Advertisement

Wireless Personal Communications

, Volume 95, Issue 4, pp 3687–3711 | Cite as

A Location Privacy-Preserving Method for Spectrum Sharing in Database-Driven Cognitive Radio Networks

  • Zeinab Salami
  • Mahmoud Ahmadian-Attari
  • Hoda Jannati
  • Mohammad Reza Aref
Article
  • 161 Downloads

Abstract

The great attention to cognitive radio networks (CRNs) in recent years, as a revolutionary communication paradigm that aims to solve the problem of spectrum scarcity, prompts serious investigation on security issues of these networks. One important security concern in CRNs is the preservation of users location privacy, which is under the shadow of threat, especially in database-driven CRNs. To this end, in this paper, we propose a Location Privacy Preserving Database-Driven Spectrum-Sharing \((\hbox {L-PDS}^2)\) protocol for sharing the spectrum between PUs and SUs in a database-driven CRN, while protecting location privacy of both primary and secondary users, simultaneously. We also present two specific algorithms as implementations of \(\hbox {L-PDS}^2\) protocol. Our analytical results for the privacy protection capability of \(\hbox {L-PDS}^2\) protocol prove that it provides location privacy preservation with very high probability for users of both networks. Moreover, the simulation results show that the proposed algorithms are efficient in terms of run time.

Keywords

Database-driven cognitive radio networks Location privacy Homomorphic cryptosystem 

