Blockchain Papers

Zhe Chen, Jia Huang, ShengZheng Liu, Haixia Long

No abstract is available for this record.

Yi Yu, Shuai Liu, Yi Huang, C. Y. Chung · 5 authors

With the ongoing development of renewable energy sources, information technologies and physical energy systems are further integrated, which leads to challenges in ensuring the secure and stable operation of renewable energy power systems in the face of potential cyber threats. The strengths of blockchain in cybersecurity make it a promising solution to these challenges. However, existing blockchains are not well-suited for control tasks due to their low real-time performance. Here, we present a consensus mechanism that enables real-time security control of systems, called Proof of Task. Instead of solving meaningless hash puzzles in Proof of Work, Proof of Task addresses problems closely related to the stable operation and control performance of these systems. With the proposed verification mechanism, Proof of Task significantly enhances the real-time performance of blockchain while mines its computational resources for tasks of interest. To demonstrate the effectiveness and necessity of Proof of Task, it is deployed across three renewable energy power systems. The results show that Proof of Task markedly fortifies the security and computing capability of these systems, ensuring their reliable and stable operation. This work highlights the promise of blockchain to facilitate security control and trusted computing of large-scale, complex-dynamic systems. For control systems, blockchain usually exhibits a trade-off between security and real-time performance. Here, authors propose a new mechanism that utilizes multi-party computation and verification with prediction, specifically tailored for real-time security control of renewable energy power systems.

Kamil Erdayandı, Lucas C. Cordeiro, Mustafa Mustafa

This paper proposes a novel Privacy-preserving and Accountable Billing (PA-Bill) protocol for peer-to-peer energy trading markets. It addresses the challenges of discrepancies between committed and delivered energy volumes, ensuring accurate billing, privacy, and accountability. PA-Bill employs a universal cost-splitting mechanism to enhance fairness and prevent indirect privacy leakage. The protocol leverages homomorphic encryption to protect user data and uses blockchain technology to maintain accountability through an immutable and transparent distributed ledger. Additionally, it includes a dispute resolution mechanism to rectify erroneous bill calculations and identify responsible parties, thus ensuring non-repudiation. Our experimental and theoretical evaluations demonstrates that PA-Bill effectively supports large communities of up to 2000 households, offering a computationally efficient, privacy-preserving, and accountable billing solution in a semi-decentralised manner.

Kai Su, Yun Yu, Jianzhong Zhang

Abstract To improve the security and efficiency of smart grid power trading, this study designs a smart grid trading system based on blockchain technology. The transaction module of the system composed of smart contracts and order-matching algorithms is proposed. The credit consensus mechanism of the system adopts a designed credit-based hybrid consensus mechanism. The experimental results showed that under this system, the successful transaction prices of consumers bidding were between the grid price and the recycling price, making bidding more reasonable. The highest power utilization rate was 0.84, the lowest was 0.67, and the transaction throughput exceeded 350TPS. The highest CPU usage was 0.74, the lowest was 0.5, and the highest memory usage was only 0.44. Compared with other systems, the order matching of this system was more reasonable and its performance was better. Furthermore, the system has been subjected to rigorous security testing and is reliable, thereby providing a secure and efficient trading platform for smart grid electricity trading.

Xinxin Fan

Decentralized physical infrastructure network (DePIN) is currently one of the hottest narratives in Web3. In this paper, we present a new thesis of DePIN, namely the modular DePIN infrastructure. By retrospecting the evolution of software development platforms for building physical infrastructure networks, we describe the new technology trend of building DePIN applications on top of a community-owned modular DePIN infrastructure and highlight the characteristics of this new DePIN thesis from both technical and economic perspectives. In particular, the emerging modular DePIN infrastructure brings a number of research challenges that need to be further addressed through collaboration between academia and industry.

Jing Wang

No abstract is available for this record.

Rachida Hireche, Houssem Mansouri, Yasmine Harbi, Al‐Sakib Khan Pathan

Medical risk management is a critical process within healthcare institutions that involves identifying, assessing, and mitigating risks to ensure patient safety and improve care quality. In recent years, the Internet of Medical Things (IoMT) has proved effective in monitoring patient health, particularly during disasters and epidemics such as COVID-19. However, the transmission of information over open channels makes such networks vulnerable to potential attacks. In addition, quantum computing presents a significant threat to current cryptographic algorithms. While existing solutions protect against well-known threats, few address the issue of quantum attacks. To address these challenges, this work presents an effective group authentication scheme for IoMT systems, leveraging post-quantum security using Kyber-PKE and Dilithium, Shamir’s secret sharing (SSS) algorithm, and smart contract. The proposed solution was simulated on the Ethereum platform and evaluated using Hyperledger Caliper, demonstrating its efficiency and scalability. A comparative analysis to recent pertinent works in terms of computation cost, power consumption, and security requirements shows that our system is well suited for various IoMT applications due to its robustness and efficiency.

