Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Balanced anonymity and traceability for outsourcing small-scale data linear aggregation in the smart grid

  • Author(s): Huaqun Wang 1, 2 ; Debiao He 3 ; Shibing Zhang 4
    • View affiliations
    • Affiliations: 1: State Key Laboratory of Cryptology, Beijing 100878, People's Republic of China ;
      2: School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, People's Republic of China ;
      3: State Key Laboratory of Software Engineering, Computer School, Wuhan University, Wuhan 430072, People's Republic of China ;
      4: School of Electronic and Information, Nantong University, Nantong 226019, People's Republic of China
  • Source: Volume 11, Issue 3, May 2017, p. 131 – 138
    DOI:  10.1049/iet-ifs.2016.0150 , Print ISSN 1751-8709, Online ISSN 1751-8717
© The Institution of Engineering and Technology
Received 24/03/2016, Accepted 19/06/2016, Revised 18/05/2016, Published 22/06/2016

Along with the development of information technology, the traditional electrical grid is moving to smart grid technology. By using the smart grid, the users and utility providers can more efficiently manage and generate power. Along with the advantages, the smart grid is also faced with new security concerns. In the smart grid, the user's citizen identity information should be preserved and the offensive user should be traced. For some low-capacity devices, it is indispensable to perform complicated computation by using outsourcing computation. The authors provide the outsourcing computation through public cloud. Anonymity and traceability are two important security properties in the smart grid. They are the unity of opposites. On the basis of the security requirements, they propose the balanced anonymity and traceability for outsourcing small-scale data linear aggregation (BAT-LA) in the smart grid. The formal definition, system model and security model are presented. Then, a concrete BAT-LA protocol is designed by using the elliptic curve cryptography and proxy re-encryption. Through security analysis and performance analysis, the designed BAT-LA protocol is provably secure and efficient.

Inspec keywords: public key cryptography; smart power grids; power engineering computing

Other keywords: balanced traceability; outsourcing small-scale data linear aggregation; security properties; elliptic curve cryptography; outsourcing computation; security model; BAT-LA protocol; balanced anonymity; proxy reencryption; public cloud; smart grid technology; formal definition; information technology

Subjects: Power systems; Data security; Power engineering computing; Cryptography

