Blockchain Papers

Zeli Wang, Weiqi Dai, Ming Li, Kim‐Kwang Raymond Choo · 5 authors

No abstract is available for this record.

Liana Toderean, Viorica Rozina Chifu, Tudor Cioara, Ionuț Anghel · 5 authors

The household prosumers’ decentralized cooperation and aggregation in energy communities are essential to increase renewable energy penetration and to ensure a successful energy transition. Despite their potential, the prosumers are not motivated to participate in local energy value chains due to the lack of trust and decentralized cooperation models for meeting community welfare and sustainability preferences, most innovation efforts being focused on financial incentives that are anyway very low. In this paper, we propose a solution for prosumers’ decentralized coordination in self-sufficient energy communities using cooperative games on top of a blockchain overlay that considers their complementary energy features and flexibility mobilization. The proposed model for community-level local energy balance fits well in circumstances in which there is a strong motivation in the community to prioritize sustainability and environmental concerns and reduce dependence on external energy. We define a governance model to support the decentralized self-organization of prosumers in coalitions for balancing the renewable generation and demand while considering via tokenization factors that go beyond purely economic motivations and foster cooperation and collaboration among the prosumers in the community. Self-enforcing contracts are used to implement the cooperative game model enabling the decentralized management of prosumers’ coalitions for optimized tokens-based payoff distribution towards self-sufficiency. The evaluation results show our solution’s effectiveness in facilitating the prosumers cooperation in self-sufficient coalitions achieving a minimal difference between the energy consumption and production in the community of approximately 0.01%, with a low transactional time overhead.

Annabelle Lee, Sri Nikhil Gupta Gourisetti, D. Jonathan Sebastian-Cardenas, Kent Lambert · 15 authors

In recent times, Distributed Ledger Technology (DLT) has gained significant attention for its potential application in the energy sector. Utilizing blockchain and DLT has demonstrated the ability to enhance the resilience of the electric infrastructure, which will support a more flexible infrastructure and advance grid modernization. However, the deployment of these technologies increases the overall attack surface. The MITRE ATT&CK® matrices have been developed to document an adversary’s tactics and techniques based on real-world observations. The MITRE ATT&CK® matrices provide a common taxonomy for offense and defense and have become a valuable conceptual tool across multiple cybersecurity disciplines for conveying threat intelligence, performing testing through red teaming or adversary emulation, and enhancing network and system defenses against intrusions. The MITRE ATT&CK® for Industrial Control Systems (ICS) matrix was created to provide knowledge about adversary behavior in the ICS technology domain. This study analyzes the relevance of various tactics and techniques across a seven-layer DLT engineering and cybersecurity stack, known as the DLT stack, designed by the Cybersecurity Taskforce under IEEE P2418.5 - Standard for Blockchain in Energy working group sponsored by Power and Energy Systems - Smart Buildings, Loads and Customer Systems (PES/SBLC) Technical Committee. Additionally, this paper identifies specific mitigation strategies tailored to the energy ICS environment.

Zhenpeng Liu, Mingxiao Jiang, Shengcong Zhang, Jialiang Zhang · 5 authors

Traditional techniques for smart contract vulnerability detection rely on fixed expert criteria to discover vulnerabilities, which are less generalizable, scalable, and accurate. Deep learning algorithms help to address these issues, but most fail to encode true expert knowledge and remain interpretable. In this paper, we present a smart contract vulnerability detection mechanism that operates in phases with graph neural networks and expert patterns in deep learning to mutually address the deficiencies of the two detection approaches and improve smart contract vulnerability detection capabilities. Experiments show that our vulnerability detection mechanism outperforms the original deep learning model by an average of 6 points in detecting vulnerabilities and that the second stage of the checking mechanism can also block contract transactions containing dangerous actions at the Ethernet Virtual Machine (EVM) level and generate error reports for submission. This strategy helps to construct more stable smart contracts and to create a secure environment for smart contracts.