Vikas Sharma, Akshi Kumar, Kapil Sharma

No abstract is available for this record.

Jalalud Din, Hongsheng Su

This research investigates the integration of blockchain technology into smart grids, focusing on optimizing both electrical billing and peer-to-peer energy trading between producers and consumers. Using blockchain smart contracts, the system automates and secures energy consumption recording, bill calculation, payment processing, and energy transactions. In the electrical billing framework, a blockchain-based approach was developed to model these functionalities, utilizing an EnergyBilling smart contract to calculate bills and an EnergyPayment smart contract to ensure payment accuracy. Validation using actual consumption data from Sinoma Handan’s project site confirmed the system’s accuracy and reliability when cross-verified with mathematical models. Simultaneously, the study explores peer-to-peer energy trading, where producers (represented by Askari Cement Plant.Nizampur, Pakistan) and consumers (Sinoma Handan Ltd, Handan, China.) conduct automated, transparent transactions. Blockchain’s decentralized nature ensures transparency, data immutability, and a secure, tamper-proof record of transactions. The system eliminates intermediaries, enhancing operational efficiency and reducing costs. Key outcomes demonstrate successful transaction execution with detailed settlements, ensuring financial accountability. Our research highlights blockchain’s transformative potential in revolutionizing electrical billing and energy trading. It offers a secure, transparent, and efficient solution while acknowledging scalability, transaction costs, and regulatory hurdles. Future work could focus on real-world implementation, integration with IoT devices for real-time data collection, and scaling these technologies for broader industrial applications in global energy markets.

Alexander Plotkin, K. Starodubov, Yuri Gromov, Alexander Prokofyev

The article addresses the issues related to the need to assess the stability of key infrastructure in systems based on distributed ledger technology against destructive influences. As a method for solving the problem, we propose the use of a mathematical model of stability based on fuzzy logic, built by taking into account the criteria of key infrastructure stability in such systems, categorized by criticality using the method of direct expert evaluation, as well as a classification of potentially destructive influences affecting stability. The results of the research allow for an assessment of the stability of key infrastructure in systems built on distributed ledger technology, enabling the identification of weaknesses in existing information systems, and by eliminating them, increasing the stability of such systems against destructive influences.

Moomin Solahudeen Tando, Sidique Gawusu, Sufyan Yakubu, Owusu Sarfo Kwabena · 6 authors

No abstract is available for this record.

Mohammed Mujeer Ulla, Preethi Preethi, Md. Sameeruddin Khan, L Shakkeera · 5 authors

Strobe appears to be a promising solution to address some of the challenges associated with securing IoT devices. Its lightweight nature and flexibility make it well-suited for deployment in resource-constrained environments such as microcontrollers and small hardware devices. By providing support for cryptographic primitives and network protocols, Strobe offers a comprehensive framework for securing IoT ecosystems. The support for Schnorr signature variant with an elliptic curve or other group primitives further enhances the security features of Strobe, making it suitable for applications where authentication and integrity are crucial. Furthermore, the lightweight implementation of Strobe is particularly noteworthy, as it addresses the constraints imposed by microcontrollers and small hardware devices. By optimizing resource usage and maximizing efficiency, this implementation ensures that Strobe can be deployed effectively in a wide range of IoT devices without compromising performance or reliability. NFTs have been widely used in blockchain systems to represent unique and irreplaceable assets. Traditional NFTs typically have one identifier representing an asset and ownership by a single entity. This work introduces smart NFTs, tagging IoT devices as Tangible Smart Assets. These devices have blockchain account addresses, establish secure communication channels, and operate in different modes based on their token states. By using Physical Unclonable Functions (PUFs), each smart NFT is securely linked to its IoT device, enabling private key recovery and corresponding blockchain address recovery. This secure pairing ensures trusted hardware and software throughout the device's lifecycle. We will demonstrate this concept using ESP32-based IoT devices and the Ethereum blockchain, utilizing the ESP32's SRAM as the PUF.

