Blockchain Papers

Rim Ben Fekih, Mariam Lahami, Salma Bradai, Mohamed Jmaïel

No abstract is available for this record.

Mishall Al-Zubaidie, Tuqa Ghani Tregi

The rapid advancement of quantum computing poses significant challenges to conventional cryptography, necessitating the adoption of post-quantum cryptography (PQC) solutions. This chapter proposes a Post-Quantum Lattice Security (PQLS) system for protecting power plant data in smart cities. It integrates Kyber for secure key exchange, Falcon for quantum-resistant digital signatures, ZKP for efficient authentication without revealing sensitive data, and JSON-LD for standardizing the format of data received from different smart meters. To evaluate the security of the proposed framework, we analyze its resistance to various threats, such as side-channel and message recovery attacks. We measured key performance indicators. The results showed an average CPU utilization of 2.4592 MS, memory consumption averaging 1843.899 KB, an execution time of 2.45 MS, and a level averaging 66.27677. This demonstrates that our proposed system offers high security and efficiency, making it a practical solution for protecting electrical infrastructure in smart cities in the quantum era.

Yenlik Begimbayeva, Temirlan Zhaxalykov, Amir Akhtanov, Ruslan Pashkevich · 6 authors

This research focuses on enhancing the security of decentralized quantum key distribution (QKD) networks, where the absence of a central authority creates significant challenges such as malicious node infiltration, undetected key leakage, and unauthorized re-entry of revoked participants. Traditional authentication and trust models are insufficient for fully distributed QKD topologies, which remain highly vulnerable to insider threats and persistent compromise. To address these risks, let’s propose a layered security framework composed of three integrated components: Challenge-Response Authentication (CRA), Dynamic Trust Scoring (DTS), and Blockchain-Based Access Control (BBAC). CRA verifies node legitimacy through randomized quantum-state interactions, significantly reducing impersonation and quantum replay attacks. DTS implements real-time trust evaluation using anomaly detection to dynamically downgrade compromised nodes based on their behavioral deviations. BBAC maintains an immutable and tamper-proof trust ledger to block revoked nodes from re-entering under falsified identities and resists Sybil attacks using post-quantum cryptographic primitives. Simulation results confirm that the system improves detection rates of covert threats, ensures authentication latency under 10 ms, and reduces re-entry success to zero. The proposed architecture ensures long-term scalability and resilience, making it applicable to critical domains such as finance, national infrastructure, and military communication. This work contributes a novel, verifiable, and scalable solution to one of the most pressing open problems in distributed quantum networks

Liao, Guofu, Taotao Wang, Shengli Zhang, Jiqun Zhang · 6 authors

Fine-tuning large language models (LLMs) is crucial for adapting them to specific tasks, yet it remains computationally demanding and raises concerns about correctness and privacy, particularly in untrusted environments. Although parameter-efficient methods like Low-Rank Adaptation (LoRA) significantly reduce resource requirements, ensuring the security and verifiability of fine-tuning under zero-knowledge constraints remains an unresolved challenge. To address this, we introduce VeriLoRA, the first framework to integrate LoRA fine-tuning with zero-knowledge proofs (ZKPs), achieving provable security and correctness. VeriLoRA employs advanced cryptographic techniques -- such as lookup arguments, sumcheck protocols, and polynomial commitments -- to verify both arithmetic and non-arithmetic operations in Transformer-based architectures. The framework provides end-to-end verifiability for forward propagation, backward propagation, and parameter updates during LoRA fine-tuning, while safeguarding the privacy of model parameters and training data. Leveraging GPU-based implementations, VeriLoRA demonstrates practicality and efficiency through experimental validation on open-source LLMs like LLaMA, scaling up to 13 billion parameters. By combining parameter-efficient fine-tuning with ZKPs, VeriLoRA bridges a critical gap, enabling secure and trustworthy deployment of LLMs in sensitive or untrusted environments.

Yini Huang, Beishui Liao, Xingchi Su

No abstract is available for this record.