References

  1. 1.
    ECC Report 159. Technical and operational requirement for the possible operation of cognitive radio system in the white space of the frequency band 470–790 MHz. Cardiff. ECC. 2011. www.erodocdb.dk/docs/doc98/official/Pdf/ECCRep159. Accessed March 2011.
  2. 2.
    FCC (2012). Third order and memorandum opinion and order, in the matter of unlicensed operation in the TV broadcast bands, additional spectrum for unlicensed devices below 900 MHz and in the 3 GHz band, April 2012.Google Scholar
  3. 3.
    Durr, F. (2011). Map-aware position sharing for location privacy in non-trusted systems. In Ninth annual IEEE international conference on pervasive computing and communications, perCom 2011, USA. March 2011.Google Scholar
  4. 4.
    Chen, V., Das, S., Zhu, L., Malyar, J., & McCann, P. (Eds.). (2015). Protocol to Access White-Space (PAWS) databases. RFC, 7545. doi: 10.17487/RFC7545. http://www.rfc-editor.org/info/rfc7545. May 2015.
  5. 5.
    Bahrak, B., Bhattarai, S., Ullah, A., Park, J., Reed, J., & Gurney, D. (2014). Protecting the primary user operational privacy in spectrum sharing. In Proceedings of IEEE international symposium on Dynamic Spectrum Access Networks (DYSPAN’14) ( pp. 236–247). April 2014.Google Scholar
  6. 6.
    Aggarwal, C., & Phillip, S. (2008). Privacy-preserving data mining, models and algorithms, ch.2: A general survey of privacy-preserving data mining models and algorithms. Berlin: Springer.CrossRefGoogle Scholar
  7. 7.
    Sweeney, L. (2002). k-anonymity: A model for protecting privacy. International Journal on Uncertainty, Fuzziness and Knowledge-based Systems, 10(5), 557–570.MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Gao, Z., Zhu, H., Liu, Y., Li, M., & Cao, Z. (2013). Location privacy in database-driven cognitive radio networks: Attacks and countermeasures. In Proceedings of IEEE conference on computer communications (INFOCOM13) (pp. 2751–2759) Apr. 2013.Google Scholar
  9. 9.
    Troja, E., & Bakiras, S. (2015). Efficient location prtivacy for moving clients in database-driven dynamic spectrum access. In textitProceedings of IEEE conference on computer communications and networks (ICCCN15). August 2015.Google Scholar
  10. 10.
    Gao, Z., Zhu, H., Li, S., Du, S., & Li, X. (2012). Security and privacy of collaborative spectrum sensing in cognitive radio networks. IEEE Journal of Wireless Communications, 19(6), 106–112.CrossRefGoogle Scholar
  11. 11.
    Liu, S., Zhu, H., Du, R., Chen, C., & Guan, X. (2013). Location privacy preserving dynamic spectrum auction in cognitive radio networks. In Proceedings of IEEE international conference on distributed computing systems (ICDCS’13), pp. 256-265. July 2013.Google Scholar
  12. 12.
    Qin, Z., Yi, S., Li, Q., & Zamkov, D. (2014). Preserving secondary users privacy in cognitive radio networks. In Proceedings of IEEE conference on computer communications (INFOCOM14) (pp. 1680–1688).Google Scholar
  13. 13.
    Solanas, A., & Martnez-Ballest, A. (2007). Privacy protection in location based services through a public-key privacy homomorphism. In Proceedings 4th European conference public key infrastructure, theory and practice (pp. 362–368).Google Scholar
  14. 14.
    Zhong, G., Goldberg, I., & Hengartner, U. (2007). Louis, lester and pierre: Three protocols for location privacy. In textitProceedings 7th international conference privacy enhancing technologies (pp. 62–76).Google Scholar
  15. 15.
    Bilogrevic, I., Jadliwala, M., Joneja, V., Kalkan, K., Hubaux, J. P., & Aad, I. (2014). Privacy-preserving optimal meeting location determination on mobile devices. IEEE Transaction on Information Forensics and Security, 9(7), 1141–1156.CrossRefGoogle Scholar
  16. 16.
    Zhao, X., Li, L., & Xue, G. (2014). RemindU: A secure and efficient location based reminder system. In Proceedings of IEEE communication and information systems security symposium (ICC2014) (pp. 1005–1010).Google Scholar
  17. 17.
    Bloom, B. H. (1970). Space/time trade-offs in hash coding with allowable errors. Communications of the ACM, 13(7), 422–426.CrossRefzbMATHGoogle Scholar
  18. 18.
    Shokri, R., Theodorakopoulos, G., Papadimitratos, P., Kazemi, E., & Hubaux, J. P. (2014). Hiding in the mobile crowd: Location privacythrough collaboration. InIEEE transaction on dependable and secure computing, Special issue on security and privacy in mobileplatforms.Google Scholar
  19. 19.
    Xiao, L., Yan, Q., Lou, W., Chen, G., & Hou, Y. T. (2013). Proximity-based security techniques for mobile users in wireless networks. Communications of the ACM, 8(12), 2089–2100.Google Scholar
  20. 20.
    Gruteser, M., & Grunwald, D. (2003). Anonymous usage of location-based services through spatial and temporal cloaking. In ACM MobiSys.Google Scholar
  21. 21.
    Gedik, B., & Liu, L. (2008). Protecting location privacy with personalized k-anonymity: Architecture and algorithms. Communications of the ACM, 7(1), 1–18.Google Scholar
  22. 22.
    Dwork, C. (2006). Differential privacy. InInternational conference on automata, languages and programming (pp. 1–12).Google Scholar
  23. 23.
    Zhu, T., Xiong, P., Li, G., & Zhou, W. (2014). Correlation differential privacy: Hiding information in non-IID data set. Communications of the ACM, 10(2), 229–242.Google Scholar
  24. 24.
    Mancuso, A. Ed., Probasco, S., & Patil, B. (2013). Protocol to access white-space (PAWS) databases: Use cases and requirements, RFC 6953. https://tools.ietf.org/html/rfc6953. May 2013.
  25. 25.
    FCC. (2008). Second report and order and memorandum opinion and order (ET Docket No. 04-186), FCC 08-260, November 14, 2008.Google Scholar
  26. 26.
    IEEE. (2009). Petition for reconsideration of proposed FCC white space rules, doc.: IEEE 802.18-09/0039r4, March 2009.Google Scholar
  27. 27.
    Farpoint Group White Paper: Rethinking Spectrum Scarcity: Database-Driven Cognitive Radio, Document FPG 2010-299.1, September 2010.Google Scholar
  28. 28.
  29. 29.
    Spectrum Bridge White Space Database, whitespaces. https://www.spectrumbridge.com.
  30. 30.
  31. 31.
    Rivest, R., Shamir, A., & Adleman, L. (1978). A method for obtaining digital signatures and public-key cryptosystems. Communications of the ACM, 21(2), 120–126.MathSciNetCrossRefzbMATHGoogle Scholar
  32. 32.
    Sen, J. (2013). Theory and practice of cryptography and network security protocols and technologies (1st ed.). Rijeka: Intech Publishers.CrossRefGoogle Scholar
  33. 33.
    Paillier, P. (1999). Public-key cryptosystems based on composite degree residuosity classes. In Proceedings of the 17th international conference theory application cryptographic techniques (pp. 223–238)Google Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Zeinab Salami
    • 1
  • Mahmoud Ahmadian-Attari
    • 1
  • Hoda Jannati
    • 2
  • Mohammad Reza Aref
    • 3
  1. 1.Department of Electrical EngineeringK. N. Toosi University of TechnologyTehranIran
  2. 2.School of Computer ScienceInstitute for Research in Fundamental Sciences (IPM)TehranIran
  3. 3.Department of Electrical EngineeringSharif University of TechnologyTehranIran

Personalised recommendations