Enhancing Privacy Preserving Query Retrieval Using Locality Sensitive Hashing

Authors(2) :-Archana M.S, K.Deepa

The usage of smart phones is tremendously increasing day by day. Due to this, Location Based Services (LBS) attracted considerably and becomes more popular and vital in the area of mobile applications. On the other hand, the usage of LBS leads to potential threat to userís location privacy. In this paper, the famous LBS provide information about points of interest (POI) in spatial range query within a given distance. For that, a more efficient and an enhanced privacy-preserving query solution for location based, Efficient Privacy-Location Query (EPLQ) is proposed along with Locality Sensitive Hashing (LSH) reduces the dimensionality of high dimensional data. Experiments are conducted extensively and the results show the efficiency of the proposed algorithm EPLQ in privacy preserving over outsourced encrypted data in spatial range queries. The proposed method performs in spatial range queries and similarity queries of privacy preserving.

Authors and Affiliations

Archana M.S
Assistant Professor, Department of Computer Science, Nilgiri College of Arts and Science, Thaloor, The Nilgiris, Tamil Nadu, India
Assistant Professor, Department of Computer Science, Providence College for Women, Coonoor, Ooty, Tamil Nadu, India

Location Based Services, points of interest, Efficient Privacy-Location Query, NICT

  1. Statista, "Number of location-based service users in the United States from2013 to 2018 (in millions),” Statista; 2017. https://www.statista.com/statistics/436071/location-based- service-users-usa
  2. K. Xie, X. Ning, X.Wang et al., "Recover corrupted data in sensornetworks: a matrix completion solution,” IEEE Transactions on Mobile Computing, vol. 16, no. 5, pp. 1434-1448, 2017.
  3. M. Li, H. Zhu, Z. Gao et al., "All your Location are belong to us: breaking mobile social networks for automated user location tracking,” in Proceedings of the 15th ACM International Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc 2014, pp. 43-52, USA, August 2014.
  4. J. Shao, R. Lu, and X. Lin, "FINE: a fine-grained privacy preserving location-based serviceframework for mobile devices,” in Proceedings of the IEEE INFOCOM, pp. 244-252, IEEE, Ontario, Canada, May 2014.
  5. G. Ghinita, P. Kalnis, A. Khoshgozaran, C. Shahabi, and K.-Tan, "Private queries in location based services: anonymizers are not necessary,” in Proceedings of the ACMSIGMOD International Conference on Management of Data (SIGMOD ’08), pp. 121-132, ACM, 2008.
  6. B. Gedik and L. Liu, "Protecting location privacy with personalized k-anonymity: architecture and algorithms,” IEEE Transactions on Mobile Computing, vol. 7, no. 1, pp. 1- 18, 2008.
  7. R. Paulet, M. G. Kaosar, X. Yi, and E. Bertino, "Privacy preserving and content-protecting location based queries,” IEEE Transactions on Knowledge and Data Engineering, vol. 26,no.5, pp. 1200-1210, 2014.
  8. L. Sweeney, "Achieving k-anonymity privacy protection using generalization and suppression,” International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 10,no. 5, pp. 571-588, 2002.

Publication Details

Published in : Volume 5 | Issue 1 | January-February 2019
Date of Publication : 2019-01-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 70-73
Manuscript Number : CSEIT1838110
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Archana M.S, K.Deepa , "Enhancing Privacy Preserving Query Retrieval Using Locality Sensitive Hashing", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 1, pp.70-73, January-February-2019. Available at doi : https://doi.org/10.32628/CSEIT1838110
Journal URL : http://ijsrcseit.com/CSEIT1838110

Article Preview