Dhawan Singh, Aditi Thakur

Security protection of dynamically generated log files requires immediate prevention against alteration, reliability, and compliance of current systems. The research creates a novel framework that integrates blockchain technology with cryptographic hashing methods to establish resistant and immutable log authentication mechanisms. The system dynamically generates log files through Python while saving a cryptographic hash (SHA-256) for verification of file integrity. Security and authentication of these hashes occurs through an Ethereum blockchain smart contract named Sepolia testnet. The framework uses Remix IDE along with Web3.py through Infura to connect into the Ethereum Sepolia testnet for launching smart contracts development. Simulation results demonstrated the system effectiveness by showcasing how logs remain immutable while providing performance data including transaction processing time and gas usage and event output. The research demonstrates how blockchain technology can power real-time log verification systems and suggests foundations for future decentralized security system developments.

Andrada Cristina Artenie, Diana Laura Silaghi, Daniela Elena Popescu

Blockchain technologies, despite their profound transformative potential across multiple industries, continue to face significant scalability challenges. These limitations are primarily observed in restricted transaction throughput and elevated latency, which hinder the ability of blockchain networks to support widespread adoption and high-volume applications. To address these issues, research has predominantly focused on Layer 1 solutions that seek to improve blockchain performance through fundamental modifications to the core protocol and architectural design. Alternatively, Layer 2 solutions enable off-chain transaction processing, increasing throughput and reducing costs while maintaining the security of the base layer. Despite their advantages, Layer 2 approaches are less explored in the literature. To address this gap, this review conducts an in-depth analysis on Ethereum Layer 2 frameworks, emphasizing their integration with machine-learning techniques, with the goal of promoting the prevailing best practices and emerging applications; this review also identifies key technical and operational challenges hindering widespread adoption.

Narges Dadkhah, Somayeh Mohammadi, Gerhard Wunder

Determining the optimal block size is crucial for achieving high throughput in blockchain systems. Many studies have focused on tuning various components, such as databases, network bandwidth, and consensus mechanisms. However, the impact of block size on system performance remains a topic of debate, often resulting in divergent views and even leading to new forks in blockchain networks. This research proposes a mathematical model to maximize performance by determining the ideal block size for Hyperledger Fabric, a prominent consortium blockchain. By leveraging machine learning and solving the model with a genetic algorithm, the proposed approach assesses how factors such as block size, transaction size, and network capacity influence the block processing time. The integration of an optimization solver enables precise adjustments to block size configuration before deployment, ensuring improved performance from the outset. This systematic approach aims to balance block processing efficiency, network latency, and system throughput, offering a robust solution to improve blockchain performance across diverse business contexts.

Herbert Jordan, Kamil Jezek, Pavle Subotic, Bernhard Scholz

Operating nodes in an L1 blockchain remains costly despite recent advances in blockchain technology. One of the most resource-intensive components of a node is the blockchain database, also known as StateDB, that manages balances, nonce, code, and the persistent storage of accounts/smart contracts. Although the blockchain industry has transitioned from forking to forkless chains due to improved consensus protocols, forkless blockchains still rely on legacy forking databases that are suboptimal for their purposes. In this paper, we propose a forkless blockchain database, showing a 100x improvement in storage and a 10x improvement in throughput compared to the geth-based Fantom Blockchain client.

Botao Amber Hu, Fangting

"Composable Life" is a hybrid project blending design fiction, experiential virtual reality, and scientific research. Through a multi-perspective, cross-media approach to speculative design, it reshapes our understanding of the digital future from AI's perspective. The project explores the hypothetical first suicide of an on-chain artificial life, examining the complex symbiotic relationship between humans, AI, and blockchain technology.

Dan Lin, Shunfeng Lu, Ziyan Liu, Jiajing Wu · 8 authors

Cross-chain bridges play a vital role in enabling blockchain interoperability. However, due to the inherent design flaws and the enormous value they hold, they have become prime targets for hacker attacks. Existing detection methods show progress yet remain limited, as they mainly address single-chain behaviors and fail to capture cross-chain semantics. To address this gap, we leverage heterogeneous graph attention networks, which are well-suited for modeling multi-typed entities and relations, to capture the complex execution semantics of cross-chain behaviors. We propose BridgeShield, a detection framework that jointly models the source chain, off-chain coordination, and destination chain within a unified heterogeneous graph representation. BridgeShield incorporates intra-meta-path attention to learn fine-grained dependencies within cross-chain paths and inter-meta-path attention to highlight discriminative cross-chain patterns, thereby enabling precise identification of attack behaviors. Extensive experiments on 51 real-world cross-chain attack events demonstrate that BridgeShield achieves an average F1-score of 92.58%, representing a 24.39% improvement over state-of-the-art baselines. These results validate the effectiveness of BridgeShield as a practical solution for securing cross-chain bridges and enhancing the resilience of multi-chain ecosystems.

