Incorporation of Blockchain Technology for Different Smart Grid Applications: Architecture, Prospects, and Challenges
Abstract
:1. Introduction
2. Overview of Blockchain
Terminologies and Components of Blockchain
- i.
- Block version: it defines the criteria for validating blocks.
- ii.
- Merkle tree root hash: the total hash value of all transactions in the frame is calculated using this hashing algorithm.
- iii.
- Timestamp: it is represented in seconds in universal time, as of 1 January 1970.
- iv.
- n-Bits: the target size of a block hash.
- v.
- Nonce: it refers to a 4-byte field that begins at 0 and increases by 1 with each hash calculation.
- vi.
- Parent block hash: the 256-bit hash value of the previous block is often known as the parent block hash.
3. Operation Blockchain for Smart Grids Applications
3.1. Blockchain for Home Automation
3.2. Blockchain for Advanced Metering Infrastructure
3.3. Blockchain for Electric Vehicles
3.4. Blockchain for Renewable Microgrids
3.5. Blockchain for Energy Management System
3.6. Blockchain for Energy Management System
4. Blockchain-Enabled Cybersecurity System for Smart Grids
4.1. Common Security Risks in Smart Grids
4.1.1. Denial-of Service (DoS) Attacks
4.1.2. False Data Injection Attack (FDIA)
4.1.3. Phishing
4.1.4. Eavesdropping
4.2. Security Breaches
4.2.1. Trojan-Horse Malware Black Energy
4.2.2. Stuxnet
4.2.3. WannaCry Ransomware
4.3. Countermeasures against Cyberattacks
4.3.1. Detection and Defense for DoS Attack
4.3.2. Encryption
4.3.3. Authentication
4.3.4. Malware Protection
4.3.5. Network Security
4.3.6. Risk and Maturity Assessments
4.3.7. IPS and IDS
5. Blockchain Implication for Cybersecurity of Smart Grid Paradigm
6. Challenges and Potential Future Research Directions
7. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Jha, A.V.; Ghazali, A.N.; Appasani, B.; Ravariu, C.; Srinivasulu, A. Reliability analysis of smart grid networks Incorporating hardware failures and packet loss. Rev. Roum. Des Sci. Tech. 2021, 65, 245–252. [Google Scholar]
- Mahmoud, M.A.; Md Nasir, N.R.; Gurunathan, M.; Raj, P.; Mostafa, S. The current state of the art in research on predictive maintenance in smart grid distribution network: Fault’s types, causes, and prediction methods—A systematic review. Energies 2021, 14, 5078. [Google Scholar] [CrossRef]
- Appasani, B.; Jha, A.V.; Mishra, S.K.; Ghazali, A.N. Communication infrastructure for situational awareness enhancement in WAMS with optimal PMU placement. Prot. Control Mod. Power Syst. 2021, 6, 9. [Google Scholar] [CrossRef]
- Kaltakis, K.; Polyzi, P.; Drosatos, G.; Rantos, K. Privacy-Preserving Solutions in Blockchain-Enabled Internet of Vehicles. Appl. Sci. 2021, 11, 9792. [Google Scholar] [CrossRef]
- Yapa, C.; de Alwis, C.; Liyanage, M.; Ekanayake, J. Survey on blockchain for future smart grids: Technical aspects, applications, integration challenges and future research. Energy Rep. 2021, 7, 6530–6564. [Google Scholar] [CrossRef]
- Baidya, S.; Potdar, V.; Ray, P.P.; Nandi, C. Reviewing the opportunities, challenges, and future directions for the digitalization of energy. Energy Res. Soc. Sci. 2021, 81, 102243. [Google Scholar] [CrossRef]
- Ma, Z.; Clausen, A.; Lin, Y.; Jørgensen, B.N. An overview of digitalization for the building-to-grid ecosystem. Energy Inform. 2021, 4, 36. [Google Scholar] [CrossRef]
- Liu, C.; Zhang, X.; Chai, K.K.; Loo, J.; Chen, Y. A survey on blockchain-enabled smart grids: Advances, applications and challenges. IET Smart Cities 2021, 3, 56–78. [Google Scholar] [CrossRef]
- Hasankhani, A.; Hakimi, S.M.; Bisheh-Niasar, M.; Shafie-khah, M.; Asadolahi, H. Blockchain technology in the future smart grids: A comprehensive review and frameworks. Int. J. Electr. Power Energy Syst. 2021, 129, 106811. [Google Scholar] [CrossRef]
- Yagmur, A.; Dedeturk, B.A.; Soran, A.; Jung, J.; Onen, A. Blockchain-based energy applications: The DSO perspective. IEEE Access 2021, 9, 145605–145625. [Google Scholar] [CrossRef]
- Mollah, M.B.; Zhao, J.; Niyato, D.; Lam, K.-Y.; Zhang, X.; Ghias, A.M.; Koh, L.H.; Yang, L. Blockchain for future smart grid: A comprehensive survey. IEEE Internet Things J. 2020, 8, 18–43. [Google Scholar] [CrossRef]
- Kumar, N.M.; Chand, A.A.; Malvoni, M.; Prasad, K.A.; Mamun, K.A.; Islam, F.; Chopra, S.S. Distributed energy resources and the application of AI, IoT, and blockchain in smart grids. Energies 2020, 13, 5739. [Google Scholar] [CrossRef]
- Miglani, A.; Kumar, N.; Chamola, V.; Zeadally, S. Blockchain for Internet of Energy management: Review, solutions, and challenges. Comput. Commun. 2020, 151, 395–418. [Google Scholar] [CrossRef]
- Zia, M.F.; Benbouzid, M.; Elbouchikhi, E.; Muyeen, S.; Techato, K.; Guerrero, J.M.J.I.A. Microgrid transactive energy: Review, architectures, distributed ledger technologies, and market analysis. IEEE Access 2020, 8, 19410–19432. [Google Scholar] [CrossRef]
- Guru, D.; Perumal, S.; Varadarajan, V. Approaches towards blockchain innovation: A survey and future directions. Electronics 2021, 10, 1219. [Google Scholar] [CrossRef]
- Khajeh, H.; Laaksonen, H.; Gazafroudi, A.S.; Shafie-khah, M. Towards flexibility trading at TSO-DSO-customer levels: A review. Energies 2019, 13, 165. [Google Scholar] [CrossRef] [Green Version]
- Liaqat, R.; Sajjad, I.A.; Waseem, M.; Alhelou, H.H. Appliance Level Energy Characterization of Residential Electricity Demand: Prospects, Challenges and Recommendations. IEEE Access 2021, 9, 148676–148697. [Google Scholar] [CrossRef]
