Blockchain Papers

Weiyi Liu, Xiaojuan Zhao, Wenjia Li, Ye Wang

No abstract is available for this record.

Farid Hamzeh Aghdam, Aleksandr Zavodovski, Mehdi Rasti, Éva Pongrácz

The energy domain worldwide is experiencing high transformative pressure due to the imperative of climate change and new opportunities brought by various rapidly evolving digital technologies. Particularly, this change is affecting smart grids (SGs), which are increasingly shifting toward utilizing renewable and distributed energy sources. The natural intermittency of these energy sources increases the complexity of SG operations, such as ensuring continuity of energy supply and demand response balancing. In mitigation of these challenges, the tools and complex approaches that digitalization can provide have shown themselves particularly advantageous. There is a solid body of work showing how technologies like the Internet of Things (IoT), distributed ledgers, edge and cloud computing, machine learning (ML), etc., can be applied to address a variety of technical and economic problems in the energy sector, emphasizing SGs. This paper presents the most comprehensive literature review to date on digitalization in renewable energy source-based SGs, synthesizing over 200 studies across data analytics, artificial intelligence and ML, digital twins, edge–fog–cloud computing, the IoT, advanced metering infrastructure, and distributed ledger technologies. Unlike previous reviews, which are often limited to a single technology or narrow application, this work provides a cross-technology synthesis linking technical and financial aspects, identifies consolidated research gaps, and proposes a unified research agenda. The review further highlights future trends, including large language models, 6G communications, and distributed autonomous organizations, and discusses their implications for both industry practice and academic research.

Gheyath Mustafa Zebari, Nasser Al Musalhi

ABSTRACT As digital transformation accelerates, the demand for secure, decentralized, and intelligent systems continues to rise across industries. Blockchain technology has emerged as a revolutionary tool for ensuring data integrity and transparency, while Artificial Intelligence (AI) offers unparalleled capabilities in enhancing decision‐making, automation, and security. This review explores the intersection of AI and blockchain, focusing on how AI techniques—including machine learning (ML), deep learning (DL), reinforcement learning (RL), and natural language processing (NLP)—can effectively mitigate security vulnerabilities within blockchain ecosystems. By analyzing over 100 peer‐reviewed studies and real‐world applications across finance, healthcare, supply chain management, and smart cities, this paper highlights the strengths and limitations of current AI‐driven solutions for addressing blockchain security challenges. Specifically, it examines AI's role in strengthening consensus mechanisms, detecting anomalies, identifying smart contract vulnerabilities, and preserving data privacy. Additionally, the review identifies emerging trends such as federated learning, quantum‐resistant cryptography, and decentralized AI models. The review concludes by discussing ethical considerations, regulatory challenges, and the necessity for standardized security frameworks to guide the future of AI‐enhanced blockchain security. Ultimately, this review offers actionable insights for building resilient, scalable, and AI‐driven blockchain systems, paving the way for innovation and enhanced security across industries.

Michael J. Diaz, Sai Batchu, Jasmine Tran, Arthur Samia · 5 authors

No abstract is available for this record.

Pedro Leale, Ivan da Silva Sendin

Este trabalho apresenta uma metodologia de detecção de contratos inteligentes do tipo mixers na rede Ethereum. Utilizou-se um modelo de aprendizado de máquina baseado em Random Forest, treinado com transações do Tornado Cash e balanceado com amostras de 100 endereços aleatórios não relacionados a mixers. O modelo foi treinado com dados de março de 2025 e validado em 29/10/2020, dia de alto volume de transações, identificando corretamente 3 endereços do Tornado Cash.

Mingwang Zhang, Liming Zhang, Tao Tan, Yang Zhao-jun · 5 authors

ABSTRACT With the rapid advancement of autonomous driving, the privacy and credibility of high‐definition (HD) maps, which serve as an essential foundation for driving safety, are receiving increasing attention. Traditional ciphertext‐domain digital watermarking technology encounters high computational overhead and risks of privacy leakage, making it challenging to balance data security, privacy protection, and trustworthiness verification. Against this background, a zero‐knowledge watermark (ZKW) algorithm based on compressed sensing is proposed. First, the high‐precision map data in OpenDrive format is dynamically encrypted using DNA‐based techniques to enhance data security and privacy. Secondly, to ensure the credibility of data verification, a zero‐knowledge watermark is generated using compressed sensing and embedded into the attribute values of ciphertext‐domain data as invisible characters. Experimental results demonstrate that the proposed ZKW scheme is commutative with the encryption scheme and can achieve zero‐knowledge proof (ZKP) in both ciphertext and plaintext domains. Furthermore, the scheme exhibits excellent robustness against various security threats, including geometric attacks, cropping attacks, and combined attacks.

