应用到整个隐私保护框架中。实验结果表明该方法能够有效地抵御现有的交叉攻击和组合攻击。

关键词: 位置服务,群最近邻查询,差分隐私,区域不可分

Abstract: For the privacy issues caused by the group nearest neighbor query scenarios formed by multi-user collaboration,a new LBS group nearest neighbor query method based on privacy protection was proposed,which introduces the “geo-indistinguishability” concept and satisfies with differential privacy property.LBS group construction mechanism based on classification and clustering was given and the group privacy budget allocation mechanism was studied.LBS Group-users’ position obfuscation by laplace (GPOL) algorithm was also introduced,which has applied the group centroid nearest neighbor query instead of group nearest neighbor query into the entire privacy protection framework.Experimental results show that this method can effectively resist the existing cross attacks and combo attacks.

Key words: Location services,Group nearest neighbor query,Differential privacy,Geo-indistinguishability

[1] ZHOU A Y,YANG B,JIN C Q,et al.Location-Based Service:Architecture and Progress [J].Chinese Journal of Computers,2011,34(7):1155-1171.
[2] FREUDIGER J,SHOKRI R,HUBAUX J P.Evaluating the privacy risk of location-based services [C]∥Proc.of FC’11.Vo-lume 7035 of LNCS,Springer,2011:31-46.
[3] KRUMM J.Inference attacks on location tracks[C]∥Proc.of PERVASIVE.Volume 4480 of LNCS,Springer,2007:127-143.
[4] GAMBS S,KILLIIJIAN M O,MNDP C.Show me how youmove and I will tell you who you are [J].Trans.on Data Privacy,2011,2(4):103-126.
[5] CHITHIKRAJA M,MOHAMED N Y,D URAIRAJAN M S.Survey of tolerant network in mobile communication [J].International Journal of Computer Science Issues,2012,9(1):1-4.
[6] 张学军,桂小林,伍忠东.位置服务隐私保护研究综述[J].软件学报,2015,26(9):2373-2395.
[7] 黄振华,张波,方强.一种社交网络群组间信息推荐的有效方法[J].电子学报,2015(6):1090-1093.
[8] CHOW C,MOKBEL M F.Enabling privacy continuous queries for revealed user locations [C]∥Proc.of the Int Symp on Advances in Spatial and Temporal Databases (SSTD).Berlin:Springer,2007.
[9] MOKBEL M F,CHOW C Y,AREF W G.The new Casper:Query processing for location services without compromising privacy [C]∥Proc.Of the Int Conf on Very Large Data Base (VLDB).New York:ACM,2006:763-774.
[10] GHINITA G,KALNIS P,KHOSHGOZARAN A,et al.Private queries in location based services:anonymizers are not necessary [C]∥ACM SIGMOD.Vancouver,BC,Canada,2008:121-132.
[11] HASHEM T,KULIK L,ZHANG R.Countering overlappingrectangle privacy attack for moving KNN queries [J].Information Systems,2013,38(3):430-453.
[12] HU H B,XU J L.2PASS:bandwith-optimized location cloaking for anonymous location-based services [J].IEEE Trans on Pa-rallel and Distributed Systems,2010,47(1):121-129.
[13] PAPADIAS D,SHEN Q,TAO Y,et al.Group nearest neighbor queries [C]∥ICDE.MA,USA,2004:301-302.
[14] PAPADIAS D,TAO Y,MOURATIDIS K,et al.Aggregate nearest neighbor queries in spatial database [J].ACM Transactions on Database Systems,2005,30(2):529-576.
[15] LIAN X,CHEN L,LIAN X,et al.Probabilistic group nearestneighbor queries in uncertain databases [J].IEEE Transactions on Knowledge and Data Engineering,2008,20(6):809-824.
[16] HUANG Y,VISHWANATHAN R.Privacy preserving groupnearest neighbor queries in location-based services using cryptographic techniques [C]∥GLOBECOM.Miami,FL,2010:1-5.
[17] HASHEM T,KULIK L,ZHANG R.Privacy preserving group nearest neighbor queries [C]∥EDBT.Lausanne,2010:489-500.
[18] SOLANAS A,MARTINE B A.A TTP-free protocol for location privacy in location-based services [J].Computer Communications,2008,31(6):1181-1191.
[19] ASHOURI T M,BARAANI D A,SELCUK A.GLP:a cryptographic approach for group location privacy [J].Computer Communication,2012,35(12):1527-1533.
[20] 高胜,马建峰,姚青松,等.LBS中面向协同位置隐私保护的群组最近邻查询[J].通信学报,2015,36(3):146-154.
[21] ANDRS M E,BORDENABE N E.Geo-Indistinguishability:Differential privacy for location-based system [C]∥Proc.of the 20th ACM Conf.on Computer and Communications Security.New York:ACM Press,2013:901-914.
[22] 李杨,温雯,谢光强.差分隐私保护综述[J].计算机应用研究,2012,9(9):3201-3211.
[23] SWEENEY L.k-anonymity:A model for protecting privacy [J].International Journal of Uncertainty,Fuzziness and Knowledge Based Systems,2002,10(5):557-570.
[24] MACHANAVAJJHALA A,KIFER D,GEHRKE J,et al.l-diversity:Privacy beyond k-anonymity[J].ACM Transactions on Knowledge Discovery from Data (TKDD),2007,1(1):3.
[25] DWORK C.Differential privacy [C]∥Proc.of the 33rd International Colloqiuium on Automata,Language and Programming.Venice,Italy,2006:1-12.
[26] DWORK C.A firm foundation for private data analysis [J].Communication of the ACM,2011,54(1):86-96.
[27] BRINKHOFF T.A framework for generating network-basedmoving objects [J].GeoInformatica,2002,6(2):153-180.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!