Fernando Bereta dos Reis, Mark Borkum, Monish Mukherjee, D. Jonathan Sebastian-Cardenas

This paper explores the potential of distributed ledger technology (DLT) to improve fault-tolerant grid operations by leveraging its core features as an immutable, decentralized ledger, a distributed, consensus-based agreement process, and a distributed state-replication engine. Distribution power systems deliver electricity to millions of customers; however, they are susceptible to various threats that can result in customer interruptions. These include faults caused by adverse weather conditions, natural disasters, vegetation growth, equipment failure, and malicious attacks. To minimize the effects of these faults, fault-handling approaches rely on network knowledge to isolate affected areas and reconnect unaffected areas, reducing the number of affected customers while maintaining safety. Here, we present a trusted data-sharing architecture that enables independent, distributed actors to reconstruct the pre-fault system state by enabling distributed resources to make appropriate decisions with limited network/system information. Although the process requires some data sharing between switch-delimited areas, the approach limits the amount of private information shared, preserving customers’ privacy and business-sensitive information. We include three use cases that form a foundation for third parties to develop functional solutions that can eventually be deployed in the field. The gross error detection method used within switch-delimited areas can identify sensor errors and accurately detect circuit breaker states. The evaluation of possible reconnection while preserving data ownership resulted in a voltage magnitude difference smaller than 0.01% from the OpenDSS power flow solution that has full system knowledge, which is below the expected power flow tolerance. The approach offers a promising opportunity for improving fault-tolerant distribution grid operations.

Ahyun Song, Euiseong Seo, Heeyoul Kim

DeFi, a decentralized financial service based on blockchain, not only provides innovative financial services, but also poses various risks, such as the Terra Luna crash. Therefore, anomaly detection in DeFi is necessary to ensure the safety and reliability of the DeFi ecosystem. However, this is very difficult because of the complex protocol, interaction among smart contracts, and high market volatility. In this study, we propose a novel method to effectively detect anomalies in DeFi. To the best of our knowledge, this is the first study that utilizes deep learning to detect anomalies in DeFi. We propose a deep learning model, anomaly VAE-Transformer, which combines the variational autoencoder to extract local information in the short term, and the transformer, to identify dependencies between data in the long term. Based on a deep understanding of DeFi protocols, the proposed model collects and analyzes various on-chain data of Olympus DAO, a representative DeFi protocol, for extracting features suitable for anomaly detection. Then, we demonstrate the superiority of the proposed model by analyzing four anomaly cases detected successfully by the proposed model in Olympus DAO. A malicious attack attempt and structural changes in DeFi protocols can be identified quickly using the proposed method; this is expected to help protect the assets of DeFi users and improve the safety, reliability, and transparency of the DeFi market. The dataset and codes are available athttps://github.com/fialle/Anomaly-VAE-Transformer

Yousef Sanjalawe, Salam Al-E’mari

Numerous abnormal transactions have been exposed as a result of targeted attacks on Ethereum, such as the Ethereum Decentralized Autonomous Organization attack. Exploiting vulnerabilities in smart contracts, malicious users can pursue their own illicit objectives through abnormal transactions. Consequently, identifying these malevolent users, implicated in fraudulent activities and their attribution, becomes exceedingly complex. Cryptocurrency transactions used for malicious purposes, employing pseudo-anonymous accounts to send and receive ransom payments and accumulating funds under various identities, further highlight the need to control and detect these abnormal transactions for maintaining a high level of security within the Ethereum network. Although existing Intrusion Detection Systems (IDSs) help mitigate abnormal transaction occurrences, their performance necessitates improvement. To address this issue, this study presents a novel approach, named Abnormal Transactions Detection Using a Semi-Supervised Generative Adversarial Network (ATD-SGAN), which efficiently detects abnormal attacks within the Ethereum network. ATD-SGAN leverages a semi-supervised generative adversarial network for this purpose. The results demonstrate that ATD-SGAN significantly enhances the performance of state-of-the-art IDSs. It achieves an increase in detection accuracy from 3.78% to 11.05% and reduces the false alarm rate from 42.29% to 0.15%. Moreover, ATD-SGAN notably improves the F1-measure, ranging from 10.39% to 3.79%, compared to the current IDSs.