Unknown author

Finance is being transformed by technology, data, and new societal values. This issue explores the rise of stablecoins, AI-driven credit, and public and private payment innovations—alongside the risks they pose to financial stability, regulation, and crime prevention.

Joseph Olusola, Quan Phung

The construction industry in developing countries continues to face significant challenges due to reliance on traditional, paper-based contract administration and management. This approach frequently results in inefficiencies, disputes, transparency issues and unethical practices. Although smart contracts enabled by blockchain technology present a promising solution to these longstanding issues, their adoption in developing countries remains limited. This study investigates the barriers to and strategies for the implementation of smart contracts within the construction industry, using Nigeria as a representative case. Adopting a qualitative research methodology, data were collected through semi-structured interviews with 14 experienced project managers selected via purposive sampling. A thematic analysis of the data identified several critical barriers, including resistance to change, low awareness, privacy concerns, legal uncertainties, technical hurdles, infrastructure deficits and economic instability. To overcome these barriers, the study proposes a strategic implementation framework informed by insights from interviewees and supported by literature. Key recommended strategies include educational and awareness initiatives, governmental support and policy reform, stakeholder collaboration, robust security measures, phased deployment and establishing supportive legal frameworks. The findings of this research offer valuable guidance for developing countries encountering similar constraints, providing a clear roadmap for successfully integrating smart contracts into construction practices.

Minwei Zhang

This paper examines the legal status of Decentralized Autonomous Organizations (DAOs) within Macau's legal framework, with particular emphasis on the potential analogical application of Article 174 of the Commercial Code. Despite the absence of specific provisions addressing these novel blockchain-based entities, this research demonstrates that Macau's existing legal infrastructure possesses sufficient flexibility to accommodate DAOs through interpretive mechanisms. By analyzing the theoretical foundations of legal personhood, the distinctive characteristics of DAOs, and the underlying principles of Macau's commercial law system, this study proposes a viable pathway for recognizing DAOs as legitimate legal entities. The research reveals that while Article 174 was not originally conceived to address blockchain-based organizations, its purposive interpretation and analogical application could provide a provisional legal foundation for DAOs, pending more specific legislative developments. This approach not only addresses immediate practical concerns regarding the legal status of DAOs but also contributes to the broader discourse on legal adaptation to technological innovation in the commercial sphere.

Damla Sarıçelik, Mohaned Chraiti, Albert Lévi, Özgür Erçetin

The Open Radio Access Network (O-RAN) paradigm fosters multi-vendor interoperability, allowing modules from different vendors to cooperatively handle network functions, such as temporary data processing or sensor data collection for network operations optimization. However, this integration agility introduces the risk of selecting suboptimal or adversarial modules, leading to moral hazard. Traditional Moral Hazard testing approaches typically rely on a benchmarking data set in addition to historical performance score. However, they deemed impractical, as vendor-supplied modules may not reveal their outputs before deployment, and the network may lack direct access to reference results for validation. This challenge is further compounded by the dynamic nature of network elements and AI-driven models, whose performance can degrade over time due to malicious tampering, obsolescence, or device deterioration, making historical quality assessments ineffective. In this paper, we address the challenge of identifying legitimate vendor-supplied modules among adversarial ones, with respect to a given network functionality/operation, in the absence of benchmarks. We propose a benchmark-free test framework that detects and eliminates adversarial modules using a methodology inspired by the WereWolf game, combined with zero-knowledge proof techniques. Monte Carlo simulations demonstrate that our approach effectively removes adversarial entities while preserving the privacy of legitimate modules.

Seyyed Reza Nakhli, Mahdi Alizade

Strengthening the economy through transformation in the tax system and decreasing the role of auditors and auditor-centric approaches should be among the priorities of the Iranian National Tax Administration.Given the country's urgent need to increase revenue sources to compensate for budget deficits, improving the tax collection system becomes even more crucial.According to clause (b) of article (1) of the "Law on Sales Terminals and Taxpayer Systems," blockchain technology can also be considered a type of sales terminal.One of the key features of blockchain is the enhancement of security, transparency, and efficiency.This study aimed to consider reality as closely as possible.For data collection, a library research method has been employed.It appears that a private consortium blockchain is a suitable option for the tax system.Based on the conducted reviews, there is still no definitive consensus mechanism for a tax system.Therefore, the proposed approach in this study is the use of a hybrid consensus mechanism, combining proof-of-authority and delegated proof-of-stake, which would be ideal for a blockchain-based tax system.One of the main features of this model is the use of multi-layered validation.A blockchain-based tax system designed to record all transactions and events related to invoice-based taxes should fundamentally be established on a multi-party smart contract between the buyer, seller, tax authorities of the origin and destination, the buyer's bank, and the seller's bank.To ensure the successful implementation of blockchain, several key considerations must be taken into account.

