A Lightweighted Secure Scheme for Data ‎Aggregation in Large-Scale IoT-Based ‎Smart Grids ‎

Document Type : Computer and Network Security-Ghaemi

Authors

1 Department of Electrical and Computer Engineering, University of Kurdistan, Sanandaj, Iran‎

2 Department of Electrical and Computer Engineering, University of Kurdistan, Sanandaj, Iran;

Abstract

With the emergence of IoT devices, data aggregation in the area of smart grids can be implemented based on IoT networks. However, the communication and computation resources of IoT devices are limited so it is not possible to apply conventional Internet protocols directly. On the other hand, gathering data of smart meters in the advanced metering infrastructure faces challenges such as privacy-preserving and heavy-loaded authentication and aggregation schemes. In this paper, we propose an improved lightweight, secure, and privacy-preserving scheme for aggregating data from smart meters in large-scale IoT-based smart grids. The proposed scheme adopts light-weight cryptography operations such as exclusive-OR, hash, and concatenation functions. In comparison with the schemes in the literature, the analysis and simulation results show that the proposed scheme satisfies the same security levels, while at the same time burdens lower computation and communication overheads. This observation makes the proposed scheme more suitable to be employed in large-scale and IoT-based smart grids for data aggregation.

Keywords

Main Subjects


[1]           IoT Analytics, “Why the internet of things is called internet of things: definition, history, disambiguation,” https://iot-analytics.com/internetof-things-definition, 2014.
[2]           M. A. Ferrag, L. A. Maglaras, H. Janicke, J. Jiang, L. Shu, “Authentication protocols for internet of things: A Comprehensive Survey”, Hindawi, Security and Communication Networks, vol. 2017, Article ID 6562953.
[3]           G. Gharepatyan, M. Shahidehpour and B. Zaker, Smart Grids and Microgrids, Tehran: Amirkabir University of Technology, 2019.
[4]           N. Saxena, B. J. Choi, and R. Lu, “Authentication and authorization scheme for various user-roles and devices in smart grid,” IEEE Trans. on Information Forensics and Security, vol. 11, pp. 907-921, May 2016
[5]           E. Kabalci, Y. Kabalci, Smart Grids and Their Communication Systems, Singapure: Springer, 2019
[6]           J. Zhang, Y. Zhao, J. Wu, and B. Chen, “A lightweight privacy-preserving data aggregation scheme for edge computing,” in 15th International Conference on Mobile Ad-hoc and Sensor Systems, October 2018.
[7]           H. Shen, M. Zhang and J. Shen, "Efficient Privacy-Preserving Cube-Data Aggregation Scheme for Smart Grids," IEEE Trans. on Information Forensics and Security, vol. 12, pp. 1369-1381, 2017.
[8]           Z. He, Sh. Pan, D. Lin, “PMDA: privacy-preserving multi-functional data aggregation without TTP in smart grid,” in 17th IEEE International Conference on Trust, Security and Privacy In Computing and Communications, 2018
[9]           R. Lu, X. Liang, X. Li and X. Shen, “EPPA: an efficient privacy-preserving aggregation scheme for secure smart grid communications,” IEEE Trans. on Parallel Distribution Systems, vol. 23, pp. 1621-1631, September 2012.
[10]         S. Li, K. Xue, Q. Yang and H. Peilin, "PPMA: Privacy-Preserving Multisubset Data Aggregation in Smart Grid," IEEE Trans. on Industrial Informatics , vol. 14, pp. 462-471, 2018.
[11]         Y. Chen, J. Ortega, P. Castillejo and L. Lopez, "A Homomorphic-Based Multiple Data Aggregation Scheme for Smart Grid," IEEE Sensors Journal, vol. 19, pp. 3921-3929, 2019.