Sthembile Mthethwa, Morné Pretorius

The ongoing push for the 4th industrial revolution is setting the stage to digitise, persist and verify identity along with credentials. Academic and skills credentials are currently verified manually and have much scope for automation using cryptographic techniques but requires standardisation to facilitate future systems interoperability. The Distributed Ledger Technology (DLT) and World Wide Web Consortium (W3C) Verifiable Credentials (VC) standards presents the possibility to achieve this credential verification automation. To accomplish this, an understanding of various DLTs and requirements for a viable skills tracking system is important. Therefore, this research aims to access the selected DLTs against the assessment criterion presented and an analysis has been completed to determine which DLT is suitable for the proposed system. The DLTs are assessed in terms of their ability to support the rapid prototyping of such a system and provide recommendations to guide a future development path from the perspective of standards compliance. We conclude that few DLTs possess the maturity to provide proper requirements coverage due to the emergent nature of the DLT space. Additionally, this paper presents the high-level requirements to achieve a minimally viable solution that can demonstrate such digital credential verification in the academic and skills tracking context.

Shekh S. Uddin, Rahul Joysoyal, Subrata K. Sarker, S. M. Muyeen · 14 authors

Technological advancements in smart grid energy systems (SGESs) are introducing sustainable frameworks to meet the demand for the fourth industrial energy revolution. These frameworks are planned to be used in the forthcoming future to maintain the energy network operation with optimization, energy trading, grid automation, and so on. Blockchain (BCn), developing after passing a diverse period of the research journey, comes to the mind of researchers and its integration in SGES paves the way to reach the goal of energy demand. However, still of interest is ongoing in the improvement of BCn features which can be regarded as the next-generation blockchain framework. This paper exhibits the technical framework of the next-generation BCn framework and explores its benefits and challenges in performing the emerging aspects of SGES. This framework enables some advanced features for the sustainable operation of SGES like smart metering, peer-to-peer (P2P) energy trading, self-operation, and transparency. The technical explanation of this BCn technology established on essential features and requisites is also presented in this paper from various points of view which include smart mechanism, intelligent storage system, and interoperability. We also highlight the recent progress and limitations of the current BCn framework in SGES. Finally, some challenges towards integrating the next-generation BCn technology in SGES are reported. This work can provide extended support for the practitioner and researcher in the context of BCn technology and SGES.

Samir M. Umran, Songfeng Lu, Zaid Ameen Abduljabbar, Xueming Tang

There are numerous internet-connected devices attached to the industrial process through recent communication technologies, which enable machine-to-machine communication and the sharing of sensitive data through a new technology called the industrial internet of things (IIoTs). Most of the suggested security mechanisms are vulnerable to several cybersecurity threats due to their reliance on cloud-based services, external trusted authorities, and centralized architectures; they have high computation and communication costs, low performance, and are exposed to a single authority of failure and bottleneck. Blockchain technology (BC) is widely adopted in the industrial sector for its valuable features in terms of decentralization, security, and scalability. In our work, we propose a decentralized, scalable, lightweight, trusted and secure private network based on blockchain technology/smart contracts for the overhead circuit breaker of the electrical power grid of the Al-Kufa/Iraq power plant as an industrial application. The proposed scheme offers a double layer of data encryption, device authentication, scalability, high performance, low power consumption, and improves the industry’s operations; provides efficient access control to the sensitive data generated by circuit breaker sensors and helps reduce power wastage. We also address data aggregation operations, which are considered challenging in electric power smart grids. We utilize a multi-chain proof of rapid authentication (McPoRA) as a consensus mechanism, which helps to enhance the computational performance and effectively improve the latency. The advanced reduced instruction set computer (RISC) machines ARM Cortex-M33 microcontroller adopted in our work, is characterized by ultra-low power consumption and high performance, as well as efficiency in terms of real-time cryptographic algorithms such as the elliptic curve digital signature algorithm (ECDSA). This improves the computational execution, increases the implementation speed of the asymmetric cryptographic algorithm and provides data integrity and device authenticity at the perceptual layer. Our experimental results show that the proposed scheme achieves excellent performance, data security, real-time data processing, low power consumption (70.880 mW), and very low memory utilization (2.03% read-only memory (RAM) and 0.9% flash memory) and execution time (0.7424 s) for the cryptographic algorithm. This enables autonomous network reconfiguration on-demand and real-time data processing.

