Akshay Chaudhary, Prateek Negi, Amit Dimari, Rohan Rohan
Energy suppliers, entrepreneurs, technological developers, financial organizations, national governments, and academics are interested in blockchains or distributed ledgers. Many of these sources believe blockchains may provide considerable advantages and innovation. Smart contracts and blockchains offer transparent, tamper-proof, and secure platforms that may allow new business solutions. This article covers core blockchain topics including system designs and distributed consensus techniques. From peer-to-peer (P2P) energy trading and Internet of Things (IoT) applications to decentralized markets, electric car charging, and e-mobility, opportunities, problems, and constraints are examined.
In Peer-to-Peer (P2P) energy trading for the smart grid, secure and efficient information exchange is essential to protect against privacy risks and cyber threats. This paper introduces a multi-stage information protection scheme that safeguards data privacy, message authentication, and confidentiality in a continuous double auction (CDA)-based trading environment. The scheme functions across three phases: (1) In the home energy data collection stage, short-key homomorphic encryption within a decentralized framework secures user data. (2) During trading, an encryption-signature (E-S) model ensures secure transmission of sensitive bidding information from prosumers. (3) In the implementation phase, a decentralized monitoring system detects and prevents node compromise attacks on power measurements. Evaluations highlight the scheme’s computational feasibility, low time costs, and resilience against cyber-attacks, with tests on the IEEE 39-bus distribution network confirming its security. Furthermore, this scheme addresses limitations of traditional, operator-reliant methods in microgrids. With zero-knowledge proof-based authentication and homomorphic encryption for private energy pricing, the framework uses a lightweight, tree-chained transaction ledger to ensure data integrity. Tests confirm the framework’s support for secure, private energy trading with high accuracy and minimal delays. Lastly, the scheme addresses security and privacy challenges of IoT-integrated smart meters, critical for global energy management but vulnerable to data breaches. Through differential privacy-based aggregation and distributed data validation, the IoT model protects consumer privacy and ensures data integrity. In conclusion, this multi-faceted protection scheme strengthens privacy and security in P2P energy trading for the smart grid, enhancing data protection, system reliability, and user confidence in a decentralized energy landscape.
As the world increasingly adopts renewable energy, the importance of smart grids grows. Integrating renewable sources into the current grid presents technical and economic challenges. Blockchain technology offers a promising solution by enabling decentralized energy trading, allowing efficient exchanges between producers and consumers. This paper proposes a detailed framework for integrating blockchain into the smart grid. The framework includes developing a blockchain-based platform for energy trading, creating smart contracts to manage and automate transactions, and incorporating IoT devices for energy data collection and sharing. By leveraging blockchain's transparency, security, and decentralization, our proposed system aims to address inefficiencies and foster a more resilient energy infrastructure. This approach could enhance the sustainability and reliability of energy distribution, supporting the transition to renewable sources. We believe our framework has the potential to significantly improve the efficiency and sustainability of the smart grid, paving the way for a more robust and adaptive energy system capable of meeting future demands.
In the context of Blockchains and Decentralized Finance the notion of Maximal Extractable Value (MEV) is attracting more and more attention. MEV is the maximum gain that users-including miners and validators-can obtain by interacting with a smart contract and with its dependencies. Such profits witness attacks that also exploit strategic transaction manipulations (e.g., reordering transactions in blocks) and distort the meaning of smart contracts. The use of the notion of noninterference for modeling and analysing MEV attacks has recently been proposed in the literature. Noninterference aims to capture unwanted information flows in multi-level systems. Various definitions of noninterference have been presented, and among these those based on unwinding conditions allow the possible flows to be specifically located in a system. In this paper we investigate the use of such unwinding conditions to analyze MEV. We exploit a simple case study-the Bet contract-to highlight the advantages and disadvantages of our proposal.
