This paper presents Zero-Knowledge Federated Learning Guard (ZK-FLGuard), a privacy-preserving and verifiable federated learning framework for real-time anomaly detection in Fifth-Generation Mobile Network (5G)-enabled Internet of Things (IoT) environments. Building on the integration of zero-knowledge proofs (zk-SNARK—Zero-Knowledge Succinct Non-interactive Argument of Knowledge) and blockchain-based access control, ZK-FLGuard ensures the integrity of model updates without exposing private data. Using real-world intrusion detection datasets (CICIDS2017—Canadian Institute for Cybersecurity Intrusion Detection System 2017, TON_IoT—Telecommunications Organisation of the National Security—IoT) and a synthetic adversarial dataset, our evaluation shows that ZK-FLGuard achieves up to 0.96 F1-score (harmonic mean of precision and recall), improves recall in low-frequency attack detection, and introduces less than 10% additional latency overhead compared to standard Federated Learning (FL). Compared with centralized Long Short-Term Memory (LSTM) and FL without Zero-Knowledge Proof (ZKP), ZK-FLGuard provides competitive accuracy while ensuring verifiable computation and strong privacy guarantees. We address the critical challenge of securing federated anomaly detection in 5G-enabled IoT systems against data leakage, model poisoning, and unauthorized access. While FL preserves privacy by keeping raw data local, it remains vulnerable to gradient leakage and adversarial manipulation. Our hypothesis is that combining zero-knowledge proofs and blockchain with FL can deliver a scalable, tamper-resistant, and privacy-preserving detection pipeline suitable for resource-constrained edge environments.
The increasing number of behind-the-meter distributed energy resources (DERs) is changing traditional distribution systems in a big way by adding new ways to control and monitor them. But the effectiveness and dependability of these systems depend heavily on the accuracy of the data (like measurements, control commands, etc.) that the prosumers, aggregators, and grid operators share with each other. In addition, traditional power systems rely entirely on trusted aggregators to gather data from these DERs. If these aggregators are hacked, the whole system could be at risk. In this paper, we respond to these concerns by suggesting a hierarchical blockchain-based framework that includes a distributed integrity auditing system for measuring DERs. By using hash functions and Merkle trees, a secure and lightweight blockchain-based hash aggregation protocol is made to make sure that behind-the-meter DERs' measurements are real. Also, an automated distributed sanity check of DERs' set points (control commands) is suggested to lower the risk of coordinated cyber attacks on a large number of DERs. The suggested framework is put into action and tested in a number of different situations to see how well it works and how safe it is. The results show that the framework can handle more work because it can cut its runtime and storage costs by about 47% and 44%, respectively.
Ileana Maria Muntean, Radu Tîrnovan, Horia G. Beleiu
As renewable generation becomes increasingly deployed at the local level, the reliability of microgrids depends not only on physical infrastructure but also on the credibility of the measurement data driving energy control decisions. In conventional Energy Management Systems (EMS) architectures, monitoring is implicitly assumed to be correct, even though no mechanism exists to verify the authenticity or integrity of the received data. This gap can lead to suboptimal or misleading control actions, especially in distributed environments involving multiple stakeholders. This paper introduces a trust-by-design approach in which monitoring and energy management processes are natively supported by a lightweight Distributed Ledger Technology (DLT) layer embedded within the EMS. Rather than relying on external trust assumptions, the proposed mechanism ensures built-in traceability and tamper-evidence, enabling independent validation of the microgrid’s operational history. A simple renewable microgrid with battery storage is used as a demonstrative case study to show how a DLT-based ledger can safeguard measurement integrity and control decisions without adding technical complexity to the EMS itself. The results demonstrate that verifiable data flows and tamper detection significantly enhance the transparency and robustness of EMS architectures, while enabling future extensions towards predictive or AI-assisted control strategies.