Rayhan Ferdous Srejon, M. Fahim, Sk. Md. Shadman Ifaz, Md. Kamrul Hasan · 6 authors

Ride-sharing platforms have revolutionized urban mobility, offering millions of users convenient and costeffective transportation. However, mainstream centralized platforms such as Uber and Lyft continue to face pressing concerns including data privacy breaches, high service charges, security vulnerabilities, and a lack of transparency due to centralized control. To address these limitations, this research proposes a semipublic blockchain-based ride-sharing platform integrating Hyperledger Fabric for secure and permissioned data management with Ethereum smart contracts for transparent ride booking, fare calculation, and payments. The platform leverages the InterPlanetary File System (IPFS) for immutable, decentralized storage and uses the Cosmos SDK to enable seamless interoperability between public and private blockchains. A user-centric pay-as-you-drive model is introduced to ensure fair and distance-based billing. Preliminary evaluations show that our system outperforms traditional blockchain consensus methods (PoW, PoA) in throughput, latency, and resource usage. At the same time, it remains economically viable with an operational cost of under 33,000 BDT per node. Future improvements include benchmarking with Hyperledger Caliper, transitioning from Vagrant to Docker for better scalability, and implementing backend services using Node.js or Golang with MongoDB for efficient metadata handling. Together, these enhancements support a secure, decentralized, and scalable alternative to existing ride-sharing systems.

Xuling Ye, Lili Liu, Markus König

Blockchain (BC) and smart contract (SC), known for their decentralized and secure frameworks, have been successfully applied across industries to enhance security, efficiency, and transparency in technical and engineering aspects such as automated transactions, data management, and supply chain monitoring. In recent years, the construction industry has seen significant advancements in adopting BC and SC. This review paper examines the latest BC and SC prototypes, case studies, and technical applications published over the past four years, focusing on how these academic developments can be transitioned into industry practice. By categorizing the collected studies using Technology Readiness Levels (TRLs) and conducting an in-depth analysis, the paper seeks to identify strategies for accelerating the adoption of these technologies in the construction sector. Reviewing recent advancements, this paper uncovers key trends, benefits, and challenges associated with implementing BC and SC in construction. The findings suggest that these technologies can significantly enhance project efficiency, contract management, and supply chain transparency while fostering trust among stakeholders. While these technologies offer significant potential, critical challenges, including scalability, privacy, and integration complexities, hinder their widespread adoption. Moreover, specific limitations, such as the difficulty in establishing regulatory compliance and technical barriers in data management, remain unresolved. By providing actionable insights and highlighting pathways to bridge the adoption gaps, the paper aims to accelerate the integration of BC and SC into the construction industry, driving innovation, transparency, and operational efficiency.

Silvia Meschini, Daniele Accardo, Lavinia Chiara Tagliabue, Stefano Rinaldi · 7 authors

The integration of blockchain and smart contracts in the construction industry has the potential to revolutionize the tender phase and enhance waste management practices. The prototype is designed to enhance transparency, efficiency, and trustworthiness in Italian public procurement. To analyze the national public procurement database with a view to identifying common issues, which are often related to the lack of trust among stakeholders, Large Language Models (LLMs) are exploited. Blockchain technology has the potential to facilitate this process by eliminating discrepancies and disputes, providing a decentralized, immutable ledger to notarize data related to digital models submitted during the tender phase, thereby ensuring transparency and tamper-proof data. The automation of bid evaluations based on predefined criteria such as those pertaining to waste management, is a key feature of smart contracts, which are of particular importance in the context of construction sustainability. Such assessments are enabled, allowing for unbiased and transparent evaluations based on quantifiable data, with the results recorded automatically on the blockchain. This results in a more efficient tender process and the promotion of sustainable practices, as projects with superior waste management are given priority. A tailor-made blockchain protocol is put forth to delineate requirements and facilitate data exchanges. It establishes standards and procedures for data submission, verification, and evaluation, ensuring secure and transparent interactions and enhancing stakeholder confidence in a fair and transparent evaluation process. In summary, the use of blockchain and smart contracts in the construction tender phase improves data integrity, transparency, and efficiency. The focus on waste management indicators allows for objective project evaluations and the promotion of sustainable practices. This innovative approach has the potential to transform public procurement, establishing a new global standard for the construction industry.