- Wang, Q.; Li, R.; Zhan, L. Blockchain technology in the energy sector: From basic research to real world applications. Comput. Sci. Rev. 2021, 39, 100362. [Google Scholar] [CrossRef]
- Khan, T.; Yu, M.; Waseem, M. Review on recent optimization strategies for hybrid renewable energy system with hydrogen technologies: State of the art, trends and future directions. Int. J. Hydrogen Energy 2022, 47, 25155–25201. [Google Scholar] [CrossRef]
- Bodkhe, U.; Tanwar, S.; Parekh, K.; Khanpara, P.; Tyagi, S.; Kumar, N.; Alazab, M. Blockchain for industry 4.0: A comprehensive review. IEEE Access 2020, 8, 79764–79800. [Google Scholar] [CrossRef]
- Lim, M.K.; Li, Y.; Wang, C.; Tseng, M.-L. A literature review of blockchain technology applications in supply chains: A comprehensive analysis of themes, methodologies and industries. Comput. Ind. Eng. 2021, 154, 107133. [Google Scholar] [CrossRef]
- Berdik, D.; Otoum, S.; Schmidt, N.; Porter, D.; Jararweh, Y. A survey on blockchain for information systems management and security. Inf. Process. Manag. 2021, 58, 102397. [Google Scholar] [CrossRef]
- Meng, T.; Zhao, Y.; Wolter, K.; Xu, C.-Z. On consortium blockchain consistency: A queueing network model approach. IEEE Trans. Parallel Distrib. Syst. 2021, 32, 1369–1382. [Google Scholar] [CrossRef]
- Bhattacharjee, A.; Badsha, S.; Shahid, A.R.; Livani, H.; Sengupta, S. Block-phasor: A decentralized blockchain framework to enhance security of synchrophasor. In Proceedings of the 2020 IEEE Kansas Power and Energy Conference (KPEC), Manhattan, KS, USA, 13–14 July 2020; pp. 1–6. [Google Scholar]
- WU, Z.; LIANG, Y.; KANG, J.; YU, R.; HE, Z. Secure data storage and sharing system based on consortium blockchain in smart grid. J. Comput. Appl. 2017, 37, 2742. [Google Scholar]
- Hasan, M.K.; Alkhalifah, A.; Islam, S.; Babiker, N.; Habib, A.; Aman, A.H.M.; Hossain, M. Blockchain technology on smart grid, energy trading, and big data: Security issues, challenges, and recommendations. Wirel. Commun. Mob. Comput. 2022, 2022, 9065768. [Google Scholar] [CrossRef]
- Kumar, A.; Bhushan, B.; Nand, P. Preventing and Detecting Intrusion of Cyberattacks in Smart Grid by Integrating Blockchain. In Micro-Electronics and Telecommunication Engineering; Springer: Singapore, 2022; pp. 119–130. [Google Scholar]
- Thakare, S.; Pund, M. Introduction to Blockchain and Terminologies. In Blockchain for Smart Systems; Chapman and Hall/CRC: Boca Raton, FL, USA, 2022; pp. 3–20. [Google Scholar]
- Çelik, D.; Meral, M.E.; Waseem, M. The progress, impact analysis, challenges and new perceptions for electric power and energy sectors in the light of the COVID-19 pandemic. Sustain. Energy Grids Netw. 2022, 31, 100728. [Google Scholar] [CrossRef]
- Guo, Y.; Wan, Z.; Cheng, X. When Blockchain Meets Smart Grids: A Comprehensive Survey. High-Confid. Comput. 2022, 2, 100059. [Google Scholar] [CrossRef]
- Çelik, D.; Meral, M.E.; Waseem, M. Scenarios, Virtualization and Applications for Blockchain Technology in Smart Grids. In Proceedings of the 2022 IEEE Kansas Power and Energy Conference (KPEC), Manhattan, KS, USA, 25–26 April 2022; pp. 1–5. [Google Scholar]
- Waseem, M.; Lin, Z.; Liu, S.; Sajjad, I.A.; Aziz, T. Optimal GWCSO-based home appliances scheduling for demand response considering end-users comfort. Electr. Power Syst. Res. 2020, 187, 106477. [Google Scholar] [CrossRef]
- Mathew, R.; Mehbodniya, A.; Ambalgi, A.P.; Murali, M.; Sahay, K.B.; Babu, D.V.J.S.E.T. Assessments. In a virtual power plant, a blockchain-based decentralized power management solution for home distributed generation. Sustain. Energy Technol. Assess. 2022, 49, 101731. [Google Scholar]
- Augello, A.; Gallo, P.; Sanseverino, E.R.; Sciumè, G.; Tornatore, M. A Coexistence Analysis of Blockchain, SCADA Systems, and OpenADR for Energy Services Provision. IEEE Access 2022, 10, 99088–99101. [Google Scholar] [CrossRef]
- Goudarzi, A.; Ghayoor, F.; Waseem, M.; Fahad, S.; Traore, I. A Survey on IoT-Enabled Smart Grids: Emerging, Applications, Challenges, and Outlook. Energies 2022, 15, 6984. [Google Scholar] [CrossRef]
- Majeed, R.; Abdullah, N.A.; Ashraf, I.; Zikria, Y.B.; Mushtaq, M.F.; Umer, M. An intelligent, secure, and smart home automation system. Sci. Program. 2020, 2020, 4579291. [Google Scholar] [CrossRef]
- Tian, H.; Jian, Y.; Ge, X. Blockchain-based AMI framework for data security and privacy protection. Sustain. Energy Grids Netw. 2022, 32, 100807. [Google Scholar] [CrossRef]
- Khan, M.A.; Sajjad, I.A.; Tahir, M.; Haseeb, A. IOT Application for Energy Management in Smart Homes. Eng. Proc. 2022, 20, 43. [Google Scholar]
- Kamal, M.; Tariq, M. Light-weight security and blockchain based provenance for advanced metering infrastructure. IEEE Access 2019, 7, 87345–87356. [Google Scholar] [CrossRef]
- Khalid, R.; Javaid, N.; Almogren, A.; Javed, M.U.; Javaid, S.; Zuair, M. A blockchain-based load balancing in decentralized hybrid P2P energy trading market in smart grid. IEEE Access 2020, 8, 47047–47062. [Google Scholar] [CrossRef]
- Sovacool, B.K.; Kester, J.; Noel, L.; de Rubens, G.Z. Actors, business models, and innovation activity systems for vehicle-to-grid (V2G) technology: A comprehensive review. Renew. Sustain. Energy Rev. 2020, 131, 109963. [Google Scholar] [CrossRef]
- Islam, M.M.; Shahjalal, M.; Hasan, M.K.; Jang, Y.M. Blockchain-based energy transaction model for electric vehicles in v2g network. In Proceedings of the 2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC), Fukuoka, Japan, 19–21 February 2020; pp. 628–630. [Google Scholar]
- Rehman, A.; Hassan, M.F.; Yew, K.H.; Paputungan, I.; Tran, D.C. State-of-the-art IoV trust management a meta-synthesis systematic literature review (SLR). PeerJ Comput. Sci. 2020, 6, e334. [Google Scholar] [CrossRef]