In response to global efforts to deal with climate change, various renewable energy policies are being implemented. Among these, renewable portfolio standards (RPS) and renewable energy 100 (RE100) regulate the obligated supply of renewable energy to ensure compliance with set quotas by nations and institutions. In this context, the renewable energy certificate (REC) system is employed to assist obligated entities in meeting their renewable energy generation quotas. Obligated entities can purchase REC from renewable energy generators to obtain recognition for their renewable energy allocation. However, the current REC system is insufficient in addressing issues related to procedural complexity and cyber security. This study aims to overcome its limitations by applying the blockchain technology. Blockchain, a distributed financial network, serves as a digital ledger, enabling peer-to-peer transactions in a simple, transparent, and secure way. The proposed new REC system based on blockchain moves away from the complex structure of the traditional REC system, simplifying the system into four processes: participation, issuance, transaction, and authentication. Moreover, by applying blockchain algorithms, it addresses the cyber security issues of the traditional system. The case study using Hyperledger Besu, or one of blockchain platforms, demonstrates that the aspects of procedural complexity and cyber security are improved in the proposed system.
Mateo D. Roig Greidanus, Gab‐Su Seo, Sudip K. Mazumder
This paper presents a unified multi-timescale control approach for a power system with distributed energy resources to achieve cyber-resilient operation. The proposed concept combines two cyber-resilient control methods: proactive and reactive methods. The proactive method uses a blockchain that ensures measurement and control data can be securely exchanged among grid assets and also derives control set points as a load-sharing supervisory control, with an embedded logic called chaincode. The proactive method ensures data integrity, but it inherits stochastic latency with significant standard deviation due to the nature of the distributed ledgers and security measures, leading to challenges in control. To overcome this trade-off, the reactive approach uses event-driven communication. For this approach, rather than communicating the complete data, a lightweight data packet is communicated in a peer-to-peer fashion. Therefore, it guarantees driving the system into a stable operation in case the proactive operation degrades with insufficient latency. To validate the concept, Hyperleger Fabric blockchain 2.2 is used to characterize the latency and is customized for an inverter control system in this study. Based on the use case, a stability analysis is presented to evaluate the impact of the variable delay and to identify the need for a reactive approach to mitigate the effects of a prolonged delay in the proactive method. A test bed with two hardware inverter prototypes and a custom blockchain programmed with the unified method is developed for validation. A set of hardware experimental results validates the methodology and demonstrates the inverter system operations achieving frequency recovery and load-sharing restoration based on the unified control method.
As the deployment of IPv6 networks continues to expand, managing security threats becomes increasingly intricate due to the protocol’s extensive address space and dynamic traffic patterns. This paper presents a novel blockchain-driven decentralized anomaly detection algorithm designed explicitly for IPv6 networks. By leveraging the inherent properties of blockchain—immutability, transparency, and decentralization—our approach enhances security monitoring capabilities. Integrating traffic analysis with a distributed ledger facilitates improved accuracy in anomaly detection and robust resilience against distributed denial-of-service (DDoS) attacks and other threats. Experimental evaluations conducted in a simulated IPv6 environment demonstrate that the proposed methodology outperforms traditional centralized detection systems, significantly improving detection accuracy, attack mitigation, and data integrity.
Haotian Deng, Tao Liu, Xiaochen Ma, Weijie Wang · 7 authors
The space-air-ground integrated networks (SAGINs) are pivotal for modern communication and surveillance, with a growing number of connected devices. The proliferation of IoT devices within these networks introduces new risks due to potential erroneous synergistic interactions that could compromise system integrity and security. This paper addresses the challenges in coordination, synchronization, and security within SAGINs by introducing a novel static program analysis (SPA) technique using zero-knowledge (ZK) proofs. This approach ensures the detection of risky interactions without compromising sensitive source code, thus safeguarding intellectual property and privacy. The proposed method overcomes the incompatibility between SPA and ZK systems by developing an imperative programming language for SAGINs and a specialized abstract domain for interaction threats. The system translates network control algorithms into arithmetic circuits suitable for ZK analysis, maintaining high accuracy in detecting risks. Evaluations of real-world scenarios demonstrate the system’s efficacy in identifying risky interactions with minimal computational overhead. This research presents the first ZK-based SPA scheme for SAGINs, enhancing security and confidentiality in network analysis while adhering to privacy regulations.