Ria Astriratma

Blockchain smart contracts are pivotal to decentralized applications, yet their security remains a critical challenge. This study analyzes a dataset of 1,000 smart contracts to investigate known vulnerabilities, audit practices, and exploit patterns. The results reveal that audited contracts are significantly less prone to exploitation, with 75% exhibiting no exploit history compared to 55% of non-audited contracts. "Integer Overflow" and "Unchecked Call" were identified as the most prevalent vulnerabilities, contributing to 60% and 50% exploit rates, respectively. The study highlights the importance of transparent audit reporting, as contracts without available reports were exploited in 35% of cases. Additionally, hidden vulnerabilities in ostensibly secure contracts underscore the evolving sophistication of blockchain threats. This research emphasizes the need for robust security practices, including stricter coding standards, comprehensive audits, and advanced vulnerability detection techniques such as formal verification and machine learning. Future works aim to integrate security tools into development workflows and foster industry-wide collaboration to standardize auditing practices, thereby enhancing the security and trustworthiness of blockchain ecosystems.

Balakrishnan Subramanian, Leelavathy Sivakumar, Sumathi Duraisamy, Simonthomas Sagayaraj · 6 authors

Purpose: The framework of the Autonomous Vehicles (AVs) is facilitated by modern communication systems. In Real-Time (RT), the data is communicated to one another, and it is encouraged by AV. This AV also communicates with organizations stationed along the roadway, and navigates without human intervention. The dynamic and decentralized communication between vehicles and Roadside Units (RSUs) is integrated in Vehicular Ad Hoc Networks (VANETs). Then, there is no centralized structure for utilization in VANET. This distributed system faces difficulties in 2 areas: Authentication and security. The susceptibility to the network is increased by the unpredictable and risky features of AV, because there is currently no robust authentication system in place for multi-broadcast situations. Hence, the network is susceptible to security breaches, illegal access, data tampering, and service interruptions. During Handover Authentication (HA) between RSUs, critical security vulnerabilities are introduced by AV communication in ad-hoc networks, because of their dynamic topology and mobility patterns.Methodology: To address these issues, this study proposes a HA system for ad hoc AVs that uses blockchain technology. Using distributed controllers and Zero Knowledge Proofs (ZKPs), the proposed methodology enables rapid and safe authentication of AVs during handover between RSUs. To optimize authentication, decentralized Smart Network Controllers (SNCs) were used by the suggested method. This suggested method also eliminates the dependency on centralized entities and mitigates Single Point of Failure (SPoF) vulnerabilities.Findings: A private Blockchain network implementation makes the system transparent and immutable while providing tamper-proof storage for vehicle data. Simulation results demonstrate that the protocol achieves a 30.4% reduction in authentication latency, 27.8% lower packet loss rate, and a 23.5% improvement in throughput compared to EMT and GMT baseline protocols. Additionally, the system sustains a 95.2% success rate in mutual authentication under high vehicle density and maintains security integrity against impersonation, Sybil, and replay attacks.Originality/Value: The suggested protocol also mitigates SPoF risk of centralized systems and offers smooth Vehicle-to-Everything (V2X) services without charging any transaction fee. This method provides strong and scalable security for the communication of AVs in smart city systems.

Anurag Shrivastava, RVS Praveen, Raed H. C. Alfilh, Navdeep Singh · 6 authors

The rapid integration of blockchain technology into smart city infrastructure presents both transformative opportunities and environmental challenges. While blockchain enhances transparency, security, and decentralization, its conventional consensus mechanisms-particularly Proof of Work (PoW)-are energy-intensive and environmentally unsustainable. As cities worldwide move towards carbon neutrality, there is an urgent need for energy-efficient and environmentally aligned blockchain systems. This paper introduces a novel Green Consensus Mechanism (GCM) tailored for smart cities that optimizes energy use, reduces carbon emissions, and leverages renewable energy sources. Drawing on interdisciplinary insights from environmental science, distributed computing, and urban planning, the proposed GCM aligns blockchain operations with sustainability goals. Through simulations and comparative analysis against existing mechanisms such as Proof of Stake (PoS), Proof of Authority (PoA), and Delegated Proof of Stake (DPoS), this study demonstrates significant gains in energy efficiency and operational scalability. The results indicate that GCM can serve as a foundational layer for building carbonneutral smart cities while ensuring secure and decentralized digital governance.

