ABSTRACT
Smart metering is considered as a key feature of smart grid network. It provides a high frequency two-way communication between the electricity consumer and the utility provider. However, as useful as the collection of fine-grained consumption measurements for the utility provider, it also puts the consumer privacy in risk by exposing sensitive personal information. In this paper, we present a summary of the existing state of the art of privacy-preserving smart metering. Specifically, we review 27 papers related to privacy preservation approaches for advanced metering infrastructure networks which were published in recent years. Hence, we provide a detailed classification of these studies, then we give a brief description of each paper as well as its limitations and finally we conclude the paper and explore some future research directions.
- S. Afrin and S. Mishra. 2016. September). An anonymized authentication framework for smart metering data privacy. In IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT) (September 2016), 1–5.Google Scholar
- A. Alabdulatif, H. Kumarage, I. Khalil, M. Atiquzzaman, and X. Yi. 2017. Privacy-preserving cloud-based billing with lightweight homomorphic encryption for sensor-enabled smart grid infrastructure. IET Wireless Sensor Systems 7, 6 (2017), 182–190.Google ScholarCross Ref
- A. Alsharif, M. Nabil, M. Mahmoud, and M. Abdallah. 2018. In Privacy-preserving collection of power consumption data for enhanced AMI networks. In25th International Conference on Telecommunications (ICT). IEEE, 196–201.Google Scholar
- M. Ambrosin, H. Hosseini, K. Mandal, M. Conti, and R. Poovendran. 2016. Despicable me (ter): Anonymous and fine-grained metering data reporting with dishonest meters. In IEEE conference on communications and network security (CNS). IEEE, 163–171.Google Scholar
- M. R. Asghar, G. Dán, D. Miorandi, and I. Chlamtac. 2017. Smart meter data privacy: A survey. IEEE Communications Surveys & Tutorials 19, 4 (2017), 2820–2835.Google ScholarCross Ref
- M. Backes and S. Meiser. 2013. Differentially private smart metering with battery recharging. In Data Privacy Management and Autonomous Spontaneous Security. Springer, Heidelberg - Berlin, 194–212.Google Scholar
- M. F. Balli, S. Uludag, A. A. Selcuk, and B. Tavli. 2018. Distributed Multi-Unit Privacy Assured Bidding (PAB) for Smart Grid Demand Response Programs. in IEEE Transactions on Smart Grid 9, 5 (September 2018), 4119–4127. https://doi.org/10.1109/TSG.2017.2651029Google ScholarCross Ref
- P. Barbosa, A. Brito, H. Almeida, and S. Clauß. 2014. Lightweight privacy for smart metering data by adding noise. Proceedings of the 29th Annual ACM Symposium on Applied Computing, 531–538.Google Scholar
- J. M. Bohli, C. Sorge, and O. Ugus. 2010. A privacy model for smart metering. In Conference on Communications Workshops. IEEE, 1–5.Google Scholar
- A. Braeken, P. Kumar, and A. Martin. 2018. Efficient and privacy-preserving data aggregation and dynamic billing in smart grid metering networks. Energies 11, 8 (2018), 2085.Google ScholarCross Ref
- H. Cao, S. Liu, L. Wu, Z. Guan, and X. Du. 2019. Achieving differential privacy against non‐intrusive load monitoring in smart grid: A fog computing approach. Concurrency and Computation: Practice and Experience 31 (2019), 22.Google ScholarCross Ref
- S. Desai, R. Alhadad, N. Chilamkurti, and A. Mahmood. 2019. A survey of privacy preserving schemes in IoE enabled Smart Grid Advanced Metering Infrastructure. Cluster Computing 22, 1 (2019), 43–69.Google ScholarDigital Library
- T. Dimitriou, T. Giannetsos, and L. Chen. 2019. REWARDS: Privacy-preserving rewarding and incentive schemes for the smart electricity grid and other loyalty systems. Computer Communications 137 (2019), 1–14.Google ScholarDigital Library