Ali Menati, Xiangtian Zheng, Kiyeob Lee, Ranyu Shi · 7 authors

Blockchain technologies are considered one of the most disruptive innovations of the last decade, enabling secure decentralized trust-building. However, in recent years, with the rapid increase in the energy consumption of blockchain-based computations for cryptocurrency mining, there have been growing concerns about their sustainable operation in electric grids. This paper investigates the tri-factor impact of such large loads on carbon footprint, grid reliability, and electricity market price in the Texas grid. We release open-source high-resolution data to enable high-resolution modeling of influencing factors such as location and flexibility. We reveal that the per-megawatt-hour carbon footprint of cryptocurrency mining loads across locations can vary by as much as 50% of the crude system average estimate. We show that the flexibility of mining loads can significantly mitigate power shortages and market disruptions that can result from the deployment of mining loads. These findings suggest policymakers to facilitate the participation of large mining facilities in wholesale markets and require them to provide mandatory demand response.

Jelena Marjanović, Nikola Dalčeković, Goran Sladić

The increasing threat landscape in Industrial Control Systems (ICS) brings different risk profiles with comprehensive impacts on society and safety. The complexity of cybersecurity risk assessment increases with a variety of third-party software components that comprise a modern ICS supply chain. A central issue in software supply chain security is the evaluation whether the secure development lifecycle process (SDL) is being methodologically and continuously practiced by all vendors. In this paper, we investigate the possibility of using a decentralized, tamper-proof system that will provide trustworthy visibility of the SDL metrics over a certain period, to any authorized auditing party. Results of the research provide a model for creating a blockchain-based approach that allows inclusion of auditors through a consortium decision while responding to SDL use cases defined by this paper. The resulting blockchain architecture successfully responded to requirements mandated by the security management practice as defined by IEC 62443-4-1 standard.

Jingjing Wang, Fei Long, Bo Jin, Dangdang Dai · 5 authors

The smart grid has provided a fascinating opportunity to move the energy industry into a new era of reliability, availability and efficiency that contributes to both energy saving and environment protection. Besides, the smart grid has abandoned the single power supply paradigm in traditional power grid, and it can promote information and resource exchange through peer-to-peer transactions. For example, electricity can be traded effectively in real-time, so that all users can be benefited from cost saving. However, the energy trading data may contain sensitive information of the participating parties. If this information is leaked, user privacy might be violated. Moreover, the trading information should be enforced with fine-grained access control. To fulfil these security requirements, we propose a privacy preserving energy trading platform based on smart contract. First, ElGamal encryption is used to protect the privacy of exchanged messages. Second, proxy re-encryption is employed to achieve fine-grained access control, and it is more efficient than attribute based encryption that is widely used in existing solutions. Third, smart contract is used as the arbitrator, and thanks to its attractive characteristics, such as transparency and trustworthy execution, it can replace the trusted third parties in many existing schemes. Security analyses prove that our scheme satisfies all the desirable security requirements, such as correctness, privacy, fine-grained access control, robustness. And performance analyses demonstrate that it is practical for large-scale applications.

Djallel Hamouda, Mohamed Amine Ferrag, Nadjette Benhamida, Hamid Séridi

No abstract is available for this record.

Moein Choobineh, Ali Arabnya, Behrouz Sohrabi, Amin Khodaei · 5 authors

Abstract Blockchain is a powerful technology to facilitate decarbonization, decentralization, digitalization, and democratization (4D's) of the energy systems of the future. The 4D's are the driving forces of transition into new energy systems that are more sustainable, resilient, efficient, and equitable. Although this technology can be applied to a wide spectrum of applications in the power sector, a set of challenges and limitations still need to be addressed to facilitate a full‐scope implementation in energy systems. This paper presents an overview of blockchain technology from its inception through its most recent evolution and presents a thematic review of state of the art in the application of this technology in power systems. Further, it addresses the barriers preventing the power sector from large‐scale, full‐scope adoption of this technology. Finally, the emerging blockchain trends in the near future will be discussed and its potential to facilitate a secure, decentralized energy trading platform will be investigated.