Kent Douglas Lambert, Tom Bradley, John M. Borky, Steve Simske · 6 authors
This research identifies a set of practical solutions to the uncontrolled growth of malicious cross-industry cybersecurity threats. Given the presence of the behaviors and negative effects of cyber threats, the research seeks to understand the effects of three eco-system-wide strategies for cyber defense: Defense-in-Depth (DiD), Zero-Trust Architectures (ZTA), and secure cryptographic key provisioning. These strategies are developed using the BlockFrame, Inc., Eco-Secure Provisioning™ (ESP™) Framework, blockchain-assisted digital logistics management and governance, and the application of Emergence Theory and Uniformity. The research addresses five specific questions to organize the approach, with practical translations of this research to selected industrial use cases.
Open access
Systems Engineering Methodologies and Applications
Infrastructure Resilience and Vulnerability Analysis
A infraestrutura das redes de registro distribuído (DLT) atravessa uma fase de escrutínio rigoroso quanto à sua viabilidade ambiental e eficiência operacional. Este relatório técnico analisa exaustivamente os três principais paradigmas de consenso contemporâneos: Proof of Work (PoW), Proof of Stake (PoS) e Proof of History (PoH), sob a ótica do custo-benefício energético e da segurança sistêmica. O Proof of Work, embora detentor de uma robustez histórica inigualável, apresenta um consumo elétrico de proporções nacionais, demandando cerca de 1.375 kWh por transação na rede Bitcoin. O Proof of Stake, consolidado pela transição do Ethereum, reduziu o dispêndio energético em 99,95%, operando com uma média de 0,0026 kWh por transação através da substituição da exaustão computacional pelo compromisso de capital. O Proof of History, atuando como um relógio criptográfico integrado ao PoS na rede Solana, otimiza a ordenação temporal e a escalabilidade, resultando em um consumo marginal de 0,00051 kWh por transação, o mais eficiente entre os protocolos de alta performance. O estudo conclui que a migração para modelos de baixo consumo e alta vazão (throughput) é impulsionada não apenas por avanços técnicos, mas por marcos regulatórios como o MiCA da União Europeia, que exige transparência absoluta sobre o impacto climático dos ativos digitais.<br>
Madina Konyrova, Katipa Chezhimbayeva, Abdul Razaque, Dina S.M. Hassan
The integration of renewable resources and prosumers into smart grids poses challenges related to scalability, transparency, and transmission efficiency. Centralized routing frequently depends on expensive technology and experiences significant losses. This study presents a blockchain-based smart contract system (BSCS) that reduces transmission losses while guaranteeing secure and decentralized energy transfers. The smart grid is represented as a weighted directed graph, with edges denoting actual power losses. Dijkstra’s shortest path algorithm generates optimal paths from the generator to the consumer with minimal loss. These optimal pathways are permanently documented and regulated by permissioned blockchain smart contracts, ensuring tamper-proof and verifiable energy settlement. Validation is performed using an enhanced IEEE 58-bus test system, which is based on the standard IEEE 57-bus network, by incorporating an additional synthetic consumer node (Bus 58) linked to Bus 12 to simulate a flexible prosumer load of 1.5 MW + 0.5 Mvar. Additionally, the synthetic consumer node employs Ganache, Truffle, and Solidity for its implementation. This modification facilitates the assessment of dynamic energy routing and decentralized transaction settlement in extended topology scenarios. The proposed BSCS demonstrates substantial enhancements compared to baseline blockchain systems. Active power losses in transmission lines are diminished, gas consumption declines by approximately 12%, latency is enhanced by as much as 21%, and throughput increases by more than 30%. The rapid deployment and execution of smart contracts within sub-second intervals validate the system's appropriateness for real-time grid operations. The proposed technique combines graph-theoretic optimization with blockchain governance to provide a safe, scalable, and hardware-independent framework for decentralized energy markets.