- T. Dimitriou and G. O. Karame. 2017. Enabling Anonymous Authorization and Rewarding in the Smart Grid. IEEE Transactions on Dependable and Secure Computing 14, 5 (2017), 565–572.Google ScholarDigital Library
- T. Eccles and B. Halak. 2017. A Secure and Private Billing Protocol for Smart Metering. IACR Cryptol. ePrint Arch(2017), 654.Google Scholar
- C. Efthymiou and G. Kalogridis. 2010. Smart grid privacy via anonymization of smart metering data. IEEE international conference on smart grid communications, 238–243.Google Scholar
- C. Efthymiou and G. Kalogridis. 2010. Smart grid privacy via anonymization of smart metering data. IEEE international conference on smart grid communications, 238–243.Google Scholar
- M. A. Ferrag, L. A. Maglaras, H. Janicke, J. Jiang, and L. Shu. 2018. A systematic review of data protection and privacy preservation schemes for smart grid communications. Sustainable cities and society 38 (2018), 806–835.Google Scholar
- S. Finster and I. Baumgart. 2015. Privacy-aware smart metering: A survey. IEEE communications surveys & tutorials 17, 2 (2015), 1088–1101.Google Scholar
- A. Ghosal and M. Conti. 2019. Key management systems for smart grid advanced metering infrastructure: A survey. IEEE Communications Surveys & Tutorials 21, 3 (2019), 2831–2848.Google ScholarCross Ref
- Y. Gong, Y. Cai, Y. Guo, and Y. Fang. 2015. A privacy-preserving scheme for incentive-based demand response in the smart grid. IEEE Transactions on Smart Grid 7, 3 (2015), 1304–1313.Google ScholarCross Ref
- P. Gope and B. Sikdar. 2018. Lightweight and privacy-friendly spatial data aggregation for secure power supply and demand management in smart grids. IEEE Transactions on Information Forensics and Security 14, 6(2018), 1554–1566.Google ScholarCross Ref
- R. Gopinath, M. Kumar, C. P. C. Joshua, and K. Srinivas. 2020. Energy management using non-intrusive load monitoring techniques-State-of-the-art and future research directions. Sustainable Cities and Society 102411 (2020).Google Scholar
- Matthew B Gough, Sérgio F Santos, Tarek AlSkaif, Mohammad S Javadi, Rui Castro, and João PS Catalão. 2021. Preserving privacy of smart meter data in a smart grid environment. IEEE Transactions on Industrial Informatics 18, 1 (2021), 707–718.Google ScholarCross Ref
- L. Grassi, D. Khovratovich, C. Rechberger, A. Roy, and M. Schofnegger. 2020. Poseidon: A new hash function for zero-knowledge proof systems. In Proceedings of the 30th USENIX Security Symposium. USENIX Association.Google Scholar
- Mahmoud M. Fouda M. M. Alsolami F. Alasmary W. & Shen X. Ibrahem, M. I.2021. Privacy Preserving and Efficient Data Collection Scheme for AMI Networks Using Deep Learning. IEEE Internet of Things Journal 8, 23 (2021), 17131–17146.Google ScholarCross Ref
- M. Jawurek, M. Johns, and F. Kerschbaum. 2011. Plug-in privacy for smart metering billing., Springer (Ed.). In International Symposium on Privacy Enhancing Technologies Symposium, Heidelberg - Berlin, 192–210.Google Scholar
- M. Jawurek, M. Johns, and K. Rieck. 2011. Smart metering de-pseudonymization.In Proceedings of the 27th annual computer security applications conference (December 2011), 227–236.Google Scholar
- A. S. Khwaja, A. Anpalagan, M. Naeem, and B. Venkatesh. 2020. Smart Meter Data Obfuscation Using Correlated Noise. IEEE Internet of Things Journal 7, 8 (2020), 7250–7264.Google ScholarCross Ref
- F. Knirsch, A. Unterweger, M. Unterrainer, and D. Engel. 2020. Comparison of the Paillier and ElGamal Cryptosystems for Smart Grid Aggregation Protocols. In ICISSP (2020), 232–239.Google Scholar
