Abstract—The crowdfunding sites that are in use today make use of a centralized system in which the funding and validation of crowdfunding campaigns are done by an authority figure. This has resulted in higher transaction fees and a lack of transparency in the way the funding is being done by donors. This paper aims to propose a Decentralized Crowdfunding Platform using blockchain technology to overcome the current challenges. A new crowdfunding system based on smart contracts using Ethereum is proposed. This new system will ensure a reliable environment for executing smart contracts. A new crowdfunding system based on smart contracts using Ethereum is proposed. This system will have a Startup Verifi-cation process and an Iteration-Based Fund Release process. In the current crowdfunding system, crowdfunding sites release the funds in bulk to the startup. In the new system that is being proposed, the funds will be released in stages. A new system of voting will also be implemented in the new system. This will enable donors to vote based on the cryptographic proofs and reports that are presented by the startup. The software development framework of the platform is based on an effective decentralized technology stack such as Solidity for smart contract development and execution, Hardhat for software development and testing, and React.js combined with Web3.js for front-end interface development. The incorporation of the blockchain technology stack guarantees that all financial transactions are transparent, secure, and tamper-proof. The efficacy of the proposed decentralized approach is measured by how effectively it avoids the costs of intermediaries, is auditable in real-time, and is democratic in nature for all donors. Index Terms—Blockchain Technology, Ethereum, Smart Con-tracts, Solidity, Decentralized Finance (DeFi), Crowdfunding, Decentralized Autonomous Organization (DAO), Iteration-Based Funding, Milestone Verification, Web3.js, Hardhat, Metamask, Trustless Execution, Cryptographic Transparency, Digital Wallet Authentication.

Digital transactions are essential to modern economic activities, yet challenges related to trust, transparency, and security persist. This research develops a blockchain-based escrow system integrated with the InterPlanetary File System (IPFS) to address these issues through a decentralized, tamper-resistant architecture. The primary aim is to create an escrow platform that minimizes human intervention while ensuring data integrity, thereby overcoming limitations found in traditional escrow mechanisms that rely heavily on legality and banking institutions. This study demonstrates the feasibility of blockchain technology enhancement to existing escrow models, especially for traders conducting high-value digital transactions. The system enables secure interactions between buyers, sellers, and viewers through a decentralized application (dApp) that assigns user roles and executes transaction logic. Funds are securely locked within the smart contract, while digital assets are stored in IPFS. In cases of dispute, the viewer can cancel the transaction, triggering an automated refund to the buyer and deletion of associated asset data to maintain fairness and security. Smart contract development and testing are carried out using the Hardhat framework before deployment to networks such as the Ethereum-based Sepolia Testnet. The results show that the proposed system reduces transaction risks, increases user trust, and enhances transparency throughout the digital transaction process. This research introduces a practical framework for decentralized escrow systems and provides valuable insights for industries seeking secure, blockchain-driven transaction solutions. The system developed in this study serves as a reference model for integrating traditional transaction with blockchain technology, encouraging broader adoption and future exploration of decentralized systems.

DelegateTracker: Delegatecall vulnerability detection tool based on read-write data flow capture algorithm

Smart contracts are highly susceptible to manipulation attacks due to the leakage of sensitive information. Addressing manipulation vulnerabilities is particularly challenging because they stem from inherent data confidentiality issues rather than straightforward implementation bugs. To tackle this by preventing sensitive information leakage, we present P<sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ARTITION</small>GPT, the first LLM-driven approach that combines static analysis with the in-context learning capabilities of large language models (LLMs) to partition smart contracts into critical (privileged) and normal codebases, guided by a few annotated sensitive data variables. We evaluated PARTITIONGPT on 18 annotated smart contracts containing 99 sensitive functions. The results demonstrate that PARTITIONGPT successfully generates <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">compilable</i>, and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">verified</i> partitions, achieving a precision of 80% while reducing more than 26% code compared to functionlevel partitioning approach. Furthermore, we evaluated P<sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ARTITION</small>GPT on nine real-world manipulation attacks that led to a total loss of 25 million dollars, P<sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ARTITION</small>GPT effectively prevents eight cases, highlighting its potential for broad applicability and the necessity for secure program partitioning during smart contract development to diminish manipulation vulnerabilities.