Aakanksha Bedi, J. Ramprabhakar, R. S. Anand, U Kumaran · 6 authors
Smart grids (SGs) are technology-powered electricity networks that support bidirectional power and data flows. This allows real-time monitoring of demand and enhances the grid’s capability to dynamically adjust the generation and reduce the gap between supply and demand. However, implementing a smart grid in the power network comes with its own set of security challenges, such as cyber-security, distrust in participants, and lack of customer engagement due to various cyber-attacks. Such cyber-attacks will create distrust among consumers/prosumers to adopt the smart grid and distributed energy resources (DER) framework. To circumvent this, a blockchain-supported hybrid authentication and handshake algorithm (BSHAHA) for smart grids is proposed in this work, which authenticates data communication between peer-to-peer, aggregators, virtual power plants, and the grid. The algorithm was developed incorporating elliptic-curve cryptography (ECC) and advanced encryption standards (AES) to enhance privacy and session security. The proposed algorithms are verified and tested using formal cyber-security tools, such as the Random oracle model and AVISPA as well as by informal security analysis. Furthermore, to simulate a real-time test environment, this paper utilized ns-3 network simulator to simulate different smart meter scenarios, and the proposed algorithms are tested for power consumption and scalability, and results are presented. Moreover, blockchain simulation was first done in the local blockchain using Ganache and Truffle IDE and later using the Holesky Ethereum test network and remix-IDE. Lastly, this paper presented a comparison analysis of power consumption for different consensus mechanisms.
In the field of Artificial Intelligence (AI), there is an increasing focus on enhancing trustworthiness especially in critical sectors such as in the management of civil infrastructure. This paper proposes the adoption of a framework based on Hybrid Distributed Ledger Technology (Hybrid-DLT) as a technological solution for improving trustworthiness. We detail three specific applications in the sector of critical infrastructure maintenance: Explainable AI (XAI) for risk classification, structural defects recognition, and real-time monitoring through IoT. The proposed approach employs tamper-resistant ledgers for tracking key processes such as dataset collection, model training, and inference generation, thereby ensuring non-repudiability for recorded actions and enabling auditability. We demonstrate how this strengthens the explainability mechanisms of AI models and enables the production of verifiable data lineage and certified inferences. Our framework can be applied to existing AI solutions, enhancing their trustworthiness.
RWAs encapsulate both tangible and intangible assets that exist in the physical world but can be digitally represented through tokenisation on blockchain or other distributed ledger technologies (DLTs). These assets cover a wide array, including cash, commodities, equities, bonds, real estate, art and intellectual property. RWAs play a crucial role in bridging the gap between traditional financial systems and the rapidly evolving digital economy, promising a pathway to more accessible, transparent and efficient asset management and investment opportunities.
The rapid advancement of grid modernization and the proliferation of smart grids have engendered a critical need for cyber-physical security. Recent cyber-attacks targeting grid infrastructure, notably leading to substantial blackouts in Ukraine, underscore the vulnerabilities and potentially catastrophic consequences of such incursions. These attacks, whether stemming from cyber threats such as Denial of Service (DOS), False Data Injection Attacks (FDIA), or complex cyber-physical manipulations, emphasize the imperative of robust cybersecurity protocols in smart grid operations. This research investigates a pivotal approach to fortify and safeguard smart grid systems by integrating blockchain technology with wireless sensor nodes. By leveraging a Proof of Authority (PoA) Ethereum Blockchain framework, the study delves into the transformative capabilities of Blockchain within Supervisory Control and Data Acquisition (SCADA) networks. Specifically, it examines configurations across IEEE 14-bus, 30-bus, and 118-bus topologies. In addition to elucidating the inherent vulnerabilities in traditional SCADA systems, this study meticulously evaluates an array of performance matrices. Statistical analyses encompassing mean, standard deviation, skewness, kurtosis, and confidence levels provide nuanced insights into the efficacy of blockchain mechanisms in enhancing SCADA resilience against contemporary cyber threats. This research endeavors to bridge the gap in modern cybersecurity paradigms by fusing blockchain technology with wireless sensor nodes. By fortifying data integrity, elevating the reliability of data transmission, and augmenting trustworthiness within SCADA infrastructures, this study aims to present robust solutions to the escalating cybersecurity challenges faced by smart grid systems.
