Skip to main content
Log in

Towards a set aggregation-based data integrity scheme for smart grids

  • Published:
Annals of Telecommunications Aims and scope Submit manuscript

Abstract

Data aggregation (DA) is the process of combining smart metering data so that it can be sent to a control center in package form rather than as individual data points. Smart metering data represents sensitive information that must be protected during the aggregation process. Traditional data aggregation schemes have addressed privacy issues based primarily on computationally expensive homomorphic encryption. In contrast, this paper presents a novel method based on hash chaining to verify the integrity of a set of aggregated data. This scheme divides the user’s data into two diverse groups. It also enables the control center to collect more fine-grained data aggregation results at a reduced cost. In addition, the proposed scheme ensures data integrity by maintaining a hash chain and assigning new values in the hash chain by XORing previous hash values with the current hash value. The proposed scheme is evaluated in terms of computational cost and communication overhead. A comparative analysis of our proposed methodology with existing aggregation schemes regarding computational cost and communication overhead illustrates the optimality of our proposed scheme.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Java Cryptography Architecture (JCA). http://docs.oracle.com/javase/7/docs/technotes/guides/security/crypto/CryptoSpec.html#KeyGeneratorvisitedon11-03-2016

  2. Abdallah A, Shen X (2016) A lightweight lattice-based homomorphic privacy-preserving data aggregation scheme for smart grid. IEEE Trans Smart Grid PP(99) https://doi.org/10.1109/TSG.2016.2553647

  3. Abdullah MDH, Welch I, Seah WK (2013) Efficient and secure data aggregation for smart metering networks. In: 2013 IEEE eight international Conference on Intelligent Sensors, Sensor Networks and Information Processing. IEEE, pp 71–76

  4. Alharbi K, Lin X (2012) LPDA: A lightweight privacy-preserving data aggregation scheme for smart grid. In: 2012 international conference on wireless communications & signal processing (WCSP). IEEE, pp 1–6

  5. Ambrosin M, Hosseini H, Mandal K, Conti M, Poovendran R (2016) Despicable me(ter): anonymous and fine-grained metering data reporting with dishonest meters. In: 2016 IEEE conference on communications and network security (CNS), pp 163–171

    Chapter  Google Scholar 

  6. Bao H, Chen L (2015) A lightweight privacy-preserving scheme with data integrity for smart grid communications. Concurrency and Computation: Practice and Experience

  7. Bao H, Lu R (2015) A new differentially private data aggregation with fault tolerance for smart grid communications. J IEEE Internet Things 2(3):248–258

    Article  Google Scholar 

  8. Bao H, Lu R (2017) A lightweight data aggregation scheme achieving privacy preservation and data integrity with di erential privacy and fault tolerance. Peer-to-Peer Netw Appl 10(1):106–121

    Article  Google Scholar 

  9. Bertino E, Yi X, Paulet R (2014) Homomorphic encryption and applications

  10. Chen L, Lu R, Cao Z, AlHarbi K, Lin X (2015) Muda: multi-functional data aggregation in privacy-preserving smart grid communications. Peer-to-Peer Netw Appl 8.5:777–792

  11. Colak I, Sagiroglu S, Fulli G, Yesilbudak M, Covrig CF (2016) A survey on the critical issues in smart grid technologies. Renew Sust Energ Rev 54:396–405

    Article  Google Scholar 

  12. DamgardI J (2001) A generalisation, a simplification and some applications of Paillier’s probabilistic public-key system. In: Proceedings of the 4th International Workshopx on Practice and Theory in Public Key Cryptosystems

    Google Scholar 

  13. Doh I, Lim J, Chae K (2013) Secure aggregation and attack detection for smart grid system. In: 2013 16th international conference on network-based information systems (NBis). IEEE, pp 270– 275

  14. Farhangi H (2010) The path of the smart grid. IEEE Power and Energy Magazine 8(1):18–28

    Article  MathSciNet  Google Scholar 

  15. Ferrag MA (2017) EPEC: an efficient privacy-preserving energy consumption scheme for smart grid communications. Telecommun. Syst:1–18. https://doi.org/10.1007/s11235-017-0315-2

  16. Fu Z, Wu X, Guan C, Sun X, Ren K (2016) Toward efficient multi-keyword fuzzy search over encrypted outsourced data with accuracy improvement. IEEE Trans Inf Forensics Secur 11(12):2706–2716

    Article  Google Scholar 

  17. Garcia FD, Jacobs B (2011) Privacy-friendly energy-metering via homomorphic encryption. In: Security and trust management. Springer, pp 226–238