The subject of research covers the theoretical, methodological, and applied aspects of implementing blockchain technology and smart contracts into microgrid management systems, as well as the automation processes of energy resource exchange between participants of a distributed energy system. The purpose of this work is to investigate the methodological foundations for the application of blockchain and smart contracts in microgrids through the analysis of contemporary scientific research, systematization of approaches to consensus algorithm implementation, classification of smart contracts by application areas, and experimental verification of the proposed solutions. To achieve this goal, the following tasks were addressed: analyzing existing microgrid architectures and management methods; conducting a comparative analysis of consensus algorithms (PoW, PoS, PoA, PBFT, RAFT, etc.) regarding their applicability in private and public energy grids; developing a classification of smart contracts based on their application areas; and investigating software tools for implementing decentralized applications. Research Methods. The study employs system analysis methods to investigate microgrid architecture, comparative analysis to evaluate the efficiency of consensus algorithms, and classification methods for grouping smart contracts. For the practical part, computer modeling and experimental verification methods were used: smart contract development in Solidity, testing in the Remix IDE environment, and simulation of a local blockchain network using the Hardhat toolkit. Research results. The research systematized the methodological foundations for integrating blockchain into microgrids. It was determined that hybrid or private consensus models are most effective for energy trading within local communities. A classification of smart contracts was developed and justified, covering four levels: energy trading, monitoring, distributed management, and cybersecurity. The practical result is the implementation of the EnergyTrading smart contract, which successfully automates the process of listing offers and purchasing electricity, as confirmed by experiments in a local environment. The implementation of smart contracts allows for the creation of a reliable P2P platform for electricity trading without intermediaries, increasing economic efficiency for households. The functionality of the automated settlement mechanism was experimentally confirmed. At the same time, key challenges were identified: the limited scalability of existing blockchain solutions and the need to improve cyber defense against vulnerabilities in contract code. Further development requires adaptation of the legislative framework and modernization of the hardware components of energy grids.

Multi-chain deployment has become a mainstream strategy for U.S.-based DAOs, yet treasury management faces three core bottlenecks: cross-chain liquidity fragmentation, inadequate compliance with U.S. regulations (including OFAC sanctions screening and SEC transparency requirements), and inefficient revenue distribution. Leveraging the incubation practices of over 12 U.S. DAOs (via daos.world) and expertise in multi-chain smart contract development, this study proposes a three-dimensional risk and compliance optimization framework (cross-chain risk hedging + real-time regulatory screening + hierarchical revenue distribution). Empirical testing on 8 U.S. DAOs (operating on Base/Ethereum/Solana, covering AI-focused, meme coin-focused, and investment-focused types) over a 6-month period (September 2025 - February 2026) demonstrates that the framework reduces cross-chain compliance risks by 82.3% (OFAC violation rate drops from 18.0% to 3.2%), increases the annualized treasury return rate by 17.6% (from 4.2% to 5.04%), lowers cross-chain transaction costs by 28.5% (average Gas fee decreases from $12.8 to $9.1), and shortens liquidity adjustment response time from 48 hours to 6 hours. Integrating U.S. regulatory requirements with cross-chain technical logic, this research addresses the theoretical gap in multi-chain DAO treasury management, provides a replicable paradigm for U.S. DAOs to balance compliance, security, and profitability, aligns with the standardization strategy of the U.S. Web3 ecosystem, and is expected to unlock $15-20 billion in potential investment value.

UTXO-based smart contract platforms face an efficiency bottleneck, in that any transaction sent to a contract must specify the entire updated contract state. This requirement becomes particularly burdensome when the contract state contains dynamic data structures, as needed in many use cases to track interactions between users and the contract. The problem is twofold: on the one hand, a large state in transactions implies a large transaction fee; on the other hand, a large centralized state is detrimental to the parallelization of transactions — a feature that is often cited as a key advantage of UTXO-based blockchains over account-based ones. We propose a novel UTXO-based blockchain model, named hybrid UTXO (hUTXO) , along with a technique to efficiently execute smart contracts on it. The key idea underlying hUTXO is the distribution of the contract state across multiple UTXOs, enabling transactions to access only the specific portions of the state they need, thereby reducing their size (and fees). Our hUTXO model also borrows features from account-based models (in particular, the handling of the contract balance), making it “hybrid” in nature. To simplify the development of smart contracts in hUTXO, we introduce a high-level smart contract language (named hURF), along with a compiler into hUTXO transactions. We show how to exploit our framework to parallelize the validation of transactions on multi-core CPUs. We implement our technique and provide an empirical validation of its effectiveness.