Shasha Yu, Yanan Qiao, Fan Yang, Wenjia Zhao · 5 authors

The proof-of-stake (PoS) mechanism is a consensus protocol within blockchain technology that determines the validation of transactions and the minting of new blocks based on the participant's stake in the cryptocurrency network. In contrast to proof-of-work (PoW), which relies on computational power to validate transactions, PoS employs a deterministic and resource-efficient approach to elect validators. Whereas, an inherent risk of PoS is the potential for centralization among a small cohort of network participants possessing substantial stakes, jeopardizing system decentralization and posing security threats. To mitigate centralization issues within PoS, this study introduces an incentive-aligned mechanism named decentralized proof-of-stake (DePoS), wherein the second-largest stakeholder is chosen as the final validator with a higher probability. Integrated with the verifiable random function (VRF), DePoS rewards the largest stake-holder with uncertainty, thus disincentivizing stakeholders from accumulating the largest stake. Additionally, a dynamic evolutionary game model is innovatively developed to simulate the evolution of staking pools, thus facilitating the investigation of staking pool selection dynamics and equilibrium stability across PoS and DePoS systems. The findings demonstrate that DePoS generally fosters wealth decentralization by discouraging the accumulation of significant cryptocurrency holdings. Through theoretical analysis of stakeholder predilection in staking pool selection and the simulation of the evolutionary tendency in pool scale, this research demonstrates the comparative advantage in decentralization offered by DePoS over the conventional PoS.

Yunus Kareem, Djamel Djenouri, Essam Ghadafi

Blockchain is expected to play a key role in securing next generation communication systems, i.e., B5G and 6G, which will be highly decentralised, with high integration of edge computing, device-to-device (D2D) communications, and notably IoT networks. This paper addresses a fundamental bottleneck of blockchain; the simulation of consensus algorithms. State-of-the-art blockchain consensus algorithm simulators are built on general data that do not consider resource-constrained devices. These simulators have limitations in performance measurement (energy, latency, and throughput) and testing of security attacks, including DoS, Sybil, and 34% or 51% attacks). This paper introduces a blockchain Internet of Things consensus algorithm (BICA) simulator, which offers a framework for testing consensus algorithms with adaptable IoT data in various attack scenarios. It evaluates metrics such as latency, throughput, and attack resilience, providing insights into their capabilities under diverse network conditions. A case study involving Proof of Stake (PoS), Delegated Proof of Stake (DPoS), Proof of Elapse Time (PoET), Proof of Authority (PoA) and Practical Byzantine Fault Tolerance (PBFT) showed PBFT’s superior performance and security against vulnerabilities such as Sybil, DoS, and 34-51% attacks. BICA’s block-creation speed surpasses that of the existing simulators.

Ibraheem M. Alharbi, Najah Kalifah Almazmomi

No abstract is available for this record.

Adi Suryaputra Paramitha

Gas fees play a crucial role in Ethereum blockchain transactions, directly affecting the cost and efficiency of decentralized applications. This study analyzes gas fee patterns across transaction types, temporal trends, and anomalous behaviors using a dataset of 1,000 Ethereum transactions. The results reveal that the average gas price was 120.5 Gwei, with a standard deviation of 45.2 Gwei, highlighting significant variability. Smart contract functions exhibited varying gas usage, with mint operations consuming the highest average gas (1,500,000 units) compared to approve (1,200,000 units) and transfer (800,000 units). A positive correlation (r = 0.65) was observed between gas price and value transferred, suggesting that higher-value transactions often incur elevated gas fees. Temporal analysis showed predictable patterns, with peak gas prices occurring between 13:00 - 17:00 UTC during high network activity and lower prices between 02:00 - 06:00 UTC. Additionally, anomaly detection identified 15 outlier transactions, including one with an unusually high gas price of 500 Gwei, reflecting network congestion or prioritization strategies. These findings provide actionable insights for optimizing transaction costs and improving smart contract efficiency. Future research could explore layer-2 scaling solutions, alternative fee mechanisms, and machine learning approaches for gas price prediction. This study contributes to a deeper understanding of Ethereum’s gas fee dynamics, offering valuable guidance for developers, users, and researchers in the blockchain ecosystem.

