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Privacy-preserving data aggregation scheme against internal attackers in smart grids

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Abstract

With fast advancements of communication, systems and information technologies, a smart grid (SG) could bring much convenience to users because it could provide a reliable and efficient energy service. The data aggregation (DA) scheme for the SG plays an important role in evaluating information about current energy usage. To achieve the goal of preserving users’ privacy, many DA schemes for the SG have been proposed in last decade. However, how to withstand attacks of internal adversaries is not considered in those schemes. To enhance preservation of privacy, Fan et al. proposed a DA scheme for the SG against internal adversaries. In Fan et al.’s DA scheme, blinding factors are used in evaluating information about current energy usage and the aggregator cannot get the consumption information of any individual user. Fan et al. demonstrated that their scheme was secure against various attacks. However, we find that their scheme suffers from the key leakage problem, i.e., the adversary could extract the user’s private key through the public information. To overcome such serious weakness, this paper proposes an efficient and privacy-preserving DA scheme for the SG against internal attacks. Analysis shows that the proposed DA scheme not only overcome the key leakage problem in Fan et al.’s DA scheme, but also has better performance.

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References

  1. 1.

    He, D., Chen, C., Bu, J., Chan, S., Zhang, Y., & Guizani, M. (2012). Secure service provision in smart grid communications. IEEE Communications Magazine, 50(8), 53–61.

  2. 2.

    Fadlullah, Z., Kato, N., Lu, R., Shen, X., & Nozaki, Y. (2012). Toward secure targeted broadcast in smart grid. IEEE Communications Magazine, 50(5), 150–156.

  3. 3.

    He, D., Chan, S., Chen, C., & Bu, J. (2014). An enhanced public key infrastructure to secure smart grid wireless communication networks. IEEE Network, 28(1), 10–16.

  4. 4.

    Gao, J., Xiao, Y., Liu, J., Liang, W., & Chen, C. (2011). A survey of communication/networking in smart grids. Future Generation Computer Systems, 28(2), 391–404.

  5. 5.

    Li, Q., & Cao, G. (2011). Multicast authentication in the smart grid with onetime signature. IEEE Transactions on Smart Grid, 2(4), 686–696.

  6. 6.

    Fouda, M., Fadlullah, Z., Kato, N., Lu, R., & Shen, X. (2011). A lightweight message authentication scheme for smart grid communications. IEEE Transactions on Smart Grid, 2(4), 675–685.

  7. 7.

    Li, H., Lu, R., Zhou, L., Yang, B., & Shen, X. (2014). An efficient merkle-tree-based authentication scheme for smart grid. IEEE Systems Journal, 8(2), 655–663.

  8. 8.

    Wu, D., & Zhou, C. (2011). Fault-tolerant and scalable key management for smart grid. IEEE Transactions on Smart Grid, 2(2), 375–381.

  9. 9.

    Tseng, H. (2014). Threshold-based privacy-preserving key management scheme for vehicle-to-grid networks. Applied Mechanics and Materials, 479(1), 978–982.

  10. 10.

    Wan, Z., Wang, G., Yang, Y., & Shi, S. (2014). SKM: Scalable key management for advanced metering infrastructure in smart grids. IEEE Transactions on Industrial Electronics, 61(12), 7055–7066.

  11. 11.

    Li, F., Luo, B., & Liu, P. (2010) Secure information aggregation for smart grids using homomorphic encryption. In First IEEE international conference on smart grid communications (pp. 327–332).

  12. 12.

    Paillier, P. (1999) A public-key cryptosystem based on composite degree residuosity classes. In EUROCRYPT ‘99 (pp. 223–238).

  13. 13.

    Garcia, F. D., & Jacobs B. (2011). Privacy-friendly energy-metering via homomorphic encryption. In 6th international conference on security and trust management (pp. 226–238).

  14. 14.

    Lu, R., Liang, X., Li, X., Lin, X., & Shen, X. (2012). EPPA: An efficient and privacy-preserving aggregation scheme for secure smart grid communications. IEEE Transactions on Parallel and Distributed Systems, 23(9), 1621–1632.

  15. 15.

    Zhang, J., Liu, L., Cui, Y., & Chen, Z. (2013). SP2DAS: Self-certified PKC-based privacy-preserving data aggregation scheme in smart grid. International Journal of Distributed Sensor Networks, 2013, 457325. doi:10.1155/2013/457325.

  16. 16.

    Chen, L., Lu, R., & Cao, Z. (2014). PDAFT: A privacy-preserving data aggregation scheme with fault tolerance for smart grid communications. Peer-to-Peer Networking and Applications. doi:10.1007/s12083-014-0255-5.

  17. 17.

    Fan, C., Huang, S., & Lai, Y. (2014). Privacy enhanced data aggregation scheme against internal attackers in smart grid. IEEE Transactions on Industrial Informatics, 10(1), 666–675.

  18. 18.

    Farash, M., & Attari, M. (2014). A secure and efficient identity-based authenticated key exchange protocol for mobile client–server networks. The Journal of Supercomputing, 69(1), 395–411.

  19. 19.

    Farash, M., & Attari, M. (2014). Cryptanalysis and improvement of a chaotic maps-based key agreement protocol using Chebyshev sequence membership testing. Nonlinear Dynamics, 76(2), 1203–1213.

  20. 20.

    Mishra, D., Jangirala, S., & Mukhopadhyay, S. (2014). A secure and efficient chaotic map-based authenticated key agreement scheme for telecare medicine information systems. Journal of Medical Systems, 38(10), 1–10.

  21. 21.

    Xie, Q., Tan, X., Wong, D., Wang, G., Bao, M., & Dong, N. (2014). A practical anonymous authentication protocol for wireless roaming. Security and Communication Networks, 7(8), 1264–1273.

  22. 22.

    He, D., & Zeadally, S. (2015). Authentication protocol for ambient assisted living system. IEEE Communications Magazine, 35(1), 71–77.

  23. 23.

    He, D., Kumar, N., & Chilamkurti, N. (2015) A secure temporal-credential-based mutual authentication and key agreement scheme with pseudo identity for wireless sensor networks. Information Sciences. doi:10.1016/j.ins.2015.02.010.

  24. 24.

    Jiang, Q., Ma, J., Li, G., & Li, X. (2015). Improvement of robust smart-card-based password authentication scheme. International Journal Communication Systems, 28(2), 383–393.

  25. 25.

    David, P., & Jacque, S. (2000). Security arguments for digital signatures and blind signatures. Journal of Cryptology, 13(3), 361–396.

  26. 26.

    Wu, T., & Tseng, Y. (2010). An efficient user authentication and key exchange protocol for mobile client–server environment. Computer Networks, 54(9), 1520–1530.

  27. 27.

    He, D. (2012). An efficient remote user authentication and key agreement protocol for mobile client–server environment from pairings. Ad Hoc Networks, 10(6), 1009–1016.

  28. 28.

    Kilinc, H. H., & Yanik, T. (2014). A survey of SIP authentication and key agreement schemes. IEEE Communications Surveys & Tutorials, 16(2), 1005–1023.

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Acknowledgments

The work of J.-H. Lee was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2014R1A1A1006770).

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Correspondence to Jong-Hyouk Lee.

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Cite this article

He, D., Kumar, N. & Lee, J. Privacy-preserving data aggregation scheme against internal attackers in smart grids. Wireless Netw 22, 491–502 (2016). https://doi.org/10.1007/s11276-015-0983-3

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Keywords

  • Smart grid
  • Data aggregation
  • Privacy
  • Internal attacker