
Cyber Threat Defense in Power Grids: Introducing the Grid-Lock Secure-Chain Consensus Framework
Blockchain technology has attracted the curiosity of experts in a variety of sectors, including its potential for Smart Grid (SG) cybersecurity. The study investigates vulnerabilities in smart Direct Current-MicroGrid (DC-MG) systems, particularly community identity servers, which pose a threat to the grid due to the increasing sophistication of existing cybersecurity frameworks, causing delays in real-time activities. The research proposes a novel, grid-lock secure-chain consensus framework to address these issues and improve contemporary power systems’ capacity to defend themselves against cyberattacks. This design makes use of Proof of Vote (PoV), a consensus technique that enables decentralized voting across the network’s meter nodes to reach consensus. For safe identification and transaction validation, every meter node has public and private keys. All information is encrypted before being transmitted to other nodes. The information is kept on a distributed ledger, where the Secure Hash Algorithm (SHA-256) hash technique is used to cryptographically connect each block. Only legitimate blocks are added to the blockchain due to the PoV process, which also maintains separate voting and accounting rights for security. The proposed design increases encryption techniques and decentralizes permission to lessen the possibility of cyberattacks without compromising system performance. The proposed framework achieves a significant improvement, with throughput increased by 53% and latency reduced by 19% compared to conventional consensus mechanisms such as Practical Byzantine Fault Tolerance (PBFT) and Proof of Work (PoW). Specifically, the framework demonstrates a throughput of 150 Transactions per second (Tx/s) and a latency of 0.89 seconds, outperforming PBFT’s throughput of 98 Tx/s and latency of 11 seconds, and PoW’s throughput of 120 Tx/s and latency of 1 second. This method represents a major leap in employing blockchain technology for current power system security as it not only strengthens the grid against assaults but also maximizes its resilience and operational efficiency. In particular, results obtained from testing on 118-bus topology setups demonstrate high throughput and low latency, confirming the framework’s suitability for SG networks under high transaction volumes and potential cyber threats.
[1] Abdelmaboud A., Ahmed A., Abaker M., Eisa T., Albasheer H., Ghorashi S., and Karim F., “Blockchain for IoT Applications: Taxonomy, Platforms, Recent Advances, Challenges and Future Research Directions,” Electronics, vol. 11, no. 4, pp. 1-35, 2022. https://doi.org/10.3390/electronics11040630
[2] Acarali D., Rao K., Rajarajan M., Chema D., and Ginzburg M., “Modelling Smart Grid IT-OT Dependencies for DDoS Impact Propagation,” Computers and Security, vol. 112, pp. 102528, 2022. https://doi.org/10.1016/j.cose.2021.102528
[3] Ahmed S., Alam M., Hassan M., Rozbu M., Ishtiak T., Rafa N., and Gandomi A., “Deep Learning Modelling Techniques: Current Progress, Applications, Advantages, and Challenges,” Artificial Intelligence Review, vol. 56, no. 11, pp. 13521-13617, 2023.
[4] Al-Mousa M., Amer W., Abualhaj M., Albilasi S., 648 The International Arab Journal of Information Technology, Vol. 22, No. 4, July 2025 Nasir O., and Samara, G., “Agile Proactive Cybercrime Evidence Analysis Model for Digital Forensics,” The International Arab Journal of Information Technology, vol. 22, no. 3, pp. 627- 636, 2025. https://doi.org/10.34028/iajit/22/3/15
[5] Amin M., El-Sousy F., Aziz G., Gaber K., and Mohammed O., “CPS Attacks Mitigation Approaches on Power Electronic Systems with Security Challenges for Smart Grid Applications: A Review,” IEEE Access, vol. 9, pp. 38571-38601, 2021. DOI:10.1109/ACCESS.2021.3063229
[6] Arvindhan M., Thirunavukarasan M., and Daniel A., Handbook of Green Computing and Blockchain Technologies, CRC Press, 2021. https://www.taylorfrancis.com/chapters/edit/10.1 201/9781003107507-8/blockchain-technology- energy-sector-arvindhan-thirunavukarasan-daniel