- Pal, R.; Chavhan, S.; Gupta, D.; Khanna, A.; Padmanaban, S.; Khan, B.; Rodrigues, J.J. A comprehensive review on IoT-based infrastructure for smart grid applications. IET Renew. Power Gener. 2021, 15, 3761–3776. [Google Scholar] [CrossRef]
- Gschwendtner, C.; Sinsel, S.R.; Stephan, A. Vehicle-to-X (V2X) implementation: An overview of predominate trial configurations and technical, social and regulatory challenges. Renew. Sustain. Energy Rev. 2021, 145, 110977. [Google Scholar] [CrossRef]
- Khan, M.A.; Ghosh, S.; Busari, S.A.; Huq, K.M.S.; Dagiuklas, T.; Mumtaz, S.; Iqbal, M.; Rodriguez, J. Robust, resilient and reliable architecture for v2x communications. IEEE Trans. Intell. Transp. Syst. 2021, 22, 4414–4430. [Google Scholar] [CrossRef]
- Nguyen, D.C.; Pathirana, P.N.; Ding, M.; Seneviratne, A. Blockchain for 5G and beyond networks: A state of the art survey. J. Netw. Comput. Appl. 2020, 166, 102693. [Google Scholar] [CrossRef]
- Xu, C.; Wu, H.; Liu, H.; Li, X.; Liu, L.; Wang, P. An intelligent scheduling access privacy protection model of electric vehicle based on 5G-V2X. Sci. Program. 2021, 2021, 1198794. [Google Scholar] [CrossRef]
- Rawat, D.B.; Doku, R.; Adebayo, A.; Bajracharya, C.; Kamhoua, C. Blockchain enabled named data networking for secure vehicle-to-everything communications. IEEE Netw. 2020, 34, 185–189. [Google Scholar] [CrossRef]
- Gomes, L.; Spínola, J.; Vale, Z.; Corchado, J.M. Agent-based architecture for demand side management using real-time resources’ priorities and a deterministic optimization algorithm. J. Clean. Prod. 2019, 241, 118154. [Google Scholar] [CrossRef]
- Khan, P.W.; Byun, Y.-C. Blockchain-based peer-to-peer energy trading and charging payment system for electric vehicles. Sustainability 2021, 13, 7962. [Google Scholar] [CrossRef]
- Musleh, A.S.; Yao, G.; Muyeen, S. Blockchain applications in smart grid–review and frameworks. IEEE Access 2019, 7, 86746–86757. [Google Scholar] [CrossRef]
- Sadiq, A.; Javed, M.U.; Khalid, R.; Almogren, A.; Shafiq, M.; Javaid, N. Blockchain based data and energy trading in internet of electric vehicles. IEEE Access 2020, 9, 7000–7020. [Google Scholar] [CrossRef]
- Kim, M.; Park, K.; Yu, S.; Lee, J.; Park, Y.; Lee, S.-W.; Chung, B. A secure charging system for electric vehicles based on blockchain. Sensors 2019, 19, 3028. [Google Scholar] [CrossRef] [Green Version]
- Dorokhova, M.; Vianin, J.; Alder, J.-M.; Ballif, C.; Wyrsch, N.; Wannier, D. A Blockchain-Supported Framework for Charging Management of Electric Vehicles. Energies 2021, 14, 7144. [Google Scholar] [CrossRef]
- Dib, O.; Brousmiche, K.-L.; Durand, A.; Thea, E.; Hamida, E.B. Consortium blockchains: Overview, applications and challenges. Int. J. Adv. Telecommun. 2018, 11, 51–64. [Google Scholar]
- Saxena, S.; Farag, H.E.; Brookson, A.; Turesson, H.; Kim, H. A permissioned blockchain system to reduce peak demand in residential communities via energy trading: A real-world case study. IEEE Access 2020, 9, 5517–5530. [Google Scholar] [CrossRef]
- Huang, Z.; Li, Z.; Lai, C.S.; Zhao, Z.; Wu, X.; Li, X.; Tong, N.; Lai, L.L. A novel power market mechanism based on blockchain for electric vehicle charging stations. Electronics 2021, 10, 307. [Google Scholar] [CrossRef]
- Vieira, G.; Zhang, J. Peer-to-peer energy trading in a microgrid leveraged by smart contracts. Renew. Sustain. Energy Rev. 2021, 143, 110900. [Google Scholar] [CrossRef]
- Yildizbasi, A. Blockchain and renewable energy: Integration challenges in circular economy era. Renew. Energy 2021, 176, 183–197. [Google Scholar] [CrossRef]
- Kavousi-Fard, A.; Almutairi, A.; Al-Sumaiti, A.; Farughian, A.; Alyami, S. An effective secured peer-to-peer energy market based on blockchain architecture for the interconnected microgrid and smart grid. Int. J. Electr. Power Energy Syst. 2021, 132, 107171. [Google Scholar] [CrossRef]
- van Leeuwen, G.; AlSkaif, T.; Gibescu, M.; van Sark, W. An integrated blockchain-based energy management platform with bilateral trading for microgrid communities. Appl. Energy 2020, 263, 114613. [Google Scholar] [CrossRef]
- Tsao, Y.-C.; Thanh, V.-V. Toward sustainable microgrids with blockchain technology-based peer-to-peer energy trading mechanism: A fuzzy meta-heuristic approach. Renew. Sustain. Energy Rev. 2021, 136, 110452. [Google Scholar] [CrossRef]
- Wang, X.; Liu, P.; Ji, Z. Trading platform for cooperation and sharing based on blockchain within multi-agent energy internet. Glob. Energy Interconnect. 2021, 4, 384–393. [Google Scholar] [CrossRef]
- Li, Q.; Li, A.; Wang, T.; Cai, Y. Interconnected hybrid AC-DC microgrids security enhancement using blockchain technology considering uncertainty. Int. J. Electr. Power Energy Syst. 2021, 133, 107324. [Google Scholar] [CrossRef]
- Wang, T.; Hua, H.; Wei, Z.; Cao, J. Challenges of blockchain in new generation energy systems and future outlooks. Int. J. Electr. Power Energy Syst. 2022, 135, 107499. [Google Scholar] [CrossRef]
- Wang, L.; Ma, Y.; Zhu, L.; Wang, X.; Cong, H.; Shi, T. Design of integrated energy market cloud service platform based on blockchain smart contract. Int. J. Electr. Power Energy Syst. 2022, 135, 107515. [Google Scholar] [CrossRef]
- Ahl, A.; Yarime, M.; Goto, M.; Chopra, S.S.; Kumar, N.M.; Tanaka, K.; Sagawa, D. Exploring blockchain for the energy transition: Opportunities and challenges based on a case study in Japan. Renew. Sustain. Energy Rev. 2020, 117, 109488. [Google Scholar] [CrossRef]
