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EFFECT: an efficient flexible privacy-preserving data aggregation scheme with authentication in smart grid

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Abstract

Smart grid is considered as a promising approach to solve the problems of carbon emission and energy crisis. In smart grid, the power consumption data are collected to optimize the energy utilization. However, security issues in communications still present practical concerns. To cope with these challenges, we propose EFFECT, an efficient flexible privacy-preserving aggregation scheme with authentication in smart grid. Specifically, in the proposed scheme, we achieve both data source authentication and data aggregation in high efficiency. Besides, in order to adapt to the dynamic smart grid system, the threshold for aggregation is adjusted according to the energy consumption information of each particular residential area and the time period, which can support fault-tolerance while ensuring individual data privacy during aggregation. Detailed security analysis shows that our scheme can satisfy the desired security requirements of smart grid. In addition, we compare our scheme with existing schemes to demonstrate the effectiveness of our proposed scheme in terms of low computational complexity and communication overhead.

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References

  1. Wang K, Du M, Maharjan S, et al. Strategic honeypot game model for distributed denial of service attacks in the smart grid. IEEE Trans Smart Grid, 2017, 8: 2474–2482

    Article  Google Scholar 

  2. Guan Z T, Si G L, Zhang X S, et al. Privacy-preserving and efficient aggregation based on blockchain for power grid communications in smart communities. IEEE Commun Mag, 2018, 56: 82–88

    Article  Google Scholar 

  3. Xue K P, Li S H, Hong J N, et al. Two-cloud secure database for numeric-related sql range queries with privacy preserving. IEEE Trans Inf Foren Sec, 2017, 12: 1596–1608

    Article  Google Scholar 

  4. Wu J, Dong M X, Ota K, et al. Securing distributed storage for social internet of things using regenerating code and blom key agreement. Peer-to-Peer Netw Appl, 2015, 8: 1133–1142

    Article  Google Scholar 

  5. Erkin Z, Troncoso-Pastoriza J, Lagendijk R, et al. Privacy-preserving data aggregation in smart metering systems: an overview. IEEE Signal Proc Mag, 2013, 30: 75–86

    Article  Google Scholar 

  6. Yan Y, Qian Y, Sharif H, et al. A survey on smart grid communication infrastructures: motivations, requirements and challenges. IEEE Commun Surv Tut, 2013, 15: 5–20

    Article  Google Scholar 

  7. Cho S, Li H, Choi B J. Palda: efficient privacy-preserving authentication for lossless data aggregation in smart grids. In: Proceedings of IEEE International Conference on Smart Grid Communications, 2014. 914–919

    Google Scholar 

  8. Guan Z T, Li J, Zhu L H, et al. Toward delay-tolerant flexible data access control for smart grid with renewable energy resources. IEEE Trans Ind Inform, 2017, 13: 3216–3225

    Article  Google Scholar 

  9. Zheng J M, Tan Y A, Zhang Q K, et al. Cross-cluster asymmetric group key agreement for wireless sensor networks. Sci China Inf Sci, 2018, 61: 048103

    Article  MathSciNet  Google Scholar 

  10. Guan Z T, Li J, Wu L F, et al. Achieving efficient and secure data acquisition for cloud-supported internet of things in smart grid. IEEE Int Thing J, 2017, 4: 1934–1944

    Article  Google Scholar 

  11. Zhang Z J, Qin Z, Zhu L H, et al. Cost-friendly differential privacy for smart meters: exploiting the dual roles of the noise. IEEE Trans Smart Grid, 2016, 8: 619–626

    Google Scholar 

  12. Li S H, Xue K P, Yang Q Y, et al. PPMA: privacy-preserving multisubset data aggregation in smart grid. IEEE Trans Ind Inf, 2018, 14: 462–471

    Article  Google Scholar 

  13. Li S H, Zhang X, Xue K P, et al. Privacy-preserving prepayment based power request and trading in smart grid. China Commun, 2018, 15: 14–27

    Article  Google Scholar 

  14. Xiao Y, Tan Y A, Sun Z Z, et al. A fault-tolerant and energy-efficient continuous data protection system. J Amb Intel Hum Comp, 2018. doi: 10.1007/s12652-018-0726-2

    Google Scholar 

  15. Przydatek B, Song D, Perrig A. Sia: secure information aggregation in sensor networks. In: Proceedings of the 1st International Conference on Embedded Networked Sensor Systems, 2003. 255–265

    Chapter  Google Scholar 

  16. Shi E, Chan T H, Rieffel E, et al. Privacy-preserving aggregation of time-series data. In: Proceedings of the 18th Annual Network and Distributed System Security Conference, 2011