Michele Fabi, Viraj Nadkarni, Leonardo Leone, Matheus V. X. Ferreira
<div> We develop an axiomatic theory for Automated Market Makers (AMMs) in local energy sharing markets and analyze the Markov Perfect Equilibrium of the resulting economy with a Mean-Field Game. In this game, heterogeneous prosumers solve a Bellman equation to optimize energy consumption, storage, and exchanges. Our axioms identify a class of mechanisms with linear, Lipschitz continuous payment functions, where prices decrease with the aggregate supply-to-demand ratio of energy. We prove that implementing batch execution and concentrated liquidity allows standard design conditions from decentralized finance-quasi-concavity, monotonicity, and homotheticity-to construct AMMs that satisfy our axioms. The resulting AMMs are budget-balanced and achieve ex-ante efficiency, contrasting with the strategy-proof, expost optimal VCG mechanism. Since the AMM implements a Potential Game, we solve its equilibrium by first computing the social planner's optimum and then decentralizing the allocation. Numerical experiments using data from the Paris administrative region suggest that the prosumer community can achieve gains from trade up to 40% relative to the grid-only benchmark. </div>
Gauhar Ali, Sajid Shah, Mohammed ElAffendi, Naveed Ahmad
Introduction Digital Twins (DT) have appeared as a significant tool in Industrial Internet of Things (IIoT) environments, allowing real-time monitoring, predictive maintenance, and maximizing device performance. However, integrating DTs with IIoT initiates serious security issues, specifically in the device’s authentication and authorization. The state-of-the-art mechanisms are exposed to insider threats, single points of failure, and privacy issues. Methods This study proposes a blockchain-based access control framework for cross-domain DTs. The blockchain (BC) integration eliminates reliance on the centralized authentication server. It uses platform verification from the manufacturer to validate IIoT device integrity and mitigate insider threats. Moreover, the authorization mechanism is implemented using smart contract and access control policies stored in BC. The proposed Non-Fungible Tokens enable role and permission delegation. Results and Discussion The integration of Hyperledger Fabric BC, platform hash verification, and NFT-based authorization in the proposed architecture enhanced its resilience against cyber-attacks i.e., replay, DoS/DDoS, insider, and spoofing attacks. Moreover, the proposed framework validates its viability with response times (approximately 300ms) for the authentication and authorization phases. Additionally, identity resolution attains 67 % depletion in latency compared to its counterpart.
G.B. Bhavana, R. S. Anand, J. Ramprabhakar, Josep M. Guerrero · 6 authors
Integration of renewable-energy (RE) sources of energy into local microgrids, decentralised energy markets using blockchain based peer-to-peer (P2P) energy trading is gaining more traction due to its ability to enable transparent, autonomous, and secure transactions among distributed energy resources (DERs). Due to the large variety in microgrid topologies and their respective operational constraints, a key challenge to obtaining the most effective trading framework is the choice of blockchain consensus protocol that suits a given microgrid type. Choice of consensus mechanism solely affects the reliability and security of a network. This paper presents a quantitative comprehensive evaluation of various blockchain consensus mechanisms such as Proof-of-Work (PoW), Proof-of-Stake (PoS), Delegated Proof-of-Stake (DPoS), Proof-of-Elapsed-Time (PoET), Practical Byzantine Fault Tolerance (PBFT), Raft, and Tendermint to determine their suitability for P2P energy trading in microgrids. Various metrics such as fault tolerance, energy efficiency, latency, throughput and consensus time were evaluated for multiple consensus mechanisms through simulations. This paper also studies node-scaling impact on the protocols and presents a final decision framework to match the suitable protocol with various microgrid topologies.
R Udayakumar, A Haja Alaudeen, Anjali Goswami, N Arvinth · 5 authors
Blockchain technologies incorporated with decentralized energy grids can offer new paradigms in energy management, distribution, and consumption. Trust building among participants in decentralized energy systems is a critical challenge in the absence of a central authority. Foremost, the self-executing, fully autonomous blockchain-based smart contracts and the decentralized automated systems enable real-time, secure, and transparent business transactions. This paper examines the domain of smart blockchain contracts in decentralized energy grids. Smart contracts facilitate self-enforcement, aiding trust-building. Invoice blockchain contracts enable automated energy exchange, thereby facilitating contract execution without third-party involvement. Trust-building, system decentralization, energy producers and consumers bypassing operators, and operational cost reduction for self-sustainability provide system autonomy. The paper also discusses self-governing blockchain contract systems engineering. In smart energy contracts, the paper outlines system challenges, which include load, interoperable infrastructure, and energy consumption. Empirical and case study research, which are the primary focus of the paper, present blockchain contracts for decentralized energy systems as a trust-management and transaction-integration technology.