Yinshi Li, Wenqiang Gu

Effective data governance is crucial in modern digital ecosystems, ensuring secure, transparent, and efficient data sharing. Traditional centralized governance models often suffer from trust issues, inefficiencies, and security vulnerabilities. Blockchain technology offers a decentralized and tamper-resistant solution to address these challenges. This paper proposes a blockchain-based data governance architecture that enhances data sharing mechanisms and optimizes smart contract execution. The framework leverages a permissioned blockchain to ensure controlled data access while maintaining data integrity and security. To further improve performance, an optimized smart contract mechanism is introduced using gas-efficient transaction designs and layer-2 scaling solutions. Experimental evaluations demonstrate that the proposed model improves transaction efficiency, reduces computational overhead, and enhances security compared to conventional blockchain-based governance systems. The results highlight the potential of blockchain in establishing a decentralized, efficient, and transparent data governance framework for secure and scalable data exchange.

Richa Golash, Ankush Goyal, Ram Kishan Dewangan

Blockchain technology(BCT) offers transformative opportunities, particularly in cross-border trade finance ($T_{F}$) and securities settlement in capital markets. Conventional capital markets face challenges such as high operational costs, lengthy settlement times, and susceptibility to fraud. This paper explores how the decentralized ledger and smart contract system of BCT can address these challenges. By examining key technological components such as consensus mechanisms, network design, and transaction validation methods, this study highlights blockchain's potential to streamline processes, reduce intermediaries, and ensure immutable record-keeping. The research also examines the impact of blockchain in securities settlement, focusing on atomic settlement models that eliminate counter-party risks and enhance liquidity management. Through a comprehensive analysis of use cases and implementation strategies, this research underscores blockchain's role in revolutionizing capital markets. The findings suggest that blockchain adoption can drive significant improvements in cross-border transactions, fostering a more resilient and efficient financial ecosystem. Future research directions include exploring interoperability challenges and regulatory considerations for broader adoption.

Reynald Dian Kristiawan, Ridwan Sanjaya, T. Brenda Chandrawati

Crowdfunding is now a significant source of financing in the form of small sums of money from many individuals through internet websites. It is a significant source of backup for raising finance, especially for student research work, because it is a quicker and more convenient way to raise capital. Traditional crowdfunding websites are beset with issues regarding security threats in the form of fund misuse, manipulation, and data intrusion, detracting from trustworthiness and performance. This article recommends the use of blockchain technology as a solution to these issues. Blockchain's immutability, transparency, and decentralization ensure secure transactions and solve data integrity concerns. The principal elements of blockchain, including immutability, transparency, security, and smart contracts, are mentioned, demonstrating their role in enhancing crowdfunding for student research.

Badie Uddin

This paper presents a comprehensive literature review on the application of blockchain technology in ensuring data integrity and security within decentralized applications (dApps). Blockchain, with its inherent features such as immutability, decentralization, and transparency, offers a robust framework for safeguarding data across various sectors, including finance, healthcare, and supply chain management. Through an extensive qualitative analysis of existing studies, this research explores how cryptographic techniques, consensus mechanisms, and blockchain's distributed nature contribute to securing data in decentralized environments. The review examines key findings from the literature, including the integration of advanced cryptographic methods such as zero-knowledge proofs and homomorphic encryption, which enhance data privacy while maintaining integrity. Furthermore, the study discusses the challenges of scalability, energy consumption, and off-chain data security in blockchain-based systems, identifying areas for future research. The review also highlights the importance of hybrid blockchain models and scalable consensus algorithms in addressing the limitations of current blockchain frameworks. Overall, this paper contributes to the growing body of knowledge on blockchain-based data security and integrity in decentralized applications and offers recommendations for further research to enhance the scalability, efficiency, and environmental sustainability of blockchain systems.

