PrivacyPreserving MultiFunctional Data Aggregation  Without TTP in Smart Grid

Abstract

Abstract: In the smart grid, residents electricity usage needs to be periodically measured and reported for the purpose of better energy management. However, many studies have shown that realtime collection of residents electricity consumption may unfavorably incur privacy leakage. Most existing work is based on trusted third party (TTP), but this approach introduces large computational overhead. In this paper, we construct a new scheme which utilizes Shamirs secret sharing to allow smart meters to negotiate aggregation parameters in the absence of a TTP. This scheme efficiently supports multifunctional aggregation of the electricity readings and simultaneously preserves residents privacy. Theoretical analysis of this scheme is provided with regard to security and efficiency. Moreover, experimental data obtained from a prototype indicates that our proposal is efficient and feasible for practical deployment.

Key words: data aggregation, smart grid, privacy preserving, multifunctional computation, security analysis

摘要： 智能电网中，居民的用电量数据会被周期性地测量和上报，以便控制中心更方便地进行电力管理.然而，当前许多研究表明，实时收集用户用电量并进行数据聚合可能导致用户的隐私泄露.多数现有工作基于可信第三方进行研究，然而该方法带来较大的计算开销.利用Shamir秘密共享的思想来实现智能电表间自主协商聚合参数，无需引入可信第三方.支持多种用电量数据的聚合方式，同时能够保护用户的隐私.通过分析，本方案能够兼顾安全性和效率，实验表明，方案效率较高且易于在实践中部署.

关键词: 数据聚合, 智能电网, 隐私保护, 多方计算, 安全分析

贺铮张伟林东岱. 智能电网中无需可信第三方的隐私保护数据聚合方案[J]. 信息安全研究, 2019, 5(12): 1059-1067.

References

[1] Efthymiou C, Kalogridis G. Smart grid privacy via anonymization of smart metering data [C] //First IEEE Int Conf on Smart Grid Communications. IEEE, 2010: 238-243 [2] Li Xu, Liang Xiaohui, Lu Rongxing, et al. Securing smart grid: cyber attacks, countermeasures, and challenges [J]. IEEE Communications Magazine, 2012, 50(8): 38-45 [3] Lu Rongxing, Heung K, Lashkari A H, et al. A lightweight privacy-preserving data aggregation scheme for fog computing-enhanced IoT [J]. IEEE Access, 2017(2), 5: 3302-3312 [4] Fan C, Huang S, Lai Y. Privacy-enhanced data aggregation scheme against internal attackers in smart grid [J]. IEEE Trans on Industrial informatics, 2014, 10(1): 666-675 [5] Jia Weiwei, Zhu Haojin, Cao Zhenfu, et al. Human-factor-aware privacy-preserving aggregation in smart grid [J]. IEEE Systems Journal, 2014, 8(2): 598-607 [6] Lu Zhuo, Lu Xiang, Wang Wenye, et al. Review and evaluation of security threats on the communication networks in the smart grid [C] // 2010 Military Communications Conf. IEEE, 2010: 1830-1835 [7] Li Hongwei, Lin Xiaodong, Yang Haomiao, et al. EPPDR: an efficient privacy-preserving demand response scheme with adaptive key evolution in smart grid [J]. IEEE Trans on Parallel and Distributed Systems, 2014, 25(8): 2053-2064 [8] Lin H, Tzeng W, Shen S, et al. A practical smart metering system supporting privacy preserving billing and load monitoring [C] // Int Conf on Applied Cryptography and Network Security. Berlin, Heidelberg: Springer, 2012: 544-560 [9] Lu Rongxing, Liang Xiaohui, Li Xu, et al. Eppa: An efficient and privacy-preserving aggregation scheme for secure smart grid communications [J]. IEEE Trans on Parallel and Distributed Systems, 2012, 23(9): 1621-1631 [10] Shi Zhiguo, Sun Ruixue, Lu Rongxing, et al. Diverse grouping-based aggregation protocol with error detection for smart grid communications [J]. IEEE Trans on Smart Grid, 2015, 6(6): 2856-2868 [11] Li Fengjun, Luo Bo, Liu Peng. Secure information aggregation for smart grids using homomorphic encryption [C] //First IEEE Int Conf on Smart Grid Communications. IEEE, 2010: 327-332 [12] Paillier P. Public-key cryptosystems based on composite degree residuosity classes [C] //Int Conf on the Theory and Applications of Cryptographic Techniques. Berlin, Heidelberg: Springer, 1999: 223-238 [13] ElGamal T. A public key cryptosystem and a signature scheme based on discrete logarithms [J]. IEEE trans on Information Theory, 1985, 31(4): 469-472 [14] Boneh D, Goh E, Nissim K. Evaluating 2-DNF formulas on ciphertexts [C] //Theory of Cryptography Conf. Berlin, Heidelberg: Springer,2005: 325-341 [15] Shi E, Chan H, Rieffel E, et al. Privacy-preserving aggregation of time-series data [C] //Annual Network & Distributed System Security Symp. Internet Society, 2011 [16] Bohli J M, Sorge C, Ugus O. A privacy model for smart metering [C] //Int Conf on Communications Workshops. IEEE, 2010: 1-5 [17] Garcia F, Jacobs B. Privacy-friendly energy-metering via homomorphic encryption [C] //Int Workshop on Security and Trust Management. Berlin, Heidelberg: Springer, 2010: 226-238 [18] Tsang P, Au M, Kapadia A, et al. PEREA: Towards practical TTP-free revocation in anonymous authentication [C] //Proc of the 15th ACM conf on Computer and communications security. ACM, 2008: 333-344 [19] Jung T, Li X, Wan M. Collusion-tolerable privacy-preserving sum and product calculation without secure channel [J]. IEEE Trans on Dependable and secure computing, 2015, 12(1): 45-57 [20] Ni Jianbing, Zhang Kuan, Lin Xiaodong, et al. EDAT: Efficient data aggregation without TTP for privacy-assured smart metering [C] // Int Conf on Communications. IEEE, 2016: 1-6 [21] Datta A, Joye M. Cryptanalysis of a privacy-preserving aggregation protocol [J]. IEEE Trans on Dependable and Secure Computing, 2017, 14(6): 693-694 [22] Chen Le, Lu Rongxing, Cao Zhenfu, et al. MuDA: Multifunctional data aggregation in privacy-preserving smart grid communications [J]. Peer-to-peer networking and applications, 2015, 8(5): 777-792 [23] Shamir A. How to share a secret [J]. Communications of the ACM, 1979, 22(11): 612-613 [24] Katz J, Menezes A, Van O, et al. Handbook of applied cryptography [M]. Boca Raton: CRC press, 1996 [25] Pointcheval D, Stern J. Security proofs for signature schemes [C] //Int Conf on the Theory and Applications of Cryptographic Techniques. Berlin, Heidelberg: Springer, 1996: 387-398