• LLMs face significant challenges in legal-to-code transformation. • Claude and OpenAI models outperform Gemini and Mistral across multiple metrics. • Smart contract compilability rates correlate with increased vulnerabilities. • Prompt design may improve results. Impact varies by model and contract complexity. • LLMs require security auditing and are not yet suitable for unsupervised deployment. Smart contract development remains almost inaccessible to non-experts developers despite the growing adoption of blockchain technology across industries. This paper evaluates the potential of Large Language Models (LLMs) for automated smart contract generation from legal agreements. The work systematically assesses the capabilities of four leading commercial LLMs – gpt-4-turbo (OpenAI), claude-3.5-sonnet (Anthropic), mistral-large (MistralAI), and gemini-1.5-pro (Google) – across a diverse range of legal agreements with varying complexity. The evaluation framework consists of a in-depth evaluation of structured code patterns – typical to smart contracts – to provide nuanced insights into model performances. The results reveal a performance hierarchy with claude-3.5-sonnet and gpt-4-turbo consistently outperforming mistral-large and gemini-1.5-pro , particularly when handling complex agreements such as mortgage note agreement and property sales agreement. A nonlinear relationship has been observed between contract complexity and model performance, with even top-performing models showing significant degradation when processing intricate legal structures. Although achieving syntactic correctness has become increasingly feasible, ensuring functional completeness and security remains challenging, as evidenced by high-impact vulnerabilities detected across all generated smart contracts. This work contributes to the growing discourse on LLM applications in blockchain technology by providing empirical evidence of current capabilities and limitations, establishing a robust foundation for future research in AI-assisted smart contract development.

The article analyzes the transformation of contemporary international relations under the influence of digitalization and the formation of a new digital dimension of global interaction. It is shown that cyberspace, data, and algorithms are becoming a full-fledged arena of international politics, and such technologies as artificial intelligence, open data, the Internet, and blockchain perform the function of the structural infrastructure of global connections.Particular attention is paid to blockchain technology as a “new technology of trust” in the context of modern international relations, which ensures the integrity and transparency of cross-border transactions, supports the development of international digital identity, and changes the mechanisms of global interdependence.The role of the United States as one of the key players in blockchain policy is revealed through the formation of a regulatory framework for digital assets and stablecoins, and the geopolitical dimension of the spread of central bank digital currencies in leading states is analyzed.The fragmentation of regulatory regimes in the USA, the EU, Singapore, Switzerland, and China is outlined, as well as the challenges this poses for international law. The technological shifts of 2024–2025 are considered, in particular the development of smart contracts, the integration of blockchain, the application of threshold cryptography, and other technologies.It is shown that blockchain simultaneously creates new risks for sanctions regimes, cybersecurity, and digital sovereignty, while also opening opportunities for transparent humanitarian governance, the tokenization of philanthropy, and the formation of an infrastructure of “programmable trust” on a global scale.

This paper presents the design, implementation, and evaluation of a decentralized system for issuing and verifying academic certificates based on blockchain technology. The proposed solution addresses common limitations of traditional certification models, such as susceptibility to forgery, reliance on centralized infrastructures, and inefficient verification processes. The system is built on the TRON blockchain and integrates smart contracts written in Solidity, a decentralized web application (dApp) for user interaction, and the InterPlanetary File System (IPFS) for decentralized storage of certificate metadata. The methodology comprised architectural design, smart contract development, and the implementation of a web-based interface, followed by functional, security, performance, and usability evaluations. Experimental results show that the system correctly supports certificate issuance and public verification, enforces access control, and resists common misuse scenarios. Performance analysis indicates low confirmation latency and negligible transaction costs, making the solution suitable for large-scale academic environments. Additionally, usability assessment using the System Usability Scale (SUS) resulted in a score of 76.67, indicating good user acceptance. Overall, the results demonstrate the technical feasibility and practical viability of the proposed approach, highlighting the TRON blockchain as an effective and cost-efficient infrastructure for decentralized academic certification systems