[12]         J. H. Jo, S. I. Kim and H. D. Lee, "Efficient and Privacy-Preserving Metering Protocols for Smart Grid Systems," IEEE Trans. on Smart Grids, vol. 7, pp. 1732-1742, 2016.
[13]         A. Abdallah and X. Shen, “A Lightweight Lattice-Based Homomorphic Privacy-Preserving Data Aggregation Scheme for Smart grid,” IEEE Trans. on Smart Grid, vol. 9, pp. 396-405, January 2018.
[14]         M. M. Fouda, Z. M. Fadlullah, N. Kato, R. Lu and X. Shen, “A lightweight message authentication scheme for smart grid communication,” IEEE Trans. on Smart Grid, vol. 2, pp. 675-685, December 2011.
[15]         H. J. Jo, I. S. Kim and D. H. Lee, “Efficient and privacy-preserving metering protocols for smart grid,” IEEE Trans. on Smart Grid, vol. 7, pp. 1732-174, May 2016.
[16]         E.  Vahedi, M. Bayat, M. Pakravan and M. Aref, “Secure ECC-based privacy preserving data aggregation scheme for smart grids,” in Computer Networks, vol. 129, no. 1, pp. 28-36, 2017
[17]         Y. Liu, W. Guo, C. Fan, L. Chang, and C. Cheng. “A practical privacy-preserving data aggregation (3PDA) scheme for smart grid,” IEEE Trans. on Industrial Informatics, vol. 15, pp. 1767-1774, March 2019.
[18]         D. He, N. Kumar, Sh. Zeadally, A. Vinel, L. T. Yang, “Efficient and privacy-preserving data aggregation scheme for smart grid against internal adversaries”, IEEE Trans. on Smart Grids, vol. 8, pp. 2411-2419, 2017
[19]         A. Abdallah and X. Shen, “Lightweight security and privacy preserving scheme for smart grid customer-side networks,” IEEE Trans. on Smart Grids, vol. 8, pp. 1064-1074, May 2017
[20]         M. A. Mustafa, S. Cleemput, A. Aly and A. Abidin, "A Secure and Privacy-Preserving Protocol for Smart Metering Operational Data Collection," IEEE Trans. on Smart Grids, vol. 10, pp. 6481-6490, 2019.
[21]         F. Knirsch, G. Eibl and D. Engel, "Error-Resilient Masking Approaches for Privacy Preserving Data Aggregation," IEEE Trans. on Smart Grid, vol. 9, pp. 3351-3361, 2018.
[22]         P. Gope and B. Sikdar, “Lightweight and privacy-friendly spatial data aggregation for secure power supply and demand management in smart grids,” IEEE Trans. on Infornation Forensics and Security, vol. 14, pp. 1554-1566, June 2019.
[23]         F. Maqsood, M. Ahmed, M. M. Ali and M. A. Shah, “Cryptography: a comparative analysis for modern techniques”, International Journal of Advanced Computer Science and Applications, vol. 8, Issue 6, 2017
[24]         H. Gilbert and H. Handschus, “Security analysis of SHA-256 and sisters”, Internationatl Workshop on Selected Areas in Cryptography, Springer, SAC 2003, pp. 175-193.
[25]         J. So, C. He, C. Yang, S. Li, Q. Yu, R. E. Ali, B. Guler and S. Avestimehr, “LightSecAgg: a lightweight and versatile design for secure aggregation in federated learning”, in Proceedings of Machine Learning and Systems, vol. 4, pp. 694-720, 2022.
[26]         M. Zhang, Y. Li, Y. Ding, and B. Yang, “A Lightweight and Robust Multi-Dimensional Data Aggregation Scheme for IoT”, IEEE Internet of Things Journal, vol. 1, no. 1, pp. 1-1, 2023
[27]         J. Qian, Z. Cao, X. Dong, J. Shen, Z. Liu, and Y. Ye, "Two Secure and Efficient Lightweight Data Aggregation Schemes for Smart Grid," IEEE Trans. on Smart Grid, vol. 12, no. 3, pp. 2625-2637, May 2021
[28]         Junhua Wu, Zhuqing Xu, Guangshun Li, Cang Fan, Zhenyu Jin, Yuanwang Zheng, "E-LPDAE: An Edge-Assisted Lightweight Power Data Aggregation and Encryption Scheme", Security and Communication Networks, vol. 2022, Article ID 6218094, 12 pages, 2022
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