  18. Gupta B, Agrawal DP, Yamaguchi S (2016) Handbook of research on modern crypto-graphic solutions for computer and cyber security IGI Global

  19. He D, Kumar N, Lee JH (2016) Privacy-preserving data aggregation scheme against internal attackers in smart grids. Wirel Netw 22(2):491–502

    Article  Google Scholar 

  20. Hoglund R, Tiloca M (2015) Current state of the art in smart metering security

  21. Kumar V, Madria S (2012) Secure hierarchical data aggregation in wireless sensor networks: performance evaluation and analysis. In: 2012 IEEE 13th international conference on mobile data management (MDM). IEEE, pp 196–201

  22. Lu R, Alharbi K, Lin X, Huang C (2015) A novel privacy-preserving set aggregation scheme for smart grid communications. In: 2015 IEEE Global Communications Conference (GLOBECOM). IEEE, pp 1–6

  23. Li F, Luo B (2012) Preserving data integrity for smart grid data aggregation. In: 2012 IEEE third international conference on Smart Grid Communications (smartgridcomm). IEEE, pp 366–371

  24. Li J, Li J, Chen X, Jia C, Lou W (2015) Identity-based encryption with outsourced revocation in cloud computing. IEEE Trans Comput 64(2):425–437

    Article  MathSciNet  MATH  Google Scholar 

  25. Li C, Lu R, Li H, Chen L, Chen J (2015) PDA: A privacy-preserving dual-functional aggregation scheme for smart grid communications security and communication Net- works

  26. Lu R, Liang X, Li X, Lin X, Shen X (2012) EPPA: An efficient and privacy-preserving ag- gregation scheme for secure smart grid communications. IEEE Trans Parallel Distrib Syst 23(9):1621–1631

    Article  Google Scholar 

  27. Memos VA, Psannis KE, Ishibashi Y, Kim BG, Gupta B (2017) An efficient algorithm for media-based surveillance system (EAMSus) in IoT Smart City framework Future Generation Computer Systems

  28. Menezes AJ, Van Oorschot PC, Vanstone SA (1996) Handbook of applied cryptography. CRC Press

  29. Mustafa MA, Zhang N, Kalogridis G, Fan Z (2015) MUSP: Multi-Service, user self- controllable and privacy-preserving system for smart metering. In: 2015 IEEE International Conference on Communications (ICC). IEEE, pp 788–794

  30. Ni J, Zhang K, Alharbi K, Lin X, Zhang N, Shen X (2017) Differentially private smart metering with fault tolerance and range-based ltering. IEEE Trans Smart Grid pp(99):1–1

    Google Scholar 

  31. Paillier P (1999) Public-key cryptosystems based on composite degree residuosity classes. In: Advances in Cryptology EUROCRYPT’99. Springer, pp 223–238

  32. Saputro N, Akkaya K (2012) Performance evaluation of smart grid data aggregation via homomorphic encryption. In: 2012 IEEE on wireless communications and networking conference (WCNC). IEEE, pp 2945–2950

  33. Shen H, Zhang M, Shen J (2017) Efficient privacy-preserving cube-data aggregation scheme for smart grids. IEEE Trans Inf Forensics Secur 12(6):1369–1381

    Article  Google Scholar 

  34. Shi E, Chan THH, Rieffel EG, Chow R, Song D (2011) Privacy-preserving aggregation of time-series data

  35. Tonyali S, Akkaya K, Saputro N, Uluagac AS, Nojoumian M (2017) Privacy-preserving protocols for secure and reliable data aggregation in IoT-enabled smart metering systems. Futur Gener Comput Syst https://doi.org/10.1016/j.future.2017.04.031

  36. Wang H, Wang Z, Domingo-Ferrer J (2017) Anonymous and secure aggregation scheme in fog-based public cloud computing. Futur Gener Comput Syst pp

  37. Zhang J, Liu L, Cui Y, Chen Z (2013) SP2DAS: self-certified PKC-based privacy-preserving data aggregation scheme in smart grid. Int J Distrib Sens Netw 9(1):457325

Download references

Acknowledgments

The authors would like to thank the COMSATS Institute of Information Technology and the Higher Education Commission of Pakistan for their support and encouragement.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Abid Khan.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tahir, M., Khan, A., Hameed, A. et al. Towards a set aggregation-based data integrity scheme for smart grids. Ann. Telecommun. 72, 551–561 (2017). https://doi.org/10.1007/s12243-017-0602-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12243-017-0602-7

Keywords

Navigation