Đức An Nguyễn, Minh Thành Phí, Duc Dung Pham, Thị Hương Thơm Hồ
Ngành logistics hiện đại đang đối mặt với các thách thức về sự thiếu minh bạch, chi phí trung gian cao và khó khăn trong việc giải quyết tranh chấp khi giao hàng trễ hạn. Nghiên cứu này đề xuất và triển khai một ứng dụng phi tập trung (Decentralized Application - DApp) quản lý hợp đồng logistics trên nền tảng Blockchain Ethereum (mạng thử nghiệm Sepolia). Hệ thống sử dụng kiến trúc lai (Hybrid Architecture) kết hợp giữa Blockchain để xử lý thanh toán hoặc logic nghiệp vụ và IPFS để lưu trữ hồ sơ phi tập trung. Điểm mới của nghiên cứu là việc tích hợp cơ chế "Ký quỹ thông minh" (Smart Escrow) và "Phạt vi phạm tự động" (Automated Penalty) ngay trong hợp đồng thông minh (Smart Contract). Kết quả thực nghiệm cho thấy hệ thống đảm bảo tính toàn vẹn dữ liệu, tự động hóa hoàn toàn quy trình thanh toán dựa trên trạng thái giao hàng thực tế và xử lý chính xác các trường hợp vi phạm thời gian cam kết mà không cần sự can thiệp của bên thứ ba.AbstractThe modern logistics industry faces challenges regarding lack of transparency, high intermediary costs, and difficulties in resolving disputes over late deliveries. This study proposes and implements a decentralized application (DApp) for logistics contract management on the