Iryna Dashko, Олександр Череп, Любомир Михайліченко

The article comprehensively examines cryptocurrencies as a strategic tool for transforming the investment environment in the context of digitalization of the global economy. The current state of the crypto market is analyzed, key trends in its evolution are identified, and the role of digital assets in the formation of new investment models is characterized. Particular attention is paid to determining the investment potential of cryptocurrencies in the long term, taking into account such advantages as decentralization, market openness, technological innovation and accessibility. The author substantiates the concept of “crypto-horizon” - a new investment paradigm that combines a strategic vision of digital finance development with an understanding of the risks and prospects of cryptocurrencies. The author considers the importance of this concept in the formation of a new type of investor capable of operating in the digital economy, effectively managing risks and using innovative financial instruments. The paper also focuses on the key challenges of the crypto market: high volatility, legal uncertainty, information asymmetry, and limited financial literacy. The SWOT analysis made it possible to identify the strengths and weaknesses of crypto investing, as well as promising areas for the development of digital finance. The importance of state regulation, creation of a regulatory framework, development of digital finance infrastructure and raising public awareness in the field of investment is determined. The author emphasizes the need to form an effective regulatory framework for the integration of cryptocurrencies into the financial system. The role of public policy, educational initiatives, and infrastructure solutions in increasing confidence in digital assets is shown. It is substantiated that successful implementation of the “crypto-horizon” concept is possible only if there is a synergy of technology, regulation and investment culture. As a result, the authors conclude that cryptocurrencies are already playing the role of a digital key to the investment future, and their competent integration into national and international financial systems will be the key to the formation of an innovative, flexible and accessible investment ecosystem for the general population.

Ezra Natanael, Ridwan Sanjaya, Erdhi Widyarto Nugroho

This research presents a decentralized platform for academic credential verification using blockchain technology. The system allows students to store and share their school diplomas in a secure, tamper-evident format. By leveraging smart contracts, diploma issuance and verification are automated, enabling educational qualifications to be independently verified without manual intervention. The proposed system significantly reduces verification time, requiring only 400 milliseconds for an individual diploma and less than 2 seconds for a complete document. These performance metrics demonstrate the system's efficiency in real-world use. Employers can validate job applicants' credentials directly through the blockchain, reducing administrative workload and improving trust in academic records. The solution benefits students, educational institutions, and employers alike by ensuring the authenticity and integrity of issued diplomas through a decentralized and transparent infrastructure.

Ziwei Li, Jiajing Wu, Zhiying Wu, D. Tan · 9 authors

Smart contracts are self-executing computer programs on blockchains. With the development of blockchain technology, the number of smart contracts has grown rapidly, as has the concern for their security. Regrettably, inconsistencies between the logic implemented in the code and the intentions described in the comments, known as Code–Comment Inconsistencies (CCI), are frequently present in some smart contracts. These inconsistencies can mislead readers in understanding the contract code and, in severe cases, may lead to vulnerabilities and economic losses. Existing learning-based methods are not tailored for smart contract languages, overlook the issue of insufficient context information caused by comment references and nested intentions, and rely on large-scale labeled data; whereas rule-based methods struggle to accommodate the flexibility with which developers express intentions, often resulting in false positives. To tackle the challenges posed by insufficient context information and the scarcity of labeled data, we introduce CCIHunter, a tool designed to detect CCIs in smart contracts. CCIHunter addresses the issue of insufficient context information during data modeling and incorporates a two-stage pre-training process that does not depend on labeled data to enhance its detection capabilities. Specifically, CCIHunter enhances comments based on templates and models code as a heterogeneous graph based on function calls. It utilizes CodeBERT and UniMp to generate embeddings for comments and code, respectively, and then calculates the similarity between these two embeddings. Consistency is judged by combining code embeddings, comment embeddings, and similarity scores. Notably, CCIHunter undergoes a two-stage pre-training that includes contrastive learning and mutation analysis, aiming to improve its ability to bridge the gap between code and comments and to focus on code elements at different granularities. Experimental results demonstrate that CCIHunter achieves a precision of 0.95, a recall of 0.90, and an F1 score of 0.93, outperforming existing tools.