Іnnа Khavina, Yu. V. Hnusov, Oleksandr Mozhaiev

The issue of creating an information security system is very relevant in the world today. One of the urgent tasks is to solve the issues of effective protection of information from both external and internal threats through the creation and implementation of information security management systems in automated systems of enterprises, which, among other things, requires the formalization of the task of protecting information for its subsequent implementation by software and other means. Now there are security analysis systems, for example, that examine the security elements settings of workstations and servers operating systems, analyze the network topology, look for unprotected network connections, examine the settings of firewalls. The disadvantage of these systems is that they are not suitable for monitoring large volumes of network traffic. The solution to this problem is the use of monitoring tools capable of analyzing large amounts of data in real time. Therefore, a significant place in the article is given to the review of developments based on artificial intelligence technologies, namely multi-agent systems, review of information security models, threat risk assessment in automated systems.
 The functional architecture of the information security management system based on a multi-agent system has been proposed to search in real time for information security optimal solutions through the selection of such coalitions of protection mechanisms agents that will allow to build the optimal protection of the automated system according to the selected criteria. The model with complete overlapping of threats has been substantiated and adopted as a basis, which allows to analyze the overall situation and choose strategically important decisions directly during the organization of information security. The essence of of multi-agent systems functioning that implement a decentralized control system based on the work of autonomous agents that can be implemented programmatically has been revealed. The role of threat agents, resource agents, agents of protection mechanisms and their functional purpose have been defined. The problem of searching a set of protection mechanisms agents coalition for the current state of the automated system as a problem of optimal search by the criterion of protection cost, taking into account the value of information, has been generalized. Due to the modularity of the multi-agent system, the further work will be aimed at detailing its components and perfection.

Dina Tarek, Tawfik Ismail

The management of energy consumption and payment transactions using a secure, decentralized energy system framework is essential in the water distribution network (WDN). The water energy market, in which energy may be transformed into a digital asset that is potentially monitored, trackable and tradable, might greatly benefit from the deployment of blockchain technology. This is because the blockchain has transaction privacy, decentralization, security, and immutability features. Furthermore, using blockchain smart contracts enables energy market management operations such as consumers, prosumers, and enterprises to register and track their utilization as well as to be aware of the financial transactions. In this paper, we optimize a secure peer-to-peer (P2P) Ethereum blockchain platform for water energy consumption and payment transactions among WDN reservoirs and customer nodes. Additionally, we developed a WDN energy trading and payment Ethereum smart contract to monitor autonomous pay-per-use payment and energy distribution on the decentralized P2P trade network.

Ran Guo, Weijie Chen, Lejun Zhang, Guopeng Wang · 5 authors

Blockchain technology is currently evolving rapidly, and smart contracts are the hallmark of the second generation of blockchains. Currently, smart contracts are gradually being used in power system networks to build a decentralized energy system. Security is very important to power systems and attacks launched against smart contract vulnerabilities occur frequently, seriously affecting the development of the smart contract ecosystem. Current smart contract vulnerability detection tools suffer from low correct rates and high false positive rates, which cannot meet current needs. Therefore, we propose a smart contract vulnerability detection system based on the Siamese network in this paper. We improved the original Siamese network model to perform smart contract vulnerability detection by comparing the similarity of two sub networks with the same structure and shared parameters. We also demonstrate, through extensive experiments, that the model has better vulnerability detection performance and lower false alarm rate compared with previous research results.

Carine Zakaret, Nikolaos Peladarinos, Vasileios Cheimaras, Efthymios Tserepas · 8 authors

This paper presents a new hybrid approach that is suitable for application to energy smart meter gateways, based on combining both blockchain and Secure Element (SE) technologies serving the roles of a secure distributed data storage system and an essential component for building a "root of trust" in IoT platforms simultaneously. Blockchain technology alone may not completely secure a transaction because it only guarantees data immutability, while in most cases, the data has to be also secured at the point of generation. The proposed combinational approach aims to build a robust root of trust by introducing the SE, which will provide IoT devices with trusted computed resources. The feasibility of the proposed method is validated by testing three different implementation scenarios, using different Secure Element systems (SES) combined with blockchain and LPWAN communication technologies to encrypt, transmit, and save data. This hybrid approach aids in overcoming the obstructions of using any one technology alone, and its use is demonstrated with a case study for an Energy Smart Metering gateway that enables the implementation of a local Peer to Peer energy trading scheme that is end-to-end secure and decentralized.