Duc‐Minh Ngo, Dominic Lightbody, Andriy Temko, Colin C. Murphy · 5 authors
With the widespread integration of new technologies, IoT devices are becoming increasingly diverse and capable of handling highly complex tasks, compared to previous generations. This evolution has led to demands for a comprehensive security approach across multiple layers of an IoT architecture. This work proposes a scalable security solution from the edge to the cloud, combining Blockchain technology and anomaly-based Intrusion Detection Systems (IDSs). Smart contracts provide a transparent environment for registering and managing IoT devices on the cloud. Specifically, the smart contract includes two authorization levels for managing administrators and IoT devices. Besides, anomaly-based IDSs are deployed at Gateways to detect network attacks. We propose using lightweight machine learning models on FPGA hardware acceleration for Gateways. We have simulated the Blockchain network on the Ganache software, demonstrating that the smart contract effectively manages administrators and devices such that only authorized entities can access the system. The FPGA-based Gateway, which contains pre-trained Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) detection models from the IoT-23 dataset, has been deployed on the Alveo U280 card. The ANN model has achieved the highest processing speed at 20Gbps. The results indicate that integrating Blockchain and anomaly-based IDS significantly enhances scalable security in IoT networks.
Arti Badhoutiya, K Sangamithrai, G. Indira, M. Suganya · 7 authors
The rise of distributed renewable energy microgrids presents new opportunities for localized energy generation, but also poses challenges in energy management, security, and transparency. This paper proposes a Blockchain-Enabled Energy Management System (EMS) for distributed renewable energy microgrids to address these challenges. By leveraging blockchain technology, the system facilitates secure and transparent energy transactions between microgrids, enabling peer-to- peer (P2P) energy trading without reliance on a central authority. Blockchain’s decentralized ledger ensures data integrity, enhances system resilience, and prevents unauthorized access, while optimizing energy distribution across the network. This approach promotes a sustainable and efficient energy ecosystem, ensuring trust and reliability in decentralized energy markets.
Camilla Fioravanti, Christoforos N. Hadjicostis, Gabriele Oliva
Networked Control Systems (NCS) are pivotal for sectors like industrial automation, autonomous vehicles, and smart grids. However, merging communication networks with control loops brings complexities and security vulnerabilities, necessitating strong protection and authentication measures. This paper introduces an innovative Zero-Knowledge Proof (ZKP) scheme tailored for NCSs, enabling a networked controller to prove its knowledge of the dynamical model and its ability to control a discrete-time linear time-invariant (LTI) system to a sensor, without revealing the model. This verification is done through the controller's capacity to produce suitable control signals in response to the sensor's output demands. The completeness, soundness, and zero-knowledge properties of the proposed approach are demonstrated. The scheme is subsequently extended by considering the presence of delays and output noise. Additionally, a dual scenario where the sensor proves its model knowledge to the controller is explored, enhancing the method's versatility. Effectiveness is shown through numerical simulations and a case study on distributed agreement in multi-agent systems.
Julia Groza, Seyyed Ali Sadat, Koami Soulemane Hayibo, Joshua M. Pearce
To assist electric utilities to overcome limitations of centralized billing and encourage distributed production of solar photovoltaic (PV) electricity, this study designs and assesses a novel open-source autonomous virtual utility to monitor users and enable peer-to-peer trading. This study provides system design and software implementation of the concept using blockchain technology written in Solidity and Truffle. A set of smart contracts adds users to a system and monitors their demand, PV generation, and facilitates transactions between users on an hourly basis when one user has PV-generated excess electricity, and another has demand. Unit tests for each of the contracts’ methods are developed in Solidity, and data on gas usage and costs is collected. Once the contracts have been written and evaluated, a JavaScript simulation is developed to use the contracts on real load and PV generation data for one year on an hourly basis. The results of two case studies are quantified: 1) true peers, where all houses are prosumers with rooftop PV, and 2) intermittent transition case, where PV deployment and demand are more varied. The results found that with ten users in the system, the true peers case study resulted in an uneconomic number of exchanges, but the intermittent transition case study resulted in more than a factor of twenty increases in exchanges and net cost savings. The savings more than doubles for both cases when time of use pricing is in effect. The system utility increases with more variability of PV production across participating users and is recommended for utilities targeting increases in distributed generation during the energy transition.