[7] Babar M., Tariq M., and Jan M., “Secure and Resilient Demand Side Management Engine Using Machine Learning for IoT-Enabled Smart Grid,” Sustainable Cities and Society, vol. 62, pp. 102370, 2020. https://doi.org/10.1016/j.scs.2020.102370
[8] Barreto C., Eghtesad T., Eisele S., Laszka A., Dubey A., and Koutsoukos X., “Cyber-Attacks and Mitigation in Blockchain Based transactive Energy Systems,” in Proceedings of the IEEE Conference on Industrial Cyberphysical Systems, Tampere, pp. 129-136, 2020. DOI:10.1109/ICPS48405.2020.9274708
[9] Bashir A., Khan S., Prabadevi B., Deepa N., Alnumay W., Gadekallu T., and Maddikunta P., “Comparative Analysis of Machine Learning Algorithms for Prediction of Smart Grid Stability,” International Transactions on Electrical Energy Systems, vol. 31, no. 3, pp. e12706, 2021. https://doi.org/10.1002/2050- 7038.12706
[10] Chen X., Shen J., Cao Z., and Dong X., “A Blockchain-based Privacy-Preserving Scheme for Smart Grids,” in Proceedings of the 2nd International Conference on Blockchain Technology, Hilo, pp. 120-124, 2020. https://doi.org/10.1145/3390566.3391667
[11] Chen Z., Amani A., Yu X., and Jalili M., “Control and Optimisation of Power Grids Using Smart Meter Data: A Review,” Sensors, vol. 23, no. 4, pp. 1-26, 2023. https://doi.org/10.3390/s23042118
[12] Dileep G., “A Survey on Smart Grid Technologies and Applications,” Renewable Energy, vol. 146, pp. 2589-2625, 2020. https://doi.org/10.1016/j.renene.2019.08.092
[13] Ding J., Qammar A., Zhang Z., Karim A., and Ning H., “Cyber Threats to Smart Grids: Review, Taxonomy, Potential Solutions, and Future Directions,” Energies, vol. 15, no. 18, pp. 1-37, 2022. https://doi.org/10.3390/en15186799
[14] Faheem M., Al-Khasawneh M., Khan A., and Madni S., “Cyberattack Patterns in Blockchain- based Communication Networks for Distributed Renewable Energy Systems: A Study on Big Datasets,” Data in Brief, vol. 53, pp. 110212, 2024. https://doi.org/10.1016/j.dib.2024.110212
[15] Gadekallu T., Pham Q., Nguyen D., Maddikunta P., Deepa N., Prabadevi B., and Hwang W., “Blockchain for Edge of Things: Applications, Opportunities, and Challenges,” IEEE Internet of Things Journal, vol. 9, no. 2, pp. 964-988, 2021. DOI:10.1109/JIOT.2021.3119639
[16] Ghiasi M., Dehghani M., Niknam T., Kavousi- Fard A., Siano P., and Alhelou H., “Cyber-Attack Detection and Cyber-Security Enhancement in Smart DC-Microgrid Based on Blockchain Technology and Hilbert Huang Transform,” IEEE Access, vol. 9, pp. 29429-29440, 2021. DOI:10.1109/ACCESS.2021.3059042
[17] Gunduz M. and Das R., “Cyber-Security on Smart Grid: Threats and Potential Solutions,” Computer Networks, vol. 169, pp. 107094, 2020. https://doi.org/10.1016/j.comnet.2019.107094
[18] Hasan M., Abdulkadir R., Islam S., Gadekallu T., and Safie N., “A Review on Machine Learning Techniques for Secured Cyber-Physical Systems in Smart Grid Networks,” Energy Reports, vol. 11, pp. 1268-1290, 2024. https://doi.org/10.1016/j.egyr.2023.12.040
[19] Hasankhani A., Hakimi S., Bisheh-Niasar M., Shafie-Khah M., and Asadolahi H., “Blockchain Technology in the Future Smart Grids: A Comprehensive Review and Frameworks,” International Journal of Electrical Power and Energy Systems, vol. 129, pp. 106811, 2021. https://doi.org/10.1016/j.ijepes.2021.106811
[20] Jha A., Appasani B., Gupta D., Ainapure B., and Bizon N., “A Blockchain-Enabled Approach for Enhancing Synchrophasor Measurement in Smart Grid 3.0,” Sustainability, vol. 15, no. 19, pp. 1-20, 2023. https://doi.org/10.3390/su151914451
[21] Kumar P., Kumar R., Aljuhani A., Javeed D., Jolfaei A., and Islam A., “Digital Twin-Driven SDN for Smart Grid: A Deep Learning Integrated Blockchain for Cybersecurity,” Solar Energy, vol. 263, pp. 111921, 2023. https://doi.org/10.1016/j.solener.2023.111921
[22] Kumari A., Gupta R., and Tanwar S., “Amalgamation of Blockchain and IoT for Smart Cities Underlying 6G Communication: A Comprehensive Review,” Computer Communications, vol. 172, pp. 102-118, 2021. https://doi.org/10.1016/j.comcom.2021.03.005
[23] Liu C., Zhang X., Chai K., Loo J., and Chen Y., “A Survey on BlockchaināEnabled Smart Grids: Advances, Applications and Challenges,” IET Smart Cities, vol. 3, no. 2, pp. 56-78, 2021. https://doi.org/10.1049/smc2.12010