- Khan, M.A.; Ali, A. Hybrid Fuzzy-PI and ANFIS Controller Design for Rotor Current Control of DFIG Based Wind Turbine. Pak. J. Eng. Technol. 2022, 5, 35–41. [Google Scholar] [CrossRef]
- Çelik, D.; Meral, M.E.; Waseem, M. Investigation and analysis of effective approaches, opportunities, bottlenecks and future potential capabilities for digitalization of energy systems and sustainable development goals. Electr. Power Syst. Res. 2022, 211, 108251. [Google Scholar] [CrossRef]
- Hu, W.; Li, H. A blockchain-based secure transaction model for distributed energy in Industrial Internet of Things. Alex. Eng. J. 2021, 60, 491–500. [Google Scholar] [CrossRef]
- Zhang, Y.; Shi, Q. An intelligent transaction model for energy blockchain based on diversity of subjects. Alex. Eng. J. 2021, 60, 749–756. [Google Scholar] [CrossRef]
- Gourisetti, S.N.G.; Sebastian-Cardenas, D.J.; Bhattarai, B.; Wang, P.; Widergren, S.; Borkum, M.; Randall, A. Blockchain smart contract reference framework and program logic architecture for transactive energy systems. Appl. Energy 2021, 304, 117860. [Google Scholar] [CrossRef]
- Khan, T.; Waseem, M.; Tahir, M.; Liu, S.; Yu, M. Autonomous hydrogen-based solar-powered energy system for rural electrification in Balochistan, Pakistan: An energy-economic feasibility analysis. Energy Convers. Manag. 2022, 271, 116284. [Google Scholar] [CrossRef]
- Appasani, B.; Mishra, S.K.; Jha, A.V.; Mishra, S.K.; Enescu, F.M.; Sorlei, I.S.; Bîrleanu, F.G.; Takorabet, N.; Thounthong, P.; Bizon, N. Blockchain-Enabled Smart Grid Applications: Architecture, Challenges, and Solutions. Sustainability 2022, 14, 8801. [Google Scholar] [CrossRef]
- Esposito, C.; Ficco, M.; Gupta, B.B. Blockchain-based authentication and authorization for smart city applications. Inf. Process. Manag. 2021, 58, 102468. [Google Scholar] [CrossRef]
- Rejeb, A.; Rejeb, K.; Simske, S.J.; Keogh, J.G. Blockchain technology in the smart city: A bibliometric review. Qual. Quant. 2022, 56, 2875–2906. [Google Scholar] [CrossRef] [PubMed]
- Enescu, F.M.; Bizon, N.; Ionescu, V.M. Blockchain–a new tehnology for the smart village. In Proceedings of the 2021 13th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), Pitesti, Romania, 1–3 July2021; pp. 1–6. [Google Scholar]
- Enescu, F.M.; Bizon, N.; Cirstea, A.; Stirbu, C. Blockchain technology applied in health the study of blockchain application in the health system (I). In Proceedings of the 2018 10th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), Iasi, Romania, 28–30 June 2018; pp. 1–4. [Google Scholar]
- Kumar, A.; Singh, A.K.; Ahmad, I.; Kumar Singh, P.; Verma, P.K.; Alissa, K.A.; Bajaj, M.; Ur Rehman, A.; Tag-Eldin, E. A novel decentralized blockchain architecture for the preservation of privacy and data security against cyberattacks in healthcare. Sensors 2022, 22, 5921. [Google Scholar] [CrossRef]
- Enescu, F.M.; Bizon, N.; Onu, A.; Răboacă, M.S.; Thounthong, P.; Mazare, A.G.; Șerban, G. Implementing blockchain technology in irrigation systems that integrate photovoltaic energy generation systems. Sustainability 2020, 12, 1540. [Google Scholar] [CrossRef] [Green Version]
- Raboaca, M.S.; Bizon, N.; Trufin, C.; Enescu, F.M. Efficient and secure strategy for energy systems of interconnected farmers′ associations to meet variable energy demand. Mathematics 2020, 8, 2182. [Google Scholar] [CrossRef]
- Rocha, G.d.S.R.; de Oliveira, L.; Talamini, E. Blockchain applications in agribusiness: A systematic review. Future Internet 2021, 13, 95. [Google Scholar] [CrossRef]
- Waseem, M.; Lin, Z.; Ding, Y.; Wen, F.; Liu, S.; Palu, I. Technologies and practical implementations of air-conditioner based demand response. J. Mod. Power Syst. Clean Energy 2020, 9, 1395–1413. [Google Scholar] [CrossRef]
- Rizwan, M.; Waseem, M.; Liaqat, R.; Sajjad, I.A.; Dampage, U.; Salmen, S.H.; Obaid, S.A.; Mohamed, M.A.; Annuk, A. SPSO Based Optimal Integration of DGs in Local Distribution Systems under Extreme Load Growth for Smart Cities. Electronics 2021, 10, 2542. [Google Scholar] [CrossRef]
- Megahed, N.A.; Abdel-Kader, R.F. Smart Cities after COVID-19: Building a conceptual framework through a multidisciplinary perspective. Sci. Afr. 2022, 17, e01374. [Google Scholar] [CrossRef]
- Wu, H.; Cao, J.; Yang, Y.; Tung, C.L.; Jiang, S.; Tang, B.; Liu, Y.; Wang, X.; Deng, Y. Data management in supply chain using blockchain: Challenges and a case study. In Proceedings of the 2019 28th International Conference on Computer Communication and Networks (ICCCN), Valencia, Spain, 29 July–1 August 2019; pp. 1–8. [Google Scholar]
- Aggarwal, S.; Chaudhary, R.; Aujla, G.S.; Kumar, N.; Choo, K.-K.R.; Zomaya, A. Blockchain for smart communities: Applications, challenges and opportunities. J. Netw. Comput. Appl. 2019, 144, 13–48. [Google Scholar] [CrossRef]
- Al Sadawi, A.; Madani, B.; Saboor, S.; Ndiaye, M.; Abu-Lebdeh, G.J. A comprehensive hierarchical blockchain system for carbon emission trading utilizing blockchain of things and smart contract. Technol. Forecast. Soc. Chang. 2021, 173, 121124. [Google Scholar] [CrossRef]
- Zia, M. B-DRIVE: A blockchain based distributed IoT network for smart urban transportation. Blockchain Res. Appl. 2021, 2, 100033. [Google Scholar] [CrossRef]
- Pournaras, E. Proof of witness presence: Blockchain consensus for augmented democracy in smart cities. J. Parallel Distrib. Comput. 2020, 145, 160–175. [Google Scholar] [CrossRef]
- Iqbal, M.M.; Waseem, M.; Manan, A.; Liaqat, R.; Muqeet, A.; Wasaya, A. IoT-Enabled Smart Home Energy Management Strategy for DR Actions in Smart Grid Paradigm. In Proceedings of the 2021 International Bhurban Conference on Applied Sciences and Technologies (IBCAST), Islamabad, Pakistan, 12–16 January 2021; pp. 352–357. [Google Scholar]