Yanan Cao, Yujue Wang, Yong Ding, Zhenwei Guo · 6 authors

No abstract is available for this record.

Muhammad Tahir, Najma Ismat, Huma Hasan Rizvi, Asma Zaffar · 6 authors

The looming energy crisis is affecting every sector of the world. The dire need to conserve energy has compelled researchers to bring automation to the power sector. The conservation of energy is one of the biggest challenges Third-World countries are facing in general and in Europe due to the Russian–Ukrainian war. There is a need to introduce such systems that can prevent energy loss and let users buy and sell excessive electricity they have. In the field of power and electricity, the Internet of Things (IoT) plays an active role in the conservation of energy. The new concept of smart grids is widely used for efficient transmission. The technique of blockchain can further reduce the wastage of energy and efficient consumption if it is used with smart grids. This article proposes a smart energy meter based on smart grids and blockchain. The proposed implementation is a demonstration containing a few microgrids, each with its very own blockchain. The users will use energy by making transactions, following the smart contracts. The focus is on the peer-to-peer transactions in a microgrid controlled by blockchain. The architectural design outcomes are a smart energy meter, a smart contract on the Ethereum blockchain, and an android application to monitor and control transactions and energy trade via smart contracts with other consumers.

Daojun Han, Qiuyue Li, Lei Zhang, Tao Xu

In recent years, smart contract vulnerability detection methods mostly view smart contract source code as natural language for processing, which cannot fully capture the semantic and structural features of the source code and has a high rate of false positives and missing positives. To improve the accuracy of vulnerability detection, this paper uses Graph Neural Network to obtain the semantic and structural information of the source code and Convolutional Neural Network to assist learning. We propose a graph neural network-based vulnerability detection model for smart contracts, which transforms smart contracts into control flow graphs, learns graph embedding using graph neural networks, and introduces Convolutional Neural Networks to learn the node order information of control flow graphs, and finally performs vulnerability detection using graph embedding and node order information. Experimenting on real datasets, our accuracy and F1 values are improved and the model can effectively detect smart contract vulnerabilities.

Ahmed Laftimi, Hind El Makhtoum, Raouya Aknin, Youssef Bentaleb

Smart grids, as all other IoT applications, are subject to numerous security challenges because of their component's constrained nature, namely smart meters, which are the weakest link in the network. Although several researchers have tried to solve the authentication issues, they did not provide a complete solution that ensures, at the same time, integrity, availability, and confidentiality of the authentication data and allows the mobility of the smart meters. The new architecture proposed in this article aims to strengthen the authentication process by adding blockchain and artificial intelligence to the current one. The artificial intelligence algorithms implemented in the MDMS server allow the detection of authentication fraud and therefore deny access. Moreover, in addition to storing the authentication data in an immutable ledger, the decentralized nature of the blockchain allows smart meters to connect to any MDMS server belonging to the cluster. The authentication policy is implemented in the smart contract and executed by the blockchain nodes. The other architecture components, namely, the smart meters and the MDMS servers, interact with this smart contract through transactions. The article also introduces the concept of the smart meter reputation, which prevents the authentication of a malicious smart meter. The smart contract used for this purpose is implemented on the remix as Ethereum integrated development environment. The simulation tests have shown the architecture's robustness and resistance against different attacks.

Abhinav Rakesh Chopra, Nirmal‐Kumar C. Nair, Rizki Dian Rahayani

VA3, is a novel web3.0 based individual peer-to-peer platform for electricity settlement between individual New Zealanders with the ability to trade at a sub-household level i.e., multiple accounts within a single home or a portable account per person. We were able create a web3 application based on the base Ethereum network to successfully automate at individual person’s power consumption and production which is fed into a smart contract using a software update to modify the home router to basically act as a home energy management system and then settlements are automatically managed by the smart contracts.