This work introduces the Adversarial Cost Model (ACM v1.0), a formal security framework unifying computational, economic, and physical attack costs in a single rational adversary model. Unlike traditional security models based purely on computational hardness, ACM evaluates real-world feasibility of attacks under post-quantum cryptography, behavioral authentication, zero-knowledge proof systems, and decentralized governance. The model formalizes adversarial actions through total cost functions combining time complexity, hardware requirements, capital liquidity, and physical laboratory constraints. Multiple critical attack classes are analyzed, including hybrid side-channel + Grover attacks, GAN-based behavioral cloning, flash-loan Sybil governance attacks, post-quantum brute-force exhaustion, and zero-knowledge proof forgery. The results demonstrate that many real-world system failures arise not from cryptographic weakness, but from mispriced economic atomicity and cost-free identity or governance acquisition. ACM provides a rationality threshold theorem formalizing when attacks become economically and physically irrational. The model directly informs secure system architecture design by enforcing multi-layer cost escalation across cryptographic, physical, behavioral, and governance layers. This work is intended for cryptography, blockchain security, adversarial machine learning, economic attack modeling, and post-quantum system design.
Open access
Cryptographic Implementations and Security
Smart Grid Security and Resilience
Physical Unclonable Functions (PUFs) and Hardware Security
This work introduces the Adversarial Cost Model (ACM v1.0), a formal security framework unifying computational, economic, and physical attack costs in a single rational adversary model. Unlike traditional security models based purely on computational hardness, ACM evaluates real-world feasibility of attacks under post-quantum cryptography, behavioral authentication, zero-knowledge proof systems, and decentralized governance. The model formalizes adversarial actions through total cost functions combining time complexity, hardware requirements, capital liquidity, and physical laboratory constraints. Multiple critical attack classes are analyzed, including hybrid side-channel + Grover attacks, GAN-based behavioral cloning, flash-loan Sybil governance attacks, post-quantum brute-force exhaustion, and zero-knowledge proof forgery. The results demonstrate that many real-world system failures arise not from cryptographic weakness, but from mispriced economic atomicity and cost-free identity or governance acquisition. ACM provides a rationality threshold theorem formalizing when attacks become economically and physically irrational. The model directly informs secure system architecture design by enforcing multi-layer cost escalation across cryptographic, physical, behavioral, and governance layers. This work is intended for cryptography, blockchain security, adversarial machine learning, economic attack modeling, and post-quantum system design.
Open access
2 source records
Cryptographic Implementations and Security
Smart Grid Security and Resilience
Physical Unclonable Functions (PUFs) and Hardware Security
Efficient energy sharing among solar-based microgrids was crucial for enhancing grid reliability, scalability, and sustainability in modern energy systems. This research presents a novel blockchain-powered decentralized energy trading framework that integrates Raspberry Pi 4, IoT-driven real-time monitoring, and Ethereum-based smart contracts to facilitate seamless and secure peer-to-peer (P2P) energy exchange. The proposed system enables real-time data acquisition and transmission of critical energy parameters, including current, voltage, and power generation, from five interconnected solar microgrids. Raspberry Pi 4 serves as the centralized edge computing node, aggregating and transmitting real-time energy data to the ThingSpeak IoT platform, where advanced AI-driven analytics optimize grid efficiency. Blockchain technology, specifically Ethereum with Ganache, was employed to create a tamper-proof, transparent, and trustless energy marketplace, eliminating reliance on centralized energy intermediaries. The incorporation of Solidity-based smart contracts automates transactions, ensuring secure, immutable, and fair energy trading while enabling dynamic pricing models based on real-time demand-supply conditions. Python, integrated with Web3.py, facilitates seamless interaction between Raspberry Pi 4 and the blockchain network, ensuring low-latency transaction execution and verifiable trade settlements. Through the integration of IoT-enabled smart grids, blockchain-based energy transactions, and AI-driven predictive analytics, the proposed system offers a scalable, autonomous, and energy-efficient solution for decentralized energy management. Experimental validation confirms the system's effectiveness, demonstrating its ability to achieve real-time energy balancing, seamless P2P trading, and enhanced security through blockchain immutability. This cutting-edge approach significantly advances the adoption of renewable energy sources, optimizes microgrid autonomy, and reinforces the resilience of next-generation smart power networks, paving the way for a sustainable and decentralized energy economy.
