Abstract
Finding a convenient meeting point for a group is a common problem. For example, a group of users may want to meet at a restaurant that minimizes the group’s total travel distance. Such queries are called Group Nearest Neighbor (GNN) queries. Up to now, users have had to rely on an external party, typically a location service provider (LSP), for computing an optimal meeting point. This implies that users have to trust the LSP with their private locations. Existing techniques for private GNN queries either cannot resist sophisticated attacks or are computationally too expensive to be implemented on the popular platform of mobile phones. This paper proposes an algorithm to efficiently process private GNN queries. To achieve high efficiency we propose an approach that approximates a GNN with a high accuracy and is robust to attacks. Unlike methods based on obfuscation, our method does not require a user to provide an imprecise location and is in fact location oblivious. Our approach is based on a distributed secure sum protocol which requires only light weight computation. Our experimental results show that we provide a readily deployable solution for real life applications which can also be deployed for other geo-spatial queries and applications.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Gruteser, M., Grunwald, D.: Anonymous usage of location-based services through spatial and temporal cloaking. In: MobiSys, pp. 31–42 (2003)
Chow, C.Y., Mokbel, M.F., Liu, X.: A peer-to- peer spatial cloaking algorithm for anonymous location based service. In: ACMGIS, pp. 171–178 (2006)
Hashem, T., Kulik, L., Zhang, R.: Privacy preserving group nearest neighbor queries. In: EDBT, pp. 489–500 (2010)
Duckham, M., Kulik, L., Birtley, A.: A spatiotemporal model of strategies and counter strategies for location privacy protection. In: Raubal, M., Miller, H.J., Frank, A.U., Goodchild, M.F. (eds.) GIScience 2006. LNCS, vol. 4197, pp. 47–64. Springer, Heidelberg (2006)
Shokri, R., Freudiger, J., Hubaux, J.P.: A unified framework for location privacy. In: HotPETs (2010)
Ashouri-Talouki, M., Baraani-Dastjerdi, A., Aydın Selçuk, A.: GLP: A cryptographic approach for group location privacy. Computer Communications 35(12), 1527–1533 (2012)
Huang, Y., Vishwanathan, R.: Privacy preserving group nearest neighbour queries in location-based services using cryptographic techniques. In: IEEE GLOBECOM, pp. 1–5 (2010)
Sheikh, R., Kumar, B., Mishra, D.: A distributed k-secure sum protocol for secure multi-party computations. Journal of Computing 2(3), 68–72 (2010)
Papadias, D., Shen, Q., Tao, Y., Mouratidis, K.: Group nearest neighbor queries. In: ICDE, pp. 301–312 (2004)
Ashouri-Talouki, M., Baraani-Dastjerdi, A.: Homomorphic encryption to preserve location privacy. International Journal of Security and Its Applications 6(4), 183–189 (2012)
Huang, Y., Chapman, P., Evans, D.: Privacy preserving applications on smartphones. In: USENIX Workshop on Hot Topics in Security, p. 4 (2011)
Mood, B., Letaw, L., Butler, K.: Memory efficient garbled circuit generation for mobile devices. In: Keromytis, A.D. (ed.) FC 2012. LNCS, vol. 7397, pp. 254–268. Springer, Heidelberg (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Khan, A.K.M.M.R., Hashem, T., Tanin, E., Kulik, L. (2014). Location Oblivious Privacy Protection for Group Nearest Neighbor Queries. In: Duckham, M., Pebesma, E., Stewart, K., Frank, A.U. (eds) Geographic Information Science. GIScience 2014. Lecture Notes in Computer Science, vol 8728. Springer, Cham. https://doi.org/10.1007/978-3-319-11593-1_20
Download citation
DOI: https://doi.org/10.1007/978-3-319-11593-1_20
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11592-4
Online ISBN: 978-3-319-11593-1
eBook Packages: Computer ScienceComputer Science (R0)