    Google Scholar 

  17. Kim Y S, Heo J. Device authentication protocol for smart grid systems using homomorphic Hash. J Commun Netw, 2012, 14: 606–613

    Article  Google Scholar 

  18. Lu R X, Liang X H, Li X, et al. EPPA: an efficient and privacy-preserving aggregation scheme for secure smart grid communications. IEEE Trans Paral Distrib Syst, 2012, 23: 1621–163

    Article  Google Scholar 

  19. Chen L, Lu R X, Cao Z F. Pdaft: a privacy-preserving data aggregation scheme with fault tolerance for smart grid communications. Peer Peer Netw Appl, 2015, 8: 1122–1132

    Article  Google Scholar 

  20. Shi Z G, Sun R X, Lu R X, et al. Diverse grouping-based aggregation protocol with error detection for smart grid communications. IEEE Trans Smart Grid, 2015, 6: 2856–2868

    Article  Google Scholar 

  21. Wu J, Dong M X, Ota K, et al. Big data analysis-based secure cluster management for optimized control plane in software-defined networks. IEEE Trans Netw Serv Manage, 2018, 15: 27–38

    Article  Google Scholar 

  22. Zhang X S, Tan Y A, Xue Y, et al. Cryptographic key protection against FROST for mobile devices. Cluster Comput, 2017, 20: 2393–2402

    Article  Google Scholar 

  23. Gao S, Ma X D, Zhu J M, et al. APRS: a privacy-preserving location-aware recommender system based on differentially private histogram. Sci China Inf Sci, 2017, 60: 119103

    Article  Google Scholar 

  24. Mustafa M A, Zhang N, Kalogridis G, et al. Dep2sa: a decentralized efficient privacy-preserving and selective aggregation scheme in advanced metering infrastructure. IEEE Access, 2016, 3: 2828–2846

    Article  Google Scholar 

  25. Wang T, Zeng J D, Bhuiyan M Z A, et al. Trajectory privacy preservation based on a fog structure for cloud location services. IEEE Access, 2017, 5: 7692–7701

    Article  Google Scholar 

  26. Shen H, Zhang M W, Shen J. Efficient privacy-preserving cube-data aggregation scheme for smart grids. IEEE Trans Inf Foren Secur, 2017, 12: 1369–1381

    Article  Google Scholar 

  27. Fouda M M, Fadlullah Z M, Kato N, et al. A lightweight message authentication scheme for smart grid communications. IEEE Trans Smart Grid, 2011, 2: 675–685

    Article  Google Scholar 

  28. Paillier P. Public-key cryptosystems based on composite degree residuosity classes. In: Proceedings of International Conference on Theory and Application of Cryptographic Techniques, 1999. 223–238

    Google Scholar 

  29. Blakley G R. Safeguarding cryptographic keys. In: Proceeding of International Workshop on Managing Requirements Knowledge, 1979. 313–317

    Google Scholar 

  30. Yu Y, Xue L, Au M H, et al. Cloud data integrity checking with an identity-based auditing mechanism from RSA. Future Gener Comput Syst, 2016, 62: 85–91

    Article  Google Scholar 

  31. Bellare M, Garay J A, Rabin T. Fast batch verification for modular exponentiation and digital signatures. In: Proceeding of International Conference on the Theory and Applications of Cryptographic Techniques, 1998. 236–250

    Google Scholar 

  32. Li H W, Lin X D, Yang H M, et al. EPPDR: an efficient privacy-preserving demand response scheme with adaptive key evolution in smart grid. IEEE Trans Paral Distrib Syst, 2014, 25: 2053–2064

    Article  Google Scholar 

  33. Dan B, Lynn B, Shacham H. Short signatures from the weil pairing. In: Proceeding of International Conference on the Theory and Application of Cryptology and Information Security, 2001. 514–532

    Google Scholar 

  34. Failla P. Privacy preserving processing of biometric templates by homomorphic encryption. Dissertation for Ph.D. Degree. Siena: University of Siena, 2011

    Google Scholar 

  35. Lynn B. PBC: the pairing-based cryptography library. Version 0.5.14, 2013. http://crypto.stanford.edu/pbc/

    Google Scholar 

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Acknowledgements

This work was partially supported by Beijing Natural Science Foundation (Grant No. 4182060), and Fundamental Research Funds for the Central Universities (Grant No. 2018ZD06).

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Correspondence to Liehuang Zhu.

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Guan, Z., Zhang, Y., Zhu, L. et al. EFFECT: an efficient flexible privacy-preserving data aggregation scheme with authentication in smart grid. Sci. China Inf. Sci. 62, 32103 (2019). https://doi.org/10.1007/s11432-018-9451-y

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  • DOI: https://doi.org/10.1007/s11432-018-9451-y

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