- Huseinović, A.; Mrdović, S.; Bicakci, K.; Uludag, S. A survey of denial-of-service attacks and solutions in the smart grid. IEEE Access 2020, 8, 177447–177470. [Google Scholar] [CrossRef]
- Huseinovic, A.; Mrdovic, S.; Bicakci, K.; Uludag, S. A taxonomy of the emerging Denial-of-Service attacks in the smart grid and countermeasures. In Proceedings of the 2018 26th Telecommunications Forum (TELFOR), Belgrade, Serbia, 20–21 November 2018; pp. 1–4. [Google Scholar]
- Du, D.; Li, X.; Li, W.; Chen, R.; Fei, M.; Wu, L. ADMM-based distributed state estimation of smart grid under data deception and denial of service attacks. IEEE Trans. Syst. Man Cybern. Syst. 2019, 49, 1698–1711. [Google Scholar] [CrossRef]
- Valliammai, A.; Bavatharinee, U.; Shivadharshini, K.; Hemavathi, N.; Meenalochani, M.; Sriranjani, R. A Comprehensive Study on Distributed Denial of Service Attacks in Internet of Things Based Smart Grid. In Proceedings of the International Conference on Intelligent Data Communication Technologies and Internet of Things, Coimbatore, India, 12–13 September 2019; pp. 685–691. [Google Scholar]
- Raja, D.J.S.; Sriranjani, R.; Parvathy, A.; Hemavathi, N. A Review on Distributed Denial of Service Attack in Smart Grid. In Proceedings of the 2022 7th International Conference on Communication and Electronics Systems (ICCES), Coimbatore, India, 22–24 June 2022; pp. 812–819. [Google Scholar]
- Holik, F.; Flå, L.H.; Jaatun, M.G.; Yayilgan, S.Y.; Foros, J. Threat modeling of a smart grid secondary substation. Electronics 2022, 11, 850. [Google Scholar] [CrossRef]
- Acarali, D.; Rao, K.R.; Rajarajan, M.; Chema, D.; Ginzburg, M. Modelling smart grid IT-OT dependencies for DDoS impact propagation. Comput. Secur. 2022, 112, 102528. [Google Scholar] [CrossRef]
- Mukherjee, D.; Chakraborty, S.; Ghosh, S. Deep learning-based multilabel classification for locational detection of false data injection attack in smart grids. Electr. Eng. 2022, 104, 259–282. [Google Scholar] [CrossRef]
- Yan, J.-J.; Yang, G.-H.; Wang, Y. Dynamic Reduced-Order Observer-Based Detection of False Data Injection Attacks With Application to Smart Grid Systems. IEEE Trans. Ind. Inform. 2022, 18, 6712–6722. [Google Scholar] [CrossRef]
- Reda, H.T.; Anwar, A.; Mahmood, A. Comprehensive survey and taxonomies of false data injection attacks in smart grids: Attack models, targets, and impacts. Renew. Sustain. Energy Rev. 2022, 163, 112423. [Google Scholar] [CrossRef]
- Mahi-Al-rashid, A.; Hossain, F.; Anwar, A.; Azam, S. False data injection attack detection in smart grid using energy consumption forecasting. Energies 2022, 15, 4877. [Google Scholar] [CrossRef]
- Wang, S.; Bi, S.; Zhang, Y.-J.A. Locational detection of the false data injection attack in a smart grid: A multilabel classification approach. IEEE Internet Things J. 2020, 7, 8218–8227. [Google Scholar] [CrossRef]
- Deng, R.; Liang, H. False data injection attacks with limited susceptance information and new countermeasures in smart grid. IEEE Trans. Ind. Inform. 2018, 15, 1619–1628. [Google Scholar] [CrossRef]
- Nafees, M.N.; Saxena, N.; Cardenas, A.; Grijalva, S.; Burnap, P. Smart grid cyber-physical situational awareness of complex operational technology attacks: A review. ACM Comput. Surv. 2022. [Google Scholar] [CrossRef]
- Kimani, K.; Oduol, V.; Langat, K. Cyber security challenges for IoT-based smart grid networks. Int. J. Crit. Infrastruct. Prot. 2019, 25, 36–49. [Google Scholar] [CrossRef]
- Gunduz, M.Z.; Das, R. Analysis of cyber-attacks on smart grid applications. In Proceedings of the 2018 International Conference on Artificial Intelligence and Data Processing (IDAP), Malatya, Turkey, 28–30 September 2018; pp. 1–5. [Google Scholar]
- Le, T.D.; Anwar, A.; Loke, S.W.; Beuran, R.; Tan, Y. Gridattacksim: A cyber attack simulation framework for smart grids. Electronics 2020, 9, 1218. [Google Scholar] [CrossRef]
- Zheng, L.; Gao, T.; Zhang, X. Security protection and testing system for cyber-physical based smart power grid. In Proceedings of the PURPLE MOUNTAIN FORUM 2019-International Forum on Smart Grid Protection and Control; Springer: Singapore, 2020; pp. 847–857. [Google Scholar]
- Abdullah, H.I.M.; Mustaffa, M.Z.; Rahim, F.A.; Ibrahim, Z.-A.; Yusoff, Y.; Yussof, S.; Bakar, A.A.; Ismail, R.; Ramli, R. Smart grid digital forensics investigation framework. In Proceedings of the 2020 8th International Conference on Information Technology and Multimedia (ICIMU), Selangor, Malaysia, 24–26 August 2020; pp. 200–205. [Google Scholar]
- Xu, K.; Wang, X.; Xu, H.; Dong, N.; Han, M.; Zhou, X. A vulnerability scanning scheme based on attack graph for smart grid industrial control system. IOP Conf. Ser. Earth Environ. Sci. 2021, 645, 012060. [Google Scholar] [CrossRef]
- Faquir, D.; Chouliaras, N.; Sofia, V.; Olga, K.; Maglaras, L. Cybersecurity in smart grids, challenges and solutions. AIMS Electron. Electr. Eng. 2021, 5, 24–37. [Google Scholar]
- Akbanov, M.; Vassilakis, V.G.; Logothetis, M.D.J. Ransomware detection and mitigation using software-defined networking: The case of WannaCry. Comput. Electr. Eng. 2019, 76, 111–121. [Google Scholar] [CrossRef]
- Kuznetsov, A.; Kavun, S.; Smirnov, O.; Babenko, V.; Nakisko, O.; Kuznetsova, K. Malware correlation monitoring in computer networks of promising smart grids. In Proceedings of the 2019 IEEE 6th International Conference on Energy Smart Systems (ESS), Kyiv, Ukraine, 17–19 April 2019; pp. 347–352. [Google Scholar]