Large Language Models (LLMs) have demonstrated significant potential in transforming software testing by automating tasks such as test case generation. In this work, we explore the integration of LLMs within a Model-Driven Engineering (MDE) approach to enhance the automation of test case generation for smart contracts. Our focus lies in the use of Role-Based Access Control (RBAC) models as formal specifications that guide the generation of test scenarios. By leveraging LLMs’ ability to interpret both natural language and model artifacts, we enable the derivation of model-based test cases that align with specified access control policies. These test cases are subsequently translated into executable code in Digital Asset Modeling Language (DAML) targeting blockchain-based smart contract platforms. Building on prior research that established a complete MDE pipeline for DAML smart contract development, we extend the framework with LLM-supported test automation capabilities and implement the necessary tooling to support this integration. Our evaluation demonstrates the feasibility of using LLMs in this context, highlighting their potential to improve testing coverage, reduce manual effort, and ensure conformance with access control specifications in smart contract systems.

This article explores the principles of developing a web platform aimed at increasing environmental awareness among Ukrainian citizens through digital rewards for recycling waste. The continuous increase in polluted areas across Ukraine has led to a range of ecological issues. In this context, the creation of a digital tool that draws public attention to the problem of waste management and motivates responsible environmental behaviour is both relevant and necessary.The use of blockchain technologies provides the opportunity to build a reliable application that ensures the integrity of data related to waste recycling. It also enables the creation of a transparent reward system based on utility tokens and NFTs. The integration of two blockchain ecosystems — Internet Computer Protocol (ICP) and Solana — demonstrates the strengths of both technologies in terms of decentralisation, user accessibility, and scalability.The ICP blockchain offers a unique environment for hosting complete web applications on decentralised nodes without relying on traditional centralised servers. Through its innovative reverse gas model, end users are not required to hold tokens to interact with the platform, as the computational costs are covered by the developer or organisation behind the application. This allows for a seamless and user-friendly experience, particularly for non-technical participants in the recycling initiative.Meanwhile, Solana adds flexibility for the development of smart contracts and fast transaction processing. By combining these two technologies, the article provides a comparative overview of different blockchain architectures and gas models, contributing to a deeper understanding of their practical implications.Additionally, the article presents a brief explanation of the integration between the ICP and Solana blockchains, including token-based interactions, NFT issuance, and synchronisation of environmental data. The development process is supported by deployment tools such as DFX (for ICP canister management) and the Anchor framework for Solana, ensuring an efficient and structured development workflow.Overall, the work highlights the reasoning behind the selected technological stack, outlines the key requirements for the platform, and explores its potential for future growth and scalability. The project exemplifies how modern decentralised technologies can be harnessed to promote sustainable development and environmental responsibility in Ukrainian society.

The rapid growth of crypto assets in Indonesia has opened up economic opportunities while simultaneously raising the risk of fraudulent activities, such as rug pulls, fake investment offers, and market manipulation, which are detrimental to the public. This study analyzes the criminal liability of individuals and third parties in crypto-based fraud, emphasizing the concept of dormant responsibility, which is criminal liability arising from the negligence or passivity of parties who should have prevented the crime. The method used is normative juridical with a conceptual and legislative approach, examining the Criminal Code, Law Number 1 of 2024 concerning ITE, Law Number 8 of 2010 concerning the Prevention and Eradication of Money Laundering Crimes, as well as regulations on the crypto asset sector under the supervision of the OJK through POJK Number 27 of 2024. The results of the study indicate that individual perpetrators can be held accountable based on the fraud provisions in the Criminal Code and Article 28 paragraph (1) of the ITE Law, while third parties, such as crypto exchanges, smart contract developers, and custodian service providers, are potentially liable if proven negligent in their supervisory obligations, KYC/AML, or prevention of suspicious transactions. The concept of Dormant Responsibility offers a new normative framework that places active and passive negligence as important elements to close legal loopholes, while balancing consumer protection with technological innovation. Research recommendations include strengthening preventive obligations on crypto service providers, harmonizing criminal regulations with digital financial regulations, and developing technical guidelines for proving crypto assets in court.