Nan Geng, Can Zhou, Jiafeng Feng, Xin Zhang · 7 authors
The advancing integration of Cyber-Physical-Social Systems (CPSS) within the modern power industry has highlighted the need for enhanced data integrity and multi-entity coordination. In this context, the pursuit of secure and trustworthy lifecycle management for power materials, regarded as a foundational component in ensuring system stability and operational efficiency, has attracted increasing attention. However, existing systems often face limitations such as information opacity, insufficient data accuracy, and the absence of a secure trust mechanism, hindering intelligent development and long-term sustainability. Blockchain technology, distinguished by its distributed ledger, transparency, immutability, and smart contract capabilities, offers a promising solution by enhancing data security and ensuring information reliability. This study introduces a blockchain-based framework for the secure and trustworthy lifecycle management of power materials within CPSS environments, which ensures lifecycle traceability, real-time monitoring, and trustworthy information exchange. By integrating key application scenarios, such as refined equipment management and paperless execution of contracts, the proposed approach addresses crucial operational needs. A multidimensional analysis with conventional systems reveals its advantages in improving management efficiency, optimizing resource allocation, enhancing data security, and reducing operational costs. The proposed framework thus provides both theoretical foundations and practical pathways for leveraging blockchain in power material lifecycle management, enabling digital transformation, managerial innovation, and collaborative industry development.
Joel Poncha Lemayian, Ghyslain Gagnon, Kaiwen Zhang, Pascal Giard
Ethereum leverages smart contracts (SCs) to power decentralized applications (dApps), with execution handled by the Ethereum virtual machine (EVM) within an Ethereum client. Other blockchain platforms, including Avalanche, Polkadot, Aurora, and Cardano, have also adopted the EVM. However, the performance of the EVM is often constrained by the limitations of general-purpose processors, a challenge that has been explored in the literature. This work aims to further address the limitation by proposing EVMx, a dedicated single-core SC execution engine implemented on a field programmable gate array (FPGA). EVMx follows a processor-like architecture inspired by the RISC philosophy. By exploiting the parallelism and high-speed processing capabilities of FPGA hardware, EVMx achieves a 61% to 99% reduction in execution time for commonly used operation codes compared to traditional central processing unit (CPU)-based environments. Furthermore, EVMx executes entire Ethereum blocks with a percentage reduction in execution time between 6% and 56% against comparable FPGA implementations and 98% to 99% compared to CPU-based EVMs in the literature. These results demonstrate the potential of EVMx to significantly accelerate SC execution and enhance the performance of EVM-compatible blockchains.
The rapid progress of quantum computing poses significant challenges to traditional cryptographic mechanisms, necessitating the adoption of post-quantum cryptography (PQC) solutions. This paper proposes a Quantum-Enhanced Security for Smart Meters (QESM) system to protect power plant data in smart cities, integrating Kyber for secure key exchange, FALCON (Fast-Fourier Transform over Lattice-based Cryptography) for quantum-resistant digital signatures, and ZKP (Zero-Knowledge Proof) for effective verification without revealing sensitive data to secure power plant data against quantum attacks. To evaluate the security of the proposed system, we analyze its resistance to various quantum threats, including Shor’s algorithm, Grover’s algorithm, quantum key analysis, quantum reversal encryption, quantum amplification, quantum switching, and quantum collision attacks. In the current study, accurate measures were used and the average was approximately 7.065 (bits/byte) for randomness, the average execution time was 6.202 milliseconds, the average memory consumption was approximately 4.343 KB, 6.4 Completeness was equal to 1 and unforgeability was 100%. As for the average throughput, it was approximately 485,605 operations per second. That shows the QESM system provides strong security and efficiency, making it a viable solution for protecting the electricity infrastructure in smart cities in the quantum era.