References

    1. 1)
      • 1. McDaniel, P., McLaughlin, S.: ‘Security and privacy challenges in the smart grid’, IEEE Secur. Priv., 2009, 7, (3), pp. 75–77.
    2. 2)
      • 18. Mambo, M., Usuda, K., Okamoto, E.: ‘Proxy signature for delegating signing operation’. CCS 1996, 1996, pp. 48–C57.
    3. 3)
      • 21. Lee, M.Z., Dunn, A.M., Waters, B., et al: ‘Anon-Pass: practical anonymous subscriptions’. IEEE Symp. on Security and Privacy, 2013, pp. 319–333.
    4. 4)
      • 27. Bernstein, D.J., Lange, T.: ‘Computing small discrete logarithms faster’. INDOCRYPT 2012, 2012, (LNCS 7668), pp. 317–338.
    5. 5)
      • 22. Wang, H., Qin, B., Wu, Q., et al: ‘TPP: Traceable privacy-preserving communication and precise reward for vehicle-to-grid networks in smart grids’, IEEE Trans. Inf. Forensics Sec., 2015, 10, (11), pp. 2340–2351.
    6. 6)
      • 3. Alharbi, K., Lin, X., Shao, J.: ‘A framework for privacy-preserving data sharing in the smart grid’. ICCC 2014, 2014, pp. 214–219.
    7. 7)
      • 7. Rial, A., Danezis, G.: ‘Privacy-preserving smart metering’. WPES, 2011, pp. 49–60.
    8. 8)
      • 17. Wang, J., Chen, X., Huang, X., et al: ‘Verifiable auditing for outsourced database in cloud computing’, IEEE Trans. Comput., doi: 10.1109/TC.2015.2401036.
    9. 9)
      • 28. Rottondi, C., Verticale, G., Krauss, C.: ‘Distributed privacy-preserving aggregation of metering data in smart grids’, IEEE J. Sel. Areas Commun., 2013, 31, (7), pp. 1342–1354.
    10. 10)
      • 24. Shen, J., Tan, H., Wang, J., et al: ‘A novel routing protocol providing good transmission reliability in underwater sensor networks’, J. Internet Technol., 2015, 16, (1), pp. 171–178.
    11. 11)
      • 25. Menezes, A.J., Van Oorschot, P.C., Vanstone, S.A.: ‘Handbook of applied cryptography’ (CRC Press, Boca Raton, FL, USA, 1997).
    12. 12)
      • 11. Yu, C.M., Chen, C.Y., Chao, H.C.: ‘Privacy-preserving multi-keyword similarity search over outsourced cloud data’, IEEE Syst. J., doi: 10.1109/JSYST.2015.2402437.
    13. 13)
      • 8. Gennaro, R., Gentry, C., Parno, B.: ‘Non-interactive verifiable computing: Outsourcing computation to untrusted workers’. CRYPTO, 2010, (LNCS 6223), pp. 465–482.
    14. 14)
      • 9. Ma, X., Li, J., Zhang, F.: ‘Outsourcing computation of modular exponentiations in cloud computing’, Cluster Comput.., 2013, 16, (4), pp. 787–796.
    15. 15)
      • 12. Lai, J., Deng, R.H., Guan, C., et al: ‘Attribute-based encryption with verifiable outsourced decryption’, IEEE Trans. Inf. Forensics Sec., 2013, 8, (8), pp. 1343–1354.
    16. 16)
      • 6. Erkin, Z., Veugen, T.: ‘Privacy enhanced personal services for smart grids’. SEGS, 2014, pp. 7–12.
    17. 17)
      • 4. Birman, K., Jelasity, M., Kleinberg, R., et al: ‘Building a secure and privacy-preserving smart grid’, ACM SIGOPS Oper. Syst. Rev., 2015, 49, (1), pp. 131–136.
    18. 18)
      • 5. Nicanfar, H., TalebiFard, P., Hosseininezhad, S., , C.M., et al: ‘Security and privacy of electric vehicles in the smart grid context: problem and solution’. DIVANet, 2013, pp. 45–54.
    19. 19)
      • 20. Hohenberger, S., Myers, S., Pass, R., et al: ‘ANONIZE: A large-scale anonymous survey system’. IEEE Symp. on Security and Privacy, 2014, pp. 375–389.
    20. 20)
      • 26. Boneh, D., Goh, E.J., Nissim, K.: ‘Evaluating 2-DNF formulas on ciphertexts’. Theory of Cryptography, 2015, (LNCS 3378), pp. 325–341.
    21. 21)
      • 16. Ren, Y., Shen, J., Wang, J., et al: ‘Mutual verifiable provable data auditing in public cloud storage’, J. Internet Technol., 2015, 16, (2), pp. 317–C323.
    22. 22)
      • 2. Nejad, M.F., Saberian, A.M., Hizam, H., et al: ‘Application of smart power grid in developing countries’. PEOCO 2013, 2013, pp. 427–431.
    23. 23)
      • 15. Fu, Z., Sun, X., Liu, Q., et al: ‘Achieving efficient cloud search services: multi-keyword ranked search over encrypted cloud data supporting parallel computing’, IEICE Trans. Commun., 2015, E98-B, (1), pp. 190–200.
    24. 24)
      • 13. Li, L., Lu, R., Huang, C.: ‘EPLQ: Efficient privacy-preserving location-based query over outsourced encrypted data’, IEEE Internet Things J., doi: 10.1109/JIOT.2015.2469605.
    25. 25)
      • 19. Li, K., Wang, J., Zhang, Y., et al: ‘Key policy attribute-based proxy re-encryption and RCCA secure scheme’, J. Internet Serv. Inf. Secur., 2014, 4, (2), pp. 70–82.
    26. 26)
      • 10. Li, J., Huang, X., Li, J., et al: ‘Securely outsourcing attribute-based encryption with checkability’, IEEE Trans. Parallel Distrib. Syst., 2014, 25, (8), pp. 2201–2210.
    27. 27)
      • 23. Ma, T., Zhou, J., Tang, M., et al: ‘Social network and tag sources based augmenting collaborative recommender system’, IEICE Trans. Inf. Syst., 2015, E98-D, (4), pp. 902–910.
    28. 28)
      • 29. Leontiadis, I., Molva, R., Onen, M.: ‘Privacy preserving statistics in the smart grid’. ICDCSW, 2014, pp. 182–187.
    29. 29)
      • 14. Lei, X., Liao, X., Huang, T., et al: ‘Outsourcing large matrix inversion computation to a public cloud’, IEEE Trans. Cloud Comput., 2013, 1, (1), pp. 78–87.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-ifs.2016.0150
Loading

Related content

content/journals/10.1049/iet-ifs.2016.0150
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
Print this page
This is a required field
Please enter a valid email address