- Shaaban, A.R.; Abdelwanees, E.; Hussein, M. Distributed Denial of Service Attacks Analysis, Detection, and Mitigation for the Space Control Ground Network: DDoS attacks analysis, detection and mitigation. Proc. Pak. Acad. Sci. A Phys. Comput. Sci. 2020, 57, 97–108. [Google Scholar]
- Sairam, V.; Kumar, M. Counter attacks as self-defense. Int. J. Sci. Res. Eng. Trends 2019, 5, 976–981. [Google Scholar]
- Toapanta, S.M.T.; Gallegos, L.E.M.; Morán, M.J.C.; Rojas, J.G.O. Analysis of models of security to mitigate the risks, vulnerabilities and threats in a company of services of telecommunications. In Proceedings of the 2020 3rd International Conference on Information and Computer Technologies (ICICT), San Jose, CA, USA, 9–12 March 2020; pp. 445–450. [Google Scholar]
- Neves, R.H.; Silva, A.A.; Gava, V.; Azevedo, M.T.; Sandoval, J.F.; Oliveira, F.S.; Guelfi, A.E.; Kofuji, S.T. DoS Attack on SDN: A study on control plane strategies in-band and out-of-band. Res. Sq. 2022, preprint.
- Zeng, Z.; Li, Y.; Cao, Y.; Zhao, Y.; Zhong, J.; Sidorov, D.; Zeng, X. Blockchain Technology for Information Security of the Energy Internet: Fundamentals, Features, Strategy and Application. Energies 2020, 13, 881. [Google Scholar] [CrossRef] [Green Version]
- Khan, M.A.; Saleh, A.M.; Waseem, M.; Sajjad, I.A. Artificial Intelligence Enabled Demand Response: Prospects and Challenges in Smart Grid Environment. IEEE Access 2023, 11, 1477–1505. [Google Scholar] [CrossRef]
- Guan, Z.; Zhang, Y.; Zhu, L.; Wu, L.; Yu, S. EFFECT: An efficient flexible privacy-preserving data aggregation scheme with authentication in smart grid. Sci. China Inf. Sci. 2019, 62, 32103. [Google Scholar] [CrossRef] [Green Version]
- Agarkar, A.; Agrawal, H. A review and vision on authentication and privacy preservation schemes in smart grid network. Secur. Priv. 2019, 2, e62. [Google Scholar] [CrossRef] [Green Version]
- Sureshkumar, V.; Anandhi, S.; Amin, R.; Selvarajan, N.; Madhumathi, R. Design of robust mutual authentication and key establishment security protocol for cloud-enabled smart grid communication. IEEE Syst. J. 2020, 15, 3565–3572. [Google Scholar] [CrossRef]
- Almasarani, A.; Majid, M. 5G-Wireless sensor networks for smart grid-accelerating technology’s progress and innovation in the kingdom of Saudi arabia. Procedia Comput. Sci. 2021, 182, 46–55. [Google Scholar]
- Nguyen, T.N.; Liu, B.-H.; Nguyen, N.P.; Chou, J.-T. Cyber security of smart grid: Attacks and defenses. In Proceedings of the ICC 2020-2020 IEEE International Conference on Communications (ICC), Dublin, Ireland, 7–11 June 2020; pp. 1–6. [Google Scholar]
- Leszczyna, R. Standards on cyber security assessment of smart grid. Int. J. Crit. Infrastruct. Prot. 2018, 22, 70–89. [Google Scholar] [CrossRef]
- Sundararajan, A.; Hernandez, A.S.; Sarwat, A.I. Adapting big data standards, maturity models to smart grid distributed generation: Critical review. IET Smart Grid 2020, 3, 508–519. [Google Scholar] [CrossRef]
- Mir, A.W.; Ramachandran, R.K. Security gaps assessment of smart grid based SCADA systems. Inf. Comput. Secur. 2019, 27, 434–452. [Google Scholar] [CrossRef]
- Annor-Asante, M.; Pranggono, B. Development of smart grid testbed with low-cost hardware and software for cybersecurity research and education. Wirel. Pers. Commun. 2018, 101, 1357–1377. [Google Scholar] [CrossRef] [Green Version]
- Kisielewicz, T.; Stanek, S.; Zytniewski, M. A Multi-Agent Adaptive Architecture for Smart-Grid-Intrusion Detection and Prevention. Energies 2022, 15, 4726. [Google Scholar] [CrossRef]
- Rafique, Z.; Khalid, H.M.; Muyeen, S. Communication systems in distributed generation: A bibliographical review and frameworks. IEEE Access 2020, 8, 207226–207239. [Google Scholar] [CrossRef]
- Jha, A.V.; Appasani, B.; Ghazali, A.N. A Comprehensive Framework for the Assessment of Synchrophasor Communication Networks from the Perspective of Situational Awareness in a Smart Grid Cyber Physical System. Technol. Econ. Smart Grids Sustain. Energy 2022, 7, 20. [Google Scholar] [CrossRef]
- Musleh, A.S.; Chen, G.; Dong, Z.Y. A survey on the detection algorithms for false data injection attacks in smart grids. IEEE Trans. Smart Grid 2019, 11, 2218–2234. [Google Scholar] [CrossRef]
- Inayat, U.; Zia, M.F.; Mahmood, S.; Khalid, H.M.; Benbouzid, M. Learning-Based Methods for Cyber Attacks Detection in IoT Systems: A Survey on Methods, Analysis, and Future Prospects. Electronics 2022, 11, 1502. [Google Scholar] [CrossRef]
- Waseem, M.; Lin, Z.; Liu, S.; Zhang, Z.; Aziz, T.; Khan, D. Fuzzy compromised solution-based novel home appliances scheduling and demand response with optimal dispatch of distributed energy resources. Appl. Energy 2021, 290, 116761. [Google Scholar] [CrossRef]
- Biswas, S.; Sharif, K.; Li, F.; Maharjan, S.; Mohanty, S.P.; Wang, Y. PoBT: A Lightweight Consensus Algorithm for Scalable IoT Business Blockchain. IEEE Internet Things J. 2020, 7, 2343–2355. [Google Scholar] [CrossRef]
- Waseem, M.; Lin, Z.; Liu, S.; Jinai, Z.; Rizwan, M.; Sajjad, I.A. Optimal BRA based electric demand prediction strategy considering instance-based learning of the forecast factors. Int. Trans. Electr. Energy Syst. 2021, 31, e12967. [Google Scholar] [CrossRef]
- Aziz, T.; Lin, Z.; Waseem, M.; Liu, S. Review on optimization methodologies in transmission network reconfiguration of power systems for grid resilience. Int. Trans. Electr. Energy Syst. 2021, 31, e12704. [Google Scholar] [CrossRef]
- Waseem, M.; Sajjad, I.A.; Haroon, S.S.; Amin, S.; Farooq, H.; Martirano, L.; Napoli, R. Electrical Demand and its Flexibility in Different Energy Sectors. Electr. Power Compon. Syst. 2020, 48, 1339–1361. [Google Scholar] [CrossRef]