Collin Arnold Kabwama, Osorachukwu Maurice Ayozie, Justin Njimgou Zeyeum, Adeniran Oluwatoyosi Awe · 6 authors
As Critical National Infrastructure (CNI) becomes increasingly digitized, traditional reactive security assessments are failing to keep pace with automated threats. This paper proposes an autonomous framework integrating Generative Adversarial Networks (GANs) and Distributed Ledger Technology (DLT) for proactive vulnerability discovery and immutable infrastructure hardening. We utilize a Physics-Aware Wasserstein GAN to synthesize protocol-specific attack vectors that identify "zero-day" weaknesses in Industrial Control Systems (ICS) by exploring the operational state space of protocols like DNP3 and Modbus. Discovered vulnerabilities are committed to an Immutable Knowledge Base (IKB) on a sharded, permissioned blockchain, providing a "Single Source of Truth" for cross-sector threat intelligence. To automate mitigation, Smart Contracts orchestrate infrastructure hardening by validating patches through digital twin simulations before network-wide deployment. Experimental results using HELICS and NS-3 demonstrate that this architecture reduces the Mean Time to Remediate (MTTR) from days to sub-second intervals. Finally, we address long-term security by incorporating Post-Quantum Cryptography (PQC) to protect the ledger against emerging quantum threats.
Open access
Smart Grid Security and Resilience
Software-Defined Networks and 5G
Infrastructure Resilience and Vulnerability Analysis
The integration of Industrial Automation Systems (IAS) with the Internet of Things (IoT) under Industry 4.0 has significantly enhanced operational efficiency but also exposed critical communication infrastructures to cyber threats. Conventional security frameworks often fail to ensure end-to-end data integrity, authentication, and confidentiality in real-time industrial networks. This paper proposes a blockchain-enabled mathematical cryptography model designed to secure data transmission between industrial nodes. The framework utilizes Elliptic Curve Cryptography (ECC) for lightweight key generation, SHA-3 hashing for immutable transaction records, and smart contract-based consensus for autonomous trust management within a distributed ledger. A simulated industrial environment demonstrates that the proposed model achieves 42% faster encryption-decryption cycles and a 38% reduction in data latency compared to traditional asymmetric cryptosystems. The mathematical foundation ensures provable security under discrete logarithm assumptions, while blockchain consensus guarantees tamper resistance and auditability. This study contributes a scalable, mathematically robust architecture for secure data transmission in automation networks, offering potential integration within Supervisory Control and Data Acquisition (SCADA) and Programmable Logic Controller (PLC) environments.
Open access
Smart Grid Security and Resilience
Physical Unclonable Functions (PUFs) and Hardware Security
Bhabendu Kumar Mohanta, Ali Ismail Awad, Tarek Elsaka, Hamza Kheddar · 5 authors
Intelligent devices with embedded technology have proliferated dramatically over the past decade. The Internet of Things (IoT) has emerged as a transformational force, advancing traditional systems to previously unattainable levels of intelligence. Smart cities, transportation, healthcare, supply-chain management, agriculture, water management, and smart grid (SG) systems are among the industries where the IoT has found applications. These developments are demonstrated by the integration of IoT systems into SG networks, offering significant improvements in sustainability, dependability, and efficiency. Such systems use various IoT devices to continuously monitor the environment and transmit data for processing and analysis. Nonetheless, the growth of the IoT has introduced security vulnerabilities, including concerns about user identification, data integrity, and trust, especially in SG applications. This study aims to resolve several security challenges in IoT-enabled SG applications to support sustainability. The proposed scheme effectively tackles critical security requirements such as data integrity, user anonymity, distributed storage, trust management, and decentralized architecture. The security concerns addressed by blockchain technology include preserving data integrity, fostering trust, providing secure communication, and enabling effective monitoring. Smart contracts automate system processes and are effective in maintaining user trust. The experimental findings support the viability of the proposed system, demonstrating a computational cost of 3.150 ms and a communication overhead of 992 bits, both representing improvements over various existing solutions. Additionally, the deployment cost for the smart contract is found to be 5.64 USD with a writing cost of 2.89 USD, both of which are lower than the costs associated with comparable approaches.