Abdullah Umar, Deepak Kumar, T. K. Ghose, Thamer A. H. Alghamdi · 5 authors
The integration of distributed energy resources (DERs) and digital technologies has accelerated the transition to decentralized energy systems. Among these technologies, blockchain stands out for its ability to facilitate peer-to-peer (P2P) energy trading efficiently and securely. This paper explores the concept of P2P energy trading within community microgrid systems, leveraging blockchain-based smart contracts. The proposed system integrates an incentive-driven demand response program directly into the smart contract framework, offering real-time rewards for load-balancing contributions. By incorporating the microgrid’s Energy Management System (EMS) and transparently recording all transactions on the blockchain, the proposed platform provides detailed data and immediate reward distribution. At the core of our system lies the Supply to Demand Ratio (SDR), ensuring fair energy exchange within the community. Dynamic pricing, enabled by blockchain and Tether (USDT) cryptocurrency, adjusts to real-time market conditions, enhancing transparency and responsiveness in energy trading. This adaptive pricing model fosters a more equitable and efficient trading environment compared to static approaches. Moreover, this system is tailored for community microgrids, emphasizing a community-centric approach. Local prosumers serve as validators in the blockchain network, aligning energy management decisions with community needs and dynamics. This localized engagement promotes efficiency and participation, fostering resilient, sustainable, and user-centric energy landscapes. Through rigorous analysis, we demonstrate the system’s effectiveness in optimizing economic efficiency, reducing operational costs, and increasing compliance rates. By combining blockchain technology with community-focused design principles, the proposed platform represents a significant advancement towards self-sufficiency and resilience in local energy systems.
In the rapidly advancing domain of smart manufacturing, securing data integrity and preventing unauthorized access are critical challenges. This study introduces a novel approach that synergizes anomaly detection techniques with Zero-Knowledge Proofs (ZKPs) to fortify the security framework of smart manufacturing systems. Our methodology employs a combination of data preprocessing, including statistical imputation and data smoothing, alongside advanced anomaly detection using classification methods and neural networks, particularly focusing on deep learning architectures. The detected anomalies undergo verification through zk-SNARKs, a specialized ZKP scheme, ensuring a robust validation process without compromising data confidentiality. Our findings reveal a notable enhancement in the accuracy of anomaly detection, achieving detection rates of approximately 95% for temperature fluctuations and 90% for pressure irregularities, with a significant reduction in false positives. This performance is markedly superior to traditional methods and aligns closely with the highest efficacy rates reported in contemporary studies. Moreover, the utilization of ZKPs for anomaly verification demonstrated a 98% success rate, ensuring the secure and private verification of anomalies. The integration of anomaly detection with ZKPs presents a significant leap forward in addressing the security vulnerabilities inherent in smart manufacturing. This study not only showcases the effectiveness of our approach in enhancing data security and integrity but also sets a benchmark for future research in creating more resilient and trustworthy industrial operations.
N. B. Sai Shibu, Aryadevi Remanidevi Devidas, S. Balamurugan, Seshaiah Ponnekanti · 5 authors
Power outages can severely affect individuals, businesses, and communities, leading to disruptions, economic losses, and safety risks. The existing power recovery strategies often fail to adequately address the challenges associated with such outages. These challenges encompass a range of complexities, including resource allocation disparities, efficient prosumer integration, energy demand variability, and isolated generators. This paper presents a microgrid-centric power recovery strategy that leverages IoT, blockchain, smart contracts, and optimisation techniques for peer-to-peer energy sharing within the microgrid. The proposed strategy comprehensively addresses the challenges associated with the existing power recovery strategies. The paper outlines the system architecture for IoT and blockchain-enabled microgrids, discusses the mathematical modelling for energy sharing, and explores cost-optimal power restoration strategies. An incentive mechanism motivates prosumers to support restoration strategies during outages. Furthermore, the paper describes a blockchain smart contract facilitating peer-to-peer energy exchange in regions affected by power outages. This approach can mitigate the disruptive impact of power outages by providing reliable and community-centric power recovery solutions. Through validation with real-world data from our university’s distribution grid test bed, Mean Time To Recover (MTTR) analysis and performance evaluations using the Hyperledger Caliper benchmark tool, this paper demonstrates its feasibility and effectiveness, paving the way for enhanced power recovery strategies and increased resilience in the face of energy disruptions.