Sudha Yadav, R. S. Anand

The renewable energy sources become a larger part of the power grid, managing their intermittent nature is of utmost significance. Blockchain technology provides secure and transparent path for energy trading to individuals directly with each other (peer-to-peer) in these systems. Proposed work gives a framework to monitor blockchain-based energy trading, where it tracks the parameters like how much energy is being generated and used, along with the details of trades recorded on the blockchain. It also monitors how well the automated trading agreements (smart contracts) are working and how fast the entire system is running. By keeping an eye on these aspects, the framework can help ensure this new way of trading energy with renewables is secure, transparent, and efficient.

Nujud AlHajri

This paper is intended to elaborate on the 4th Industrial Revolution (Industry 4.0) that will alter and shift technologies and the utilities sector. Alongside advanced Cybersecurity technologies to be aligned with the need for more resilience and secured environments that empower digital transformation. Where we explore the drivers and applications of Cybersecurity considering 4thIR as an engine of digital transformation, that is governed and measured by complying with digital transformation rules, flowing from modern technology to the evolution where the quality of life is measured by its speed, energy, and security. As such, Industrial Control Systems (ICS) are a solid infrastructure for such a digital transformation. As the acceleration of cyberattacks are becoming more sophisticated, a well Cybersecurity strategies must be applied. Furthermore, we propose advanced Cybersecurity solutions for the smart grid that can be addressed by the efficiency of the Next Generation (SOC) and the utilization of Distributed Ledger Technology (DLT).

Chengfei Qi, Yaoyu Wang, Yanpei Zhu, Yachao Wang · 6 authors

In modern power collection systems, ensuring data integrity and transparency is critical for maintaining grid reliability and trust among stakeholders. Traditional centralized systems are vulnerable to tampering, lack transparency, and are susceptible to cyberattacks. In this paper, we propose a Consensus-based Integrity and Transparency Algorithm (CITA) that integrates blockchain technology and smart contracts to enhance data security in decentralized power grids. CITA employs a dual-layer Proof of Stake (PoS) consensus mechanism to ensure the integrity of collected data and automate data verification through smart contracts. By utilizing off-chain storage, the system maintains scalability while reducing energy consumption. Experimental results show that CITA improves data integrity by 99.8%, reduces latency, and provides higher transparency compared to traditional and existing blockchain-based models. This makes CITA an ideal solution for real-time, secure, and scalable power data collection systems.

Yinfeng Chen, B.K.H. Sun, Yaofei Wang, Zhixin Qiu · 5 authors

IOTA is an emerging decentralized computing paradigm for developing blockchain-based Internet of Things (IoT) applications. It has the advantages of zero transaction fees, incremental scalability, and high-performance transaction rates. Despite its well-understood benefits, IOTA nodes need to withstand considerable resource costs to generate the distributed ledger. The main reason for this is that IOTA abandons the original blockchain reward mechanism and does not charge transaction fees. Therefore, in this paper we address the cost optimization issue for IOTA based on Lyapunov optimization theory. We take the first step in investigating the cost optimization problem of IOTA and exploring a new optimization scheme using Lyapunov optimization theory. Our proposed scheme enables IOTA to minimize the total cost of IOTA nodes through a computational optimization algorithm. Then, an optimized transaction rate control algorithm can be designed based on the large deviation theory to reduce orphan tangles that waste computational costs. In addition, we define and deduce the effective width of the tangle to monitor the total throughput and reduce the time spent on cost optimization to avoid unnecessary waste of resources. Lastly, a comprehensive theoretical analysis and simulation experiments demonstrate that the proposed strategy is both efficient and practical.

Preeti Prasada, S.J. Suji Prasad

Cyber-Physical Systems (CPS) have become a research hotspot due to their vulnerability to stealthy network attacks like ZDA and PDA, which can lead to unsafe states and system damage. Recent defense mechanisms for ZDA and PDA often rely on model-based observation techniques prone to false alarms. In this paper, we present an innovative approach to securing CPS against Advanced Persistent Threat (APT) injection attacks by integrating machine learning with blockchain technology. Our system leverages a robust ML model trained to detect APT injection attacks with high accuracy, achieving a detection rate of 99.89%. To address the limitations of current defense mechanisms and enhance the security and integrity of the detection process, we utilize blockchain technology to store and verify the predictions made by the ML model. We implemented a smart contract on the Ethereum blockchain using Solidity, which logs the input features and corresponding predictions. This immutable ledger ensures the integrity and traceability of the detection process, mitigating risks of data tampering and reducing false alarms, thereby enhancing trust in the system's outputs. The implementation includes a user-friendly interface for inputting features, a backend for data processing and model prediction, and a blockchain interaction module to store and verify predictions. The integration of blockchain with Machine learning enhances both the precision and resilience of APT detection while providing an additional layer of security by ensuring the transparency and immutability of the recorded data. This dual approach represents a substantial advancement in protecting CPS from sophisticated cyber threats.