The rapid decentralization and digitalization of local electricity markets have introduced new cyber-physical vulnerabilities, including key leakage, data tampering, and identity spoofing. Existing blockchain-based solutions provide transparency and traceability but still depend on classical cryptographic primitives that are vulnerable to quantum attacks. To address these challenges, this paper proposes Q-EnergyDEX, a zero-trust distributed energy trading framework driven by quantum key distribution and blockchain. The framework integrates physical-layer quantum randomness with market-level operations, providing an end-to-end quantum-secured infrastructure. A cloud-based Quantum Key Management Service continuously generates verifiable entropy and regulates key generation through a rate-adaptive algorithm to sustain high-quality randomness. A symmetric authentication protocol (Q-SAH) establishes secure and low-latency sessions, while the quantum-aided consensus mechanism (PoR-Lite) achieves probabilistic ledger finality within a few seconds. Furthermore, a Stackelberg-constrained bilateral auction couples market clearing with entropy availability, ensuring both economic efficiency and cryptographic security. Simulation results show that Q-EnergyDEX maintains robust key stability and near-optimal social welfare, demonstrating its feasibility for large-scale decentralized energy markets.
The smart grid (SG) plays a seminal role in the modern energy landscape by integrating digital technologies, the Internet of Things (IoT), and Advanced Metering Infrastructure (AMI) to enable bidirectional energy flow, real-time monitoring, and enhanced operational efficiency. However, these advancements also introduce critical challenges related to data privacy, cybersecurity, and operational balance. This review critically evaluates SG systems, beginning with an analysis of data privacy vulnerabilities, including Man-in-the-Middle (MITM), Denial-of-Service (DoS), and replay attacks, as well as insider threats, exemplified by incidents such as the 2023 Hydro-Québec cyberattack and the 2024 blackout in Spain. The review further details the SG architecture and its key components, including smart meters (SMs), control centers (CCs), aggregators, smart appliances, and renewable energy sources (RESs), while emphasizing essential security requirements such as confidentiality, integrity, availability, secure storage, and scalability. Various privacy preservation techniques are discussed, including cryptographic tools like Homomorphic Encryption, Zero-Knowledge Proofs, and Secure Multiparty Computation, anonymization and aggregation methods such as differential privacy and k-Anonymity, as well as blockchain-based approaches and machine learning solutions. Additionally, the review examines pricing models and their resolution strategies, Demand–Supply Balance Programs (DSBPs) utilizing optimization, game-theoretic, and AI-based approaches, and energy storage systems (ESSs) encompassing lead–acid, lithium-ion, sodium-sulfur, and sodium-ion batteries, highlighting their respective advantages and limitations. By synthesizing these findings, the review identifies existing research gaps and provides guidance for future studies aimed at advancing secure, efficient, and sustainable smart grid implementations.
The smart grid is the next evolution of electrical power systems, a continuation of the old grids that involves a mix of digital and traditional power grid technologies to allow the potential to communicate in both directions, decentralized energy production and real-time monitoring. However, such a connection exposes it to cyber attacks, data fraud, and unauthorized access as well. Blockchain technology is one of these technologies because it is transparent, immutable, and decentralized to overcome these security obstacles. In this paper, an overview of blockchain technology smart grid security, architecture, consensus algorithm, and application are presented. Some of the most notable blockchain works in the smart grid include secure energy trading, decentralised identity management, detecting attacks and preserving privacy. When applied in smart grids, reviewed blockchain protocols also comprise Proof of Work (PoW) and Proof of Stake (PoS) along with Practical Byzantine Fault Tolerance (PBFT). Top of that, there are hybrid types of blockchain such as artificial intelligence (AI) and the Internet of things (IoT) that are also covered as the next picture to enable the system to become more scalable and interoperable. Power consumption, time wastage, and regulation hurdle is greatly considered. This paper has concluded that blockchain is a bottom-up technology, which can cause smart grid infrastructures to be much more resilient, transparent, and efficient.