Junsouk Choi, Robert S. Chapkin, Yang Ni

Observational zero-inflated count data arise in a wide range of areas such as genomics. One of the common research questions is to identify causal relationships by learning the structure of a sparse directed acyclic graph (DAG). While structure learning of DAGs has been an active research area, existing methods do not adequately account for excessive zeros and therefore are not suitable for modeling zero-inflated count data. Moreover, it is often interesting to study differences in the causal networks for data collected from two experimental groups (control vs treatment). To explicitly account for zero-inflation and identify differential causal networks, we propose a novel Bayesian differential zero-inflated negative binomial DAG (DAG0) model. We prove that the causal relationships under the proposed DAG0 are fully identifiable from purely observational, cross-sectional data, using a general proof technique that is applicable beyond the proposed model. Bayesian inference based on parallel-tempered Markov chain Monte Carlo is developed to efficiently explore the multi-modal posterior landscape. We demonstrate the utility of the proposed DAG0 by comparing it with state-of-the-art alternative methods through extensive simulations. An application in a single-cell RNA-sequencing dataset generated under two experimental groups finds some interesting results that appear to be consistent with existing knowledge. A user-friendly R package that implements DAG0 is available at https://github.com/junsoukchoi/BayesDAG0.git.

Gabriele Fredduzzi, Baruch Manigrasso, Nerminko Omanic

The sustainable and efficient management of the built environment is a crucial challenge in the increasingly digitalized AEC sector. Innovative technologies such as Building Information Modeling (BIM) and Digital Twin (DT) offer significant opportunities to enhance the operational efficiency and sustainability of physical assets. However, digitalization generates vast amounts of Big Data, and their handling through centralized architectures leads to risks of fragmentation, lack of transparency, and vulnerability to manipulation. In response to these challenges, this study presents an innovative Proof of Concept (PoC) that integrates Blockchain (BT), Digital Twin (DT), and Non-Fungible Token (NFT) technologies to promote decentralized and sustainable data management in the construction industry. The application, called dDT (decentralized Digital Twin), was initially deployed on the Solana blockchain and later integrated with Polygon to leverage EVM compatibility and the ERC-721 standard for NFTs. The platform enables the tokenization of data flows generated by physical assets, ensuring traceability, security, and transparency throughout the entire asset lifecycle. The dDT system represents a sustainable innovation as it creates a secondary data market, fostering collaboration among industry stakeholders and financing new developments through the sale of data-linked NFTs. This decentralized solution addresses fragmentation and transparency issues, promoting more secure, resilient, and sustainable data management practices. The PoC demonstrates how the integration of BT, DT, and NFT can accelerate the transition toward more efficient and innovative practices, with positive impacts on sustainability and technological advancement in the AEC sector.

SK. Mahboob Basha, Brijesh Kumar, Praveen Anand, Kaspa Tejashwini

The traditional cheque clearance systems face several challenges, including processing delays, high operational costs, and a lack of transparency—often resulting in inefficiencies and increased risk of fraud. To address these issues, a Blockchain-Based Cheque Clearance System Using Ethereum is proposed, aiming to revolutionize the banking sector by providing a secure, transparent, and efficient mechanism for cheque transactions between banks and users. This system leverages Ethereum’s decentralized blockchain network and smart contracts to automate the cheque clearance process, ensuring faster and tamper-proof transactions. Historically, cheque clearance relied on manual or centralized procedures that were prone to errors and fraudulent activities. Traditional methods often required inter-bank coordination, causing delays and inconsistencies. Although some digitized systems were introduced over time, they remained centralized and lacked the trust and security required for critical financial operations. Inspired by the capabilities of blockchain technology, this project seeks to overcome these limitations by decentralizing the cheque clearance process. The motivation lies in the growing need for a solution that enhances security, reduces processing time, and ensures data integrity in financial transactions. By adopting blockchain, the system can provide immutable transaction records, minimize human intervention, and significantly reduce operational inefficiencies. The proposed solution uses Ethereum smart contracts to enable real-time verification, validation, and clearance of cheques. Each transaction is permanently recorded on the blockchain, ensuring transparency and auditability. The decentralized nature of Ethereum removes reliance on a central authority, thereby increasing system resilience and reliability. This innovative approach aims to redefine the cheque clearance process, offering banks and users a seamless, secure, and efficient transactional experience.