Ru Jia, Yun Li, Yu Zhou, Mingze Gao · 6 authors

The current power networked command system is usually centrally deployed, and there is a risk of data tampering during the command process. This article utilizes the technological advantages of blockchain tamper resistance and traceability to design smart contracts for the entire commanding process, achieving full process tracking of the commanding, orderly storage of instruction information, and effective verification of the operation process. This article first analyzes the security issues existing in the current networked command system and explains the necessity of instruction authentication and verification. Then, combined with the command process, the technical architecture and business logic of the smart contract were designed, including a scheduling instruction certificate contract, a content consistency verification contract, and a sequence verification contract. Finally, according to the scheduling instruction execution scheme of the smart contract, a typical networked ordering process is implemented. Tests have shown that the ordering contract has anti tampering and traceability characteristics, and its performance meets the system requirements.

Sabah Suhail, Mubashar Iqbal, Rasheed Hussain, Saif Ur Rehman Malik · 5 authors

Cyber–physical systems (CPSs) are being increasingly adopted for industrial applications, yet they involve a dynamic threat landscape that requires CPSs to adapt to emerging threats during their operation. Recently, digital twin (DT) technology (which refers to a virtual representation of a product, process, or environment) has emerged as a suitable candidate to address the security challenges faced by dynamic CPSs. DT has the capability of strengthening the security of CPSs by continuously mapping the physical to twin counterparts to detect inconsistencies. The existing DT-based security solutions are constrained by untrustworthy data dissemination as well as limited data sharing among the involved stakeholders, which, in turn, limit the ability of DTs to run accurate simulations or make valid decisions. To address these challenges, this paper proposes a modular framework called TR usted and I ntelligent cyber- P hysica L syst E m (TRIPLE), that leverages blockchain , DTs, and threat intelligence (TI) to secure CPSs. The blockchain-based DT components in the framework provide data integrity, traceability, and availability for trusted DTs. Furthermore, to accurately and comprehensively model system states, the framework envisions fusing process knowledge for modeling DTs from system specification-based and learning-based information and other sources, including infrastructure-as-code (IaC) and knowledge base (KB). The framework also integrates TI for future-proofing against emerging threats, such that threats can be detected either reactively by mapping the behavior of physical and virtual spaces or proactively by TI and threat hunting. We demonstrate the viability of the framework through a proof of concept . Finally, we formally verify the TRIPLE framework to demonstrate its correctness and effectiveness in enhancing CPS security.

Jiajing Wu, Kaixin Lin, Dan Lin, Bozhao Zhang · 6 authors

Cross-chain bridges are essential decentralized applications (DApps) to facilitate interoperability between different blockchain networks. Unlike regular DApps, the functionality of cross-chain bridges relies on the collaboration of information both on and off the chain, which exposes them to a wider risk of attacks. According to our statistics, attacks on cross-chain bridges have resulted in losses of nearly 4.3 billion since 2021. Therefore, it is particularly necessary to understand and detect attacks on cross-chain bridges. In this paper, we collect the largest number of cross-chain bridge attack incidents to date, including 49 attacks that occurred between June 2021 and September 2024, of which 22 were attacks on cross-chain bridge business logic. Our analysis reveal that attacks against cross-chain business logic cause significantly more damage than those that do not. These cross-chain attacks exhibit different patterns compared to normal transactions in terms of call structure, which effectively indicates potential attack behaviors. Given the significant losses in these cases and the scarcity of related research, this paper aims to detect attacks against cross-chain business logic, and propose the BridgeGuard tool. Specifically, BridgeGuard models cross-chain transactions from a graph perspective, and employs a two-stage detection framework comprising global and local graph mining to identify attack patterns in cross-chain transactions. We conduct multiple experiments on the datasets with 203 attack transactions and 40,000 normal cross-chain transactions. The results show that BridgeGuard's reported recall score is 36.32% higher than that of state-of-the-art tools and can detect unknown attack transactions.

L. K. Bang, H. V. Khanh, M. N. Triet, N. N. Hung · 8 authors

No abstract is available for this record.