Quentin Botha, Laurent Bindschaedler, Christoph Siebenbrunner

Decentralized mathematics prediction markets promise new forms of collaboration and incentive alignment, but traditional requirements engineering methods fail to address the unique governance, incentive, and security challenges of such Web3 systems. This paper demonstrates how they can be addressed through a requirements-driven design of a decentralized prediction market for mathematical conjectures, and proposes concrete enhancements to existing frameworks. Our work delivers actionable guidelines for engineering secure, incentive-aligned decentralized platforms, and sets a new standard for early-stage RE in the Web3 era.

Ethan Hadar

The integration of distributed digital twins (DTs) within an industrial metaverse presents a significant challenge to system stability and predictability. Continuous, asynchronous updates to individual DTs and their underlying generative AI foundation models create dynamic interdependencies that traditional, centralized requirements management systems cannot adequately govern due to inherent issues of trust, transparency, and data integrity. This paper argues for a paradigm shift, proposing a decentralized, multi-party requirements management framework built on Web3 distributed ledger technology. In this approach, requirements are transformed from static documents into immutable, traceable transactions on a shared ledger, with their validation and enforcement automated through smart contracts. The proposed system establishes a single, verifiable source of truth, enabling the use of automated guardrails and negotiated adjustments to contain the impact of changes. This ensures that the complex mesh of DTs can co-evolve in a stable, predictable, and secure manner, addressing key barriers and fostering the adoption of a collaborative industrial metaverse, as illustrated through a practical semiconductor manufacturing use case.

Suraphan Chantanasut

This study investigates the relationship between gas consumption and value transferred in Ethereum smart contracts, offering insights into resource utilization and efficiency within the blockchain ecosystem. Analyzing a dataset of 1,000 smart contracts, a moderate positive correlation r=0.45,p<0.05 was observed, indicating that higher gas consumption generally corresponds to larger financial transactions. The average gas consumption per contract was found to be 58,451,329.47 units, with a standard deviation of 20,123,456.89, highlighting significant variability in computational resource usage. Similarly, the average value transferred was 7,851.47 ETH, ranging from 0.001 ETH to over 100,000 ETH, showcasing the diverse financial applications of smart contracts. Efficiency analysis, measured as the ratio of value transferred to gas consumed, revealed an average efficiency of 0.00013 ETH per unit of gas, with some contracts achieving up to 0.01 ETH per unit of gas and others as low as 0.000007 ETH per unit of gas, reflecting varying levels of optimization. Outliers with disproportionately high gas consumption relative to value transferred were identified, suggesting inefficiencies or unique use cases. These findings underscore the importance of optimizing smart contract design to minimize gas costs and improve performance. Future research directions include functionality-specific analyses, anomaly detection, comparative studies across blockchain platforms, and exploring the economic implications of gas consumption. This work provides actionable insights for developers, researchers, and policymakers aiming to enhance the efficiency and sustainability of decentralized systems.

Gao Haodic

Ethereum's transition from a Proof-of-Work (PoW) to a Proof-of-Stake (PoS) consensus mechanism has significantly altered the network’s block generation process and transaction efficiency. This study investigates the impact of stake-based block generation on Ethereum’s transaction fees, block density, and overall network performance by analyzing a dataset containing 303 records of Ethereum blockchain activity. The findings reveal a strong positive correlation between block generation rate and stake reward (r = 0.78, p < 0.01) and coin stake (r = 0.74, p < 0.01), indicating that validators with larger stakes generate blocks more frequently. Additionally, transaction fees positively correlate with block density (r = 0.65, p < 0.01), suggesting that network congestion remains a key determinant of transaction costs, despite the PoS transition. Further analysis shows that Ethereum’s PoS system optimizes block space utilization, with an observed mean block density of 1393.6% and a transaction fee standard deviation of 0.12 ETH, demonstrating a more stable fee structure than PoW. The average transaction fee recorded is 0.179 ETH, with a maximum observed fee of 0.98 ETH and a minimum of 0 ETH in some cases. While PoS provides greater fee stability, minor fluctuations in fees persist due to congestion-related effects. Additionally, the mean stake reward is 0.98, suggesting a relatively stable staking incentive structure across different blocks.

Ziyi Xiong, Rong Liu, Hemang Subramanian

No abstract is available for this record.

Lené Tourn

No abstract is available for this record.