- Kim, S.; Kwon, Y.; Cho, S. A Survey of Scalability Solutions on Blockchain. In Proceedings of the 2018 International Conference on Information and Communication Technology Convergence (ICTC), Jeju Island, Republic of Korea, 17–19 October 2018; pp. 1204–1207. [Google Scholar]
- Wood, E. A Secure Decentralised Generalised Transaction Ledger, Ethereum Proj. Yellow Pap. 2014, 151, 1–32. [Google Scholar]
- Jabbar, A.; Dani, S. Investigating the link between transaction and computational costs in a blockchain environment. Int. J. Prod. Res. 2020, 58, 3423–3436. [Google Scholar] [CrossRef]
- Michelin, R.A.; Dorri, A.; Steger, M.; Lunardi, R.C.; Kanhere, S.S.; Jurdak, R.; Zorzo, A.F. SpeedyChain: A framework for decoupling data from blockchain for smart cities. In Proceedings of the 15th EAI international conference on mobile and ubiquitous systems: Computing, networking and services, New York, NY, USA, 5–7 November 2018; pp. 145–154. [Google Scholar]
- Huang, J.; Kong, L.; Chen, G.; Wu, M.-Y.; Liu, X.; Zeng, P. Towards secure industrial IoT: Blockchain system with credit-based consensus mechanism. IEEE Trans. Ind. Inform. 2019, 15, 3680–3689. [Google Scholar] [CrossRef]
- Alladi, T.; Chamola, V.; Parizi, R.M.; Choo, K.-K.R. Blockchain applications for industry 4.0 and industrial IoT: A review. IEEE Access 2019, 7, 176935–176951. [Google Scholar] [CrossRef]
- Kang, J.; Xiong, Z.; Niyato, D.; Ye, D.; Kim, D.I.; Zhao, J. Toward secure blockchain-enabled internet of vehicles: Optimizing consensus management using reputation and contract theory. IEEE Trans. Veh. Technol. 2019, 68, 2906–2920. [Google Scholar] [CrossRef] [Green Version]
- Goudarzi, A.; Fahad, S.; Ni, J.; Ghayoor, F.; Siano, P.; Haes Alhelou, H. A sequential hybridization of ETLBO and IPSO for solving reserve-constrained combined heat, power and economic dispatch problem. IET Gener. Transm. Distrib. 2022, 16, 1930–1949. [Google Scholar] [CrossRef]
- Goudarzi, A.; Zhang, C.; Fahad, S.; Mahdi, A.J. A hybrid sequential approach for solving environmentally constrained optimal scheduling in co-generation systems. Energy Rep. 2021, 7, 3460–3479. [Google Scholar] [CrossRef]
- Fahad, S.; Goudarzi, A.; Li, Y.; Xiang, J. A coordination control strategy for power quality enhancement of an active distribution network. Energy Rep. 2022, 8, 5455–5471. [Google Scholar] [CrossRef]
- Fahad, S.; Goudarzi, A.; Xiang, J. In From Grid Feeding to Grid Supporting Converters: A Constant Power Active Distribution Network Perspective. In Proceedings of the 2020 IEEE 29th International Symposium on Industrial Electronics (ISIE), Delft, The Netherlands, 17–19 June 2020; pp. 862–867. [Google Scholar]
Applications | [6] | [7] | [8] | [9] | [10] | [11] | [12] | [13] | [14] | [15] | [16] | [17] | [18] | [19] | This Study |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
HA | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
EVs | ✓ | ✗ | ✗ | ✓ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ |
Smart Cities | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ |
AMI | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ |
MGs | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✗ | ✓ | ✓ |
EMs | ✗ | ✗ | ✗ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ |
Application Area | Description | Domain | Mechanism Used |
---|---|---|---|
Home Automation (HA) | While computationally quick and affordable, access control in smart homes is vulnerable to malicious assaults. | Access control | Private blockchain |
Secure method of transferring medical data to the medical facility, but has higher overhead | Home care | Ethereum blockchain | |
Reduces communication overhead but adds extra overhead when sending patient data. | Home care | Private blockchain | |
Decreases the block size for charging bill payment. Cyberattacks could happen because of this as well. | EV-charging bill payment | Lightweight basic blockchain | |
The storage of older people’s data is efficient and of higher quality, but it is subject to DoS attacks. | Home care | Consortium blockchain | |
A scalable but pricey method of IoT device authentication | Authentication mechanism | Ethereum blockchain | |
A very flexible automated payment system with off-chain transaction support | Automated payment | Bitcoin blockchain | |
A quick and efficient payment procedure. This might be open to nefarious attacks. | Lightweight payment system | NA | |
Electric Vehicles (EVs) | Utilizing a game-theoretic method to effectively distribute mining duties to the mining clusters | V2X communications | Blockchain-based cellular V2X networks |
Deploying a novel framework (secure V2X) while protecting the confidentiality and security of the V2X protocol | Secure V2X communications | Blockchain and NDN (named data networking) | |
Maintaining data confidentiality and information anonymity while improving the distribution network and renewable energy network. | Energy trading and charging payment system for EVs | Private blockchain | |
Charging management framework with crediting in the safety zone of the energy flows between the owners and the companies. | Charging management | Ethereum blockchain platform | |
Residential energy trading systems with reduced impact on the energy distribution network. | Blockchain platform | Ethereum blockchain platform | |
Microgrids (MGs) | Economic and energy blockchain-based flow with fund authentication and automatic control of transactions. | Local energy market | Public blockchain |