G.B. Bhavana, Aakanksha Bedi, R. S. Anand, J. Ramprabhakar · 5 authors

World’s population is rapidly expanding, and so is the need for an uninterrupted power supply. Along with this, there is also a rapid rise in tech-savvy initiatives and industrialization. All these lead to an increase in the carbon footprint, thereby resulting in an increasingly polluted world. Most governments, regardless of their politics, are pledging to reduce their carbon emissions and shift to greener energy resources. Integrating renewable energy (RE) into the current energy system is a key step in that direction, but the existing energy infrastructure is incapable of incorporating RE sources and catering to the rising demands without technological interventions. Electricity obtained through RE is very volatile and subject to environmental conditions. In such a scenario, the RE alone would not be able to support the grid at peak demand times. Grid would need additional support in the form of demand response (DR). DR incentivizes consumers to reduce their electricity usage during peak demand, but calculating the real-time data of all the consumers and rewarding them becomes a hassle without smart, secure, and reliable communication and storage systems. Hence, to enhance participant trust and automate the entire DR process, blockchain and smart contracts (SC) are viable solutions due to their transparency and immutability. This paper works on a SC-based DR programme to incentivize users based on their choices using an ethereum test network (testnet).

Emilio C. Piesciorovsky, Gary Hahn, Raymond Borges Hink, Aaron Werth

In modern electrical grids, the numbers of customer-owned distributed energy resources (DERs) have increased, and consequently, so have the numbers of points of common coupling (PCC) between the electrical grid and customer-owned DERs. The disruptive operation of and out-of-tolerance outputs from DERs, especially owned DERs, present a risk to power system operations. A common protective measure is to use relays located at the PCC to isolate poorly behaving or out-of-tolerance DERs from the grid. Ensuring the integrity of the data from these relays at the PCC is vital, and blockchain technology could enhance the security of modern electrical grids by providing an accurate means to translate operational constraints into actions/commands for relays. This study demonstrates an advanced power system application solution using distributed ledger technology (DLT) with smart contracts to manage the relay operation at the PCC. The smart contract defines the allowable total power factor (TPF) of the DER output, and the terms of the smart contract are implemented using DLT with a Cyber Grid Guard (CGG) system for a customer-owned DER (wind farm). This article presents flowcharts for the TPF smart contract implemented by the CGG using DLT. The test scenarios were implemented using a real-time simulator containing a CGG system and relay in-the-loop. The data collected from the CGG system were used to execute the TPF smart contract. The desired TPF limits on the grid-side were between +0.9 and +1.0, and the operation of the breakers in the electrical grid and DER sides was controlled by the relay consistent with the provisions of the smart contract. The events from the real-time simulator, CGG, and relay showed a successful implementation of the TPF smart contract with CGG using DLT, proving the efficacy of this approach in general for implementing electrical grid applications for utilities with connections to customer-owned DERs.

Jingjie Xu, Ting Wang, Mingqi Lv, Tieming Chen · 6 authors

Abstract Smart contracts have significant losses due to various types of vulnerabilities. However, traditional vulnerability detection methods rely extensively on expert rules, resulting in low detection accuracy and poor adaptability to novel attacks. To address these problems, in this paper, deep learning methods are combined with smart contract vulnerability code detection approaches. Abstract syntax trees (ASTs), which are special isomorphic graph structures, are an important bridge between source code and graph neural networks. By learning the AST, the model can understand the semantics of the source code. Moreover, graph neural networks have an increasing ability to address complex heterogeneous graphs. Therefore, control flow graphs are fused with data flow graphs on the basis of the ASTs to build heterogeneous graphs with richer code semantics. Furthermore, multigranularity analysis of the vulnerability detection results is performed, including coarse-grained contract-level vulnerability detection and fine-grained line-level vulnerability detection. Through this multigranularity detection approach, vulnerabilities in contracts can be identified and analysed more comprehensively, providing a richer perspective and more solutions for vulnerability detection. The experimental results show that the proposed multigranularity vulnerability detection method based on heterogeneous graphs (MVD-HG) improves both the accuracy and range of the detected vulnerability types in contract-level vulnerability detection tasks; moreover, in the line-level vulnerability detection task, the MVD-HG model achieves significant results and addresses the shortcomings of existing methods. In addition, based on code generation methods used in related fields, a data enhancement method based on the source code is developed, which effectively expands the experimental dataset to address the reduced credibility of the results due to insufficient amounts of data.