- M. LeMay, G. Gross, C. A. Gunter, and S. Garg. 2007. Unified architecture for large-scale attested metering, IEEE (Ed.). In 40th Annual Hawaii International Conference on System Sciences (HICSS’07)., 115–115.Google Scholar
- Y. Liu, W. Guo, C. I. Fan, L. Chang, and C. Cheng. 2018. A practical privacy-preserving data aggregation (3PDA) scheme for smart grid. IEEE Transactions on Industrial Informatics 15, 3 (2018), 1767–1774.Google ScholarCross Ref
- M. A. Mustafa, S. Cleemput, A. Aly, and A. Abidin. 2019. A secure and privacy-preserving protocol for smart metering operational data collection. IEEE Transactions on Smart Grid 10, 6 (2019), 6481–6490.Google ScholarCross Ref
- R. Petrlic. 2010. A privacy-preserving concept for smart grids. Sicherheit in vernetzten Systemen 18 (2010), B1–B14.Google Scholar
- M. S. Rahman, A. Basu, S. Kiyomoto, and M. A. Bhuiyan. 2017. Privacy-friendly secure bidding for smart grid demand-response. Information Sciences 379(2017), 229–240.Google ScholarCross Ref
- R. B. Romdhane, H. Hammami, M. Hamdi, and T. H. Kim. 2019. At the cross roads of lattice-based and homomorphic encryption to secure data aggregation in smart grid. In 15th International Wireless Communications & Mobile Computing Conference (IWCMC) (). IEEE (June 2019), 1067–1072.Google ScholarCross Ref
- R. B. Romdhane, H. Hammami, M. Hamdi, and T. H. Kim. 2019. A novel approach for privacy-preserving data aggregation in smart grid. In 15th International Wireless Communications & Mobile Computing Conference (IWCMC) (). IEEE (June 2019), 1060–1066.Google ScholarCross Ref
- H. Souri, A. Dhraief, S. Tlili, K. Drira, and A. Belghith. 2014. Smart metering privacy-preserving techniques in a nutshell. Procedia Computer Science 32 (2014), 1087–1094.Google ScholarCross Ref
- S. Sultan. 2019. Privacy-preserving metering in smart grid for billing, operational metering, and incentive-based schemes: A survey. Computers & Security 84(2019), 148–165.Google ScholarDigital Library
- X. Wang, Y. Liu, and K. R. Choo. 2020. Fault tolerant, multi-subset aggregation scheme for smart grid. IEEE Transactions on Industrial Informatics.Google Scholar
- X. F. Wang, Y. Mu, and R. M. Chen. 2016. An efficient privacy‐preserving aggregation and billing protocol for smart grid. Security and Communication Networks 9, 17 (2016), 4536–4547.Google ScholarDigital Library
- L. Zhang, J. Zhang, and Y. H. Hu. 2019. A privacy-preserving distributed smart metering temporal and spatial aggregation scheme. IEEE Access 7(2019), 28372–28382.Google ScholarCross Ref
- Privacy-Preserving approaches for smart metering: A survey
Recommendations
Pseudonymous Smart Metering without a Trusted Third Party
TRUSTCOM '13: Proceedings of the 2013 12th IEEE International Conference on Trust, Security and Privacy in Computing and CommunicationsPrivacy concerns in smart metering are one of the most discussed challenges encountered by introducing the smart grid. Several approaches to tackle this problem exist. One of these approaches is the usage of pseudonyms to protect the privacy of ...
A practical smart metering system supporting privacy preserving billing and load monitoring
ACNS'12: Proceedings of the 10th international conference on Applied Cryptography and Network SecurityFine-grained meter readings enable applications in an advanced metering infrastructure. However, those meter readings threaten personal privacy by implying a sketch of daily activities of households. The privacy issue has been addressed in smart ...
An efficient privacy-preserving comparison protocol in smart metering systems
In smart grids, providing power consumption statistics to the customers and generating recommendations for managing electrical devices are considered to be effective methods that can help to reduce energy consumption. Unfortunately, providing power ...
Comments