Decrease electricity costs for each time slot and local energy demand and generation balance, and optimize energy use, particularly during peak hours. | Local energy market/microgrid/smart grid | Private blockchain with PoW mechanism | |
Decentralized market mechanism | Microgrid/smart grid | Private blockchain | |
Lower electricity price control over power generation, and full self-consumption of renewable energy | Local energy market/microgrid | Public blockchain | |
Both a decentralized and a semi-centralized structure are suggested. Framework 2 utilizes fewer transactions, is more flexible, and is less secure compared to Framework 1, which uses more transactions. | Local energy market/microgrid | Solc, Mocha, React.js, Next.js, Ganachecli, Metamask, Ganache-cli, and Web3 | |
Ensure security and reach consensus when cyberattacks happen. | Microgrid/smart grid | Either public or private blockchain | |
Improve microgrid energy flow and lower import prices | Microgrid | Private blockchain | |
Framework and proposed methodology for energy management | Renewable energy | Either public or private blockchain | |
Energy Management Systems (EMS) | Real-time consumer transaction verification, risk management for energy transactions, and security | Secure energy transaction | Blockchain |
Determining the energy trade’s open price and allowing network members to monitor transactions | Energy price | Blockchain | |
Lowering the cost of electricity needed to power the blockchain’s operations while also improving the technology’s energy efficiency | Blockchain performance. Blockchain-based virtual electricity generation | Blockchain | |
Securing energy flow and users, as well as differentiating prices based on a classification of providers and consumers. | Smart contract trading | Blockchain | |
Energy architecture objectives, and increased security | Energy market | Blockchain | |
Energy trading between residents | Energy trading | Blockchain | |
Energy trading with low transaction costs | Renewable energy | Blockchain | |
Cloud service platform design for energy trading without intermediaries | Smart contract | Blockchain | |
Trading through a secure decentralized system and smart contracts | Blockchain evolution and challenges | Blockchain | |
Smart Cities (SCs) | Enhancing citizens’ standards of living | Smart village architecture | Blockchain in healthcare |
Online consultation data storage security, privacy, and integrity | Application of BC in the health system | Blockchain in healthcare | |
How to use BC technology in the medical field to keep track of the patient’s health. Effective data management and real-time patient monitoring | Application of BC technology in the healthcare | Blockchain in healthcare | |
Modernizing the healthcare system with improved data security, privacy, and integrity | Public health in the smart society | Blockchain in healthcare | |
A combination strategy based on off-chain storage and on-chain verification to increase privacy and security | Development of a BC based platform for healthcare | Blockchain in healthcare | |
Exploiting photovoltaic parks, reducing pollution, selling extra energy, and lowering production costs | Green energy marketing | Blockchain in Smart City | |
Effective trade, high-quality production, and capitalizing on energy surplus | Energy management | Blockchain in Smart City | |
Energy trading, control, and use for irrigation systems that is effective | Utilizing renewable energy for irrigation | Blockchain in Smart City | |
Design of a model for processing edge nodes in real time to increase system resilience | Scalable network of smart cities with hybrid architecture | Blockchain in Smart City | |
An extensive analysis spanning numerous viewpoints on blockchain in smart cities and communities | Security issues for the smart city | Blockchain in Smart City | |
Applications and study options for the BC-based smart city concept | Social issues | Blockchain in Smart City | |
With the deployment of BC, the chain-based food traceability system was used as a case study to improve the effectiveness of supply chain management in the sector. | Supply chain data management | Blockchain in Smart City |
CIA | Attack |
---|---|
Confidentiality [15] | Social Engineering, Eavesdropping, Traffic Analysis, Unauthorized Access, Password Pilfering, MITM, Snifitting, Replay, Masquerading, and Data Injection |
Integrity [16] | Tampering, Replay, Wormhole, False Data Injection, Spoofing, Data Modification, Time Synchronization, Load Drop, MITM, and Masquerading |
Availability [17] | Wormhole, Jamming, Denial of service, LDos, Buffer Overflow, Teardrop, Smurf, MITM, Spoofing, Puppet, Time Synchronization, and Masquerading |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Waseem, M.; Adnan Khan, M.; Goudarzi, A.; Fahad, S.; Sajjad, I.A.; Siano, P. Incorporation of Blockchain Technology for Different Smart Grid Applications: Architecture, Prospects, and Challenges. Energies 2023, 16, 820. https://doi.org/10.3390/en16020820
Waseem M, Adnan Khan M, Goudarzi A, Fahad S, Sajjad IA, Siano P. Incorporation of Blockchain Technology for Different Smart Grid Applications: Architecture, Prospects, and Challenges. Energies. 2023; 16(2):820. https://doi.org/10.3390/en16020820
Chicago/Turabian StyleWaseem, Muhammad, Muhammad Adnan Khan, Arman Goudarzi, Shah Fahad, Intisar Ali Sajjad, and Pierluigi Siano. 2023. "Incorporation of Blockchain Technology for Different Smart Grid Applications: Architecture, Prospects, and Challenges" Energies 16, no. 2: 820. https://doi.org/10.3390/en16020820