[24] Liu Z., Wang D., Wang J., Wang X., and Li H., “A Cyber Threat Defense in Power Grids: Introducing the Grid-Lock Secure-Chain … 649 Blockchain-Enabled Secure Power Trading Mechanism for Smart Grid Employing Wireless Networks,” IEEE Access, vol. 8, pp. 177745- 177756, 2020. DOI:10.1109/ACCESS.2020.3027192
[25] Mahmud R. and Seo G., “Blockchain-Enabled Cyber-Secure Microgrid Control Using Consensus Algorithm,” in Proceedings of the IEEE 22nd Workshop on Control and Modelling of Power Electronics, Cartagena, pp. 1-7, 2021. DOI:10.1109/COMPEL52922.2021.9645973
[26] Mazhar T., Irfan H., Khan S., Haq I., Ullah I., Iqbal M., and Hamam H., “Analysis of Cyber Security Attacks and their Solutions for the Smart Grid Using Machine Learning and Blockchain Methods,” Future Internet, vol. 15, no. 2, pp. 1- 37, 2023. https://doi.org/10.3390/fi15020083
[27] Mirzaee P., Shojafar M., Cruickshank H., and Tafazolli R., “Smart Grid Security and Privacy: From Conventional to Machine Learning Issues (Threats and Countermeasures),” IEEE Access, vol. 10, pp. 52922-52954, 2022. DOI:10.1109/ACCESS.2022.3174259
[28] Moniruzzaman M., Yassine A., and Benlamri R., “Blockchain and Cooperative Game Theory for Peer-to-Peer Energy Trading in Smart Grids,” International Journal of Electrical Power and Energy Systems, vol. 151, pp. 109111, 2023. https://doi.org/10.1016/j.ijepes.2023.109111
[29] Park K., Lee J., Das A., and Park Y., “BPPS: Blockchain-Enabled Privacy-Preserving Scheme for Demand-Response Management in Smart Grid Environments,” IEEE Transactions on Dependable and Secure Computing, vol. 20, no. 2, pp. 1719-1729, 2022. DOI:10.1109/TDSC.2022.3163138
[30] Prieto Gonzalez L., Fensel A., Gomez Berbis J., Popa A., and De Amescua Seco A., “A Survey on Energy Efficiency in Smart Homes and Smart Grids,” Energies, vol. 14, no. 21, pp. 1-16, 2021. https://doi.org/10.3390/en14217273
[31] Reda H., Anwar A., Mahmood A., and Tari Z., “A Taxonomy of Cyber Defence Strategies against False Data Attacks in Smart Grids,” ACM Computing Surveys, vol. 55, no. 14s, pp. 1-37, 2023. https://doi.org/10.1145/3592797
[32] Sapra N., Shaikh I., and Dash A., “Impact of Proof of Work (PoW)-based Blockchain Applications on the Environment: A Systematic Review and Research Agenda,” Journal of Risk and Financial Management, vol. 16, no. 4, pp. 1-29, 2023. https://doi.org/10.3390/jrfm16040218
[33] Sheng C., Yao Y., Fu Q., and Yang W., “A Cyber- Physical Model for SCADA System and Its Intrusion Detection,” Computer Networks, vol. 185, pp. 107677, 2021. https://doi.org/10.1016/j.comnet.2020.107677
[34] Singh P., Masud M., Hossain M., and Kaur A., “Blockchain and Homomorphic Encryption- Based Privacy-Preserving Data Aggregation Model in Smart Grid,” Computers and Electrical Engineering, vol. 93, pp. 107209, 2021. https://doi.org/10.1016/j.compeleceng.2021.1072 09
[35] Tushar W., Saha T., Yuen C., Smith D., and Poor H., “Peer-to-Peer Trading in Electricity Networks: An Overview,” IEEE Transactions on Smart Grid, vol. 11, no. 4, pp. 3185-3200, 2020. DOI:10.1109/TSG.2020.2969657
[36] Venkatesan K. and Rahayu S., “Blockchain Security Enhancement: An Approach Towards Hybrid Consensus Algorithms and Machine Learning Techniques,” Scientific Reports, vol. 14, no. 1, pp. 1-24, 2024. https://doi.org/10.1038/s41598-024-51578-7
[37] Xia X., Xiao Y., Liang W., and Cui J., “Detection Methods in Smart Meters for Electricity Thefts: A Survey,” Proceedings of the IEEE, vol. 110, no. 2, pp. 273-319, 2022. DOI:10.1109/JPROC.2021.3139754
[38] Yapa C., De Alwis C., Liyanage M., and Ekanayake J., “Utilization of a Blockchainized Reputation Management Service for Performance Enhancement of Smart Grid 2.0 Applications,” Journal of Industrial Information Integration, vol. 39, pp. 100580, 2024. https://doi.org/10.1016/j.jii.2024.100580
[39] Zhong Y., Zhou M., Li J., and Chen J., et al., “Distributed Blockchainābased Authentication and Authorization Protocol for Smart Grid,” Wireless Communications and Mobile Computing, vol. 2021, no. 1, pp. 5560621, 2021. https://doi.org/10.1155/2021/5560621
[40] Zhuang P., Zamir T., and Liang H., “Blockchain for Cybersecurity in Smart Grid: A Comprehensive Survey,” IEEE Transactions on Industrial Informatics, vol. 17, no. 1, pp. 3-19, 2020. DOI:10.1109/TII.2020.2998479 650