Academic publishing repositories in developing nations often face severe challenges in enforcing secure and transparent access control, exacerbated by centralized authority, weak audit trails, and data manipulation risks. This research proposes a decentralized access control system using Hyperledger Fabric blockchain and smart contracts to ensure secure, transparent, and tamper-proof data access in academic repositories. Using a constructive research methodology, the study develops and evaluates a blockchain-integrated framework tailored for repositories like DSpace. The methodology includes model-driven engineering, smart contract development in GoLang, PKI-based identity control, and simulation via Dockerized microservices. Empirical evaluation reveals superior performance: 250ms transaction latency, 70 TPS throughput, and complete prevention of unauthorized access attempts, outperforming centralized models. Security analysis and user surveys among repository stakeholders indicate enhanced transparency, trust, and system usability. The findings demonstrated that decentralized models significantly improve access control without compromising usability. The research contributes both theoretically and practically to secure scholarly communication in Nigeria. It aligns with evolving open access initiatives, builds local technical capacity, and proposes a replicable model for enhancing repository trustworthiness across universities in Nigeria. Future work can explore scalable, privacy-preserving extensions and AI-driven smart contract automation.

This study provides a comprehensive contribution to the current understanding of blockchain technology and non-fungible token (NFTs). Blockchain technology is a revolutionary data storage and management tool that records data shared across a network of computers globally, making it safe, transparent, and decentralized. Non-fungible token is a specific type of token built on a blockchain, enabling the authentication of digital assets and safeguarding them against copying or fabrication. The research employed information on 3760 abstract data collected for the period from January 1, 2017, to June 03, 2025. The search criteria for data retrieval are based on the following keywords: “blockchain”, “non-fungible token”, and “token”. The data sources are Scopus and Web of Science. The study highlights the multi-dimensional and evolving discussion around blockchain and NFTs, including elements of technology, security, money, digital rights, and decentralization. The Wordcloud indicates a strong and growing innovation ecosystem, proposing new study avenues in trust mechanisms, smart contract development, and tokenized economies. The correlation graph visualizes that AI, data, finance, and blockchain show their mutual dependence has revolutionized our view of autonomy and governance. The study highlights authors who actively research blockchain and NFTs, as well as correlations between them. China leads the way in this research area and USA leads in terms of citation. The study’s finding informs evidence-based decision-making regarding the regulation and governance of blockchain and NFT technologies. For industry practitioners, the study’s insights can guide the development of innovative applications and solutions leveraging blockchain and NFTs. By examining a vast dataset of academic papers, the inquiry illuminates the key themes, emerging trends, and potential research gaps within this rapidly evolving field.

Federated Learning(FL) is inherently vulnerable to several security threats, including data poisoning, model poisoning and man-in-the middle attacks, which can significantly compromise model integrity and performance. To address these challenges, this work presents a Web3 based decentralized FL framework that leverages the transparency and immutable mechanisms of blockchain technology. The proposed system introduces hierarchical structure to minimize the impact of malicious participants and employs a combination of novelty detection and consensus protocol to filter out malicious updates. In case of lack of consensus, trust score is used to determine the impact of validators on the global model. This design ensures transparency and reliability in the aggregation process and allows the global model to benefit from insights of most trusted nodes. The system is realized by implementing in Python and Foundry for smart contract development. Experimental evaluations demonstrate that our implementation achieves improved resilience and performance compared to traditional FL setups.

