Proposed Authentication Model for Location Based Queries

Roshan S. Deshmukh¹ , D.G. Harkut²

1. Dept. CSE, Prof Ram Meghe College of Engineering and Management, Amravati, India.
2. Dept. CSE, Prof Ram Meghe College of Engineering and Management, Amravati, India.

Correspondence should be addressed to: roshan.deshmukh@gmail.com.

Section:Review Paper, Product Type: Isroset-Journal
Vol.5 , Issue.4 , pp.66-69, Aug-2017

Online published on Aug 30, 2017

Copyright © Roshan S. Deshmukh, D.G. Harkut . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
the popularity of location-based services leads to serious concerns on user privacy. It is very easy for a person to know his/her location with the help of devices having GPS facility. When user’s location is provided to Location Based Services (LBS), it is possible for user to know all location dependent information like location of friends or Nearest Restaurant, whether or traffic conditions. The massive use of mobile devices paves the way for the creation of wireless networks that can be used to exchange information. When the exchange of information is done amongst entrusted parties, the privacy of the user could be in harmful. Existing protocol doesn’t work on many different mobile devices and another issue is that, Location Server (LS) should provide misleading data to user. This gives rise to new challenges and reconsideration of the existing privacy metrics.

Key-Words / Index Term :
Location Based Services, Location Server, Path Confusion, Private Information Retrieval, K-anonymity

References :
[1] A. Beresford and F. Stajano, “Location privacy in pervasive comput,”IEEE Pervasive Computing., vol. 2, no. 1, pp. 46–55, Jan.–Mar.2003.
[2] B. Palanisamy and L. Liu, “MobiMix: Protecting location privacy with mix-zones over road networks,” in Proc. ICDE, Hannover, Germany, pp. 494–505, 2011.
[3] C. Bettini, X. Wang, and S. Jajodia, “Protecting privacy against location-based personal identification,” in Proc. 2nd VDLB Int. Conf. SDM, W. Jonker and M. Petkovic, Eds., Trondheim, Norway, pp. 185–199, LNCS 3674, 2005.
[4] B. Gedik and L. Liu, “Location privacy in mobile systems: A personalized anonymization model,” in Proc. ICDCS, Columbus, OH, USA, pp. 620–629, 2005.
[5] M. Gruteser and D. Grunwald, “Anonymous usage of location based services through spatial and temporal cloaking,” in Proc.1st Int. Conf. MobiSys, pp. 31–42, 2003.
[6] L. Sweeney, “k-Anonymity: A model for protecting privacy,” Int. J. Uncertain. Fuzziness Knowl. Based Syst., vol. 10, no. 5, pp. 557–570, Oct. 2002.
[7] S. Mascetti and C. Bettini, “A comparison of spatial generalization algorithms for lbs privacy preservation,” in Proc. Int. Mobile Data Manage., Mannheim, Germany, pp. 258–262, 2007.
[8] M. F. Mokbel, C.-Y. Chow, and W. G. Aref, “The new Casper: Query processing for location services without compromising privacy,” in Proc. VLDB, Seoul, Korea, pp. 763–774, 2006.
[9] L. Marconi, R. Pietro, B. Crispo, and M. Conti, “Time warp: How time affects privacy in LBSs,” in Proc. ICICS, Barcelona, Spain, pp. 325–339, 2010.
[10] T. Xu and Y. Cai, “Feeling-based location privacy protection for location-based services,” in Proc. 16th ACM CCS, Chicago, IL,USA, pp. 348–357, 2009.
[11] X. Chen and J. Pang, “Measuring query privacy in location-based services,” in Proc. 2nd ACM CODASPY, San Antonio, TX, USA, pp. 49–60, 2012.
[12] B. Hoh and M. Gruteser, “Protecting location privacy through path confusion,” in Proc. 1st Int. Conf. SecureComm, pp. 194–205, 2005.
[13] P. Kalnis, G. Ghinita, K. Mouratidis, and D. Papadias, “Preventing location-based identity inference in anonymous spatial queries,” IEEE Trans. Knowl. Data Eng., vol. 19, no. 12, pp. 1719–1733, Dec. 2007.
[14] M. Damiani, E. Bertino, and C. Silvestri, “The PROBE framework for the personalized cloaking of private locations,” Trans. Data Privacy, vol. 3, no. 2, pp. 123–148, 2010.
[15] T. Hashem and L. Kulik, “Safeguarding location privacy in wireless ad-hoc networks,” in Proc. 9th Int. Conf. UbiComp, Innsbruck, Austria, pp. 372–390, 2007.
[16] M. Duckham and L. Kulik, “A formal model of obfuscation and negotiation for location privacy,” in Proc. 3rd Int. Conf. Pervasive Comput., H. Gellersen, R. Want, and A. Schmidt, Eds., pp. 243–251, LNCS 3468, 2005.
[17] H. Kido, Y. Yanagisawa, and T. Satoh, “An anonymous communication technique using dummies for location-based services,” in Proc. Int. Conf. ICPS, pp. 88–97, 2005.
[18] J. Krumm, “A survey of computational location privacy,” Pers. Ubiquitous Comput., vol. 13, no. 6, pp. 391–399, Aug. 2009.
[19] G. Ghinita, P. Kalnis, A. Khoshgozaran, C. Shahabi, and K.-L. Tan, “Private queries in location based services: Anonymizers are not necessary,” in Proc. ACM SIGMOD, Vancouver, BC, Canada, pp. 121–132, 2008.
[20] B. Chor, E. Kushilevitz, O. Goldreich, and M. Sudan, “Private information retrieval,” J. ACM, vol. 45, no. 6, pp. 965–981, 1998.
[21] E. Kushilevitz and R. Ostrovsky, “Replication is not needed: Single database, computationally-private information retrieval,” in Proc. FOCS, Miami Beach, FL, USA, pp. 364–373, 1997.
[22] G. Ghinita, P. Kalnis, M. Kantarcioglu, and E. Bertino, “A hybrid technique for private location-based queries with database protection,” in Proc. Adv. Spatial Temporal Databases, N. Mamoulis, T. Seidl, T. Pedersen, K. Torp, and I. Assent, Eds., Aalborg, Denmark, pp. 98–116, LNCS 5644, 2009.
[23] G. Ghinita, P. Kalnis, M. Kantarcioglu, and E. Bertino, “Approximate and exact hybrid algorithms for private nearest-neighbor queries with database protection,” GeoInformatica, vol. 15, no. 14, pp. 1–28, 2010.
[24] P. Paillier, “Public-key cryptosystems based on composite degree residuosity classes,” in Proc. EUROCRYPT, vol. 1592, Prague, Czech Republic, pp. 223–238, 1999.