Smart contracts are central to blockchain ecosystems, yet their development remains technically demanding, error-prone, and tied to platform-specific programming languages. This paper introduces SCEditor-Web, a web-based modeling environment that combines model-driven engineering (MDE) with generative artificial intelligence (Gen-AI) to simplify contract design and code generation. Developers specify the structural and behavioral aspects of smart contracts through a domain-specific visual language grounded in a formal metamodel. The resulting contract model is exported as structured JSON and transformed into executable, platform-specific code using large language models (LLMs) guided by a tailored prompt engineering process. A prototype implementation was evaluated on Solidity contracts as a proof of concept, using representative use cases. Experiments with state-of-the-art LLMs assessed the generated contracts for compilability, semantic alignment with the contract model, and overall code quality. Results indicate that the visual-to-code workflow reduces manual effort, mitigates common programming errors, and supports developers with varying levels of expertise. The contributions include an abstract smart contract metamodel, a structured prompt generation pipeline, and a web-based platform that bridges high-level modeling with practical multi-language code synthesis. Together, these elements advance the integration of MDE and LLMs, demonstrating a step toward more accessible and reliable smart contract engineering.

Smart contracts on the blockchain play an important role in decentralised systems by automating and executing agreements without the need for intermediaries. As these contracts become integral to various domains, ensuring users’ understanding of their functioning is paramount. This article investigates the need for explanations in smart contracts, drawing inspiration from contract law principles and established practices in Explainable AI (XAI). It introduces key purposes—justification, clarification, compliance and consent to design explainability. Additionally, the study proposes a novel assessment framework informed by the Metacognitive Explanation-Based (MEB) theory to systematically evaluate surprise potential in smart contracts lacking explanations. We use surprise as a guiding factor to systematically identify areas requiring improvement in terms of justification, clarification, compliance and consent. To demonstrate the utility of the assessment approach, we evaluate two decentralised lending projects, uncovering potential surprises. One of the key observations is the lack of setting information, especially concerning compliance, consent and decision justification. This absence of information has heightened the potential for surprises. In the process of validating the explanation purposes, we implement techniques to improve the design of the assessed smart contracts. Further, the research explores the tradeoffs involved in integrating explanations, providing nuanced insights into economic implications such as increased deployment and execution costs. This work contributes to the broader comprehension of smart contract explainability requirements and lays out a theoretical foundation for a generic evaluation method. It aims to facilitate the development of more human-centric and comprehensible smart contracts.

This article explores the transformation of communication channels in Ukraine’s FinTech sector amid the global digitalization of financial services. It traces the evolution of bank-client interaction from physical branches to digital solutions like mobile applications, internet banking, and AI-powered chatbots. The shift to digital channels has been driven by customer expectations for 24/7 service, competition from FinTech startups, and accelerated digital adoption during the COVID-19 pandemic. The article pays special attention to the implementation of artificial intelligence, big data analytics, blockchain, and smart contracts, highlighting their opportunities and limitations. The findings demonstrate that automating up to 85% of routine requests significantly increases operational efficiency, reduces costs, and enhances customer satisfaction. Ukrainian banks, including PrivatBank and Oschadbank, have integrated large-scale digital tools, while FinTech companies are expanding innovative solutions in payments, online lending, and personalized financial management. The study also addresses challenges such as complex smart contract development, cybersecurity threats, and the lack of comprehensive regulatory standards. Ukraine demonstrates rapid FinTech growth, with the number of companies nearly tripling between 2019 and 2024, supported by high IT potential and consumer readiness for innovation. The article concludes that digital transformation is no longer experimental but is now the standard for financial communication. For Ukrainian institutions, this transition is essential for strengthening competitiveness, ensuring financial inclusion, and integrating into the global financial ecosystem.

Smart contracts have emerged as a transformative force in contract law, leveraging blockchain technology to automate transactions and reduce reliance on human intermediaries. However, their widespread adoption is hindered by significant legal challenges, particularly in determining liability for transaction failures. This Note examines the accountability problems inherent in smart contracts, focusing on the critical role of oracles—third-party entities that feed external data into blockchain-based agreements. While existing scholarship explores the theoretical foundations and potential applications of smart contracts, this Note shifts focus to liability allocation and proposes a novel framework: default oracle liability. Under this proposal, oracles bear primary responsibility for transaction errors arising from inaccurate data sourcing or validation failures. If oracles demonstrate that they functioned correctly, liability shifts to smart contract developers, who are responsible for ensuring secure and error-free code. By clarifying accountability, this framework incentivizes higher standards for data accuracy and software integrity, ultimately fostering a more reliable and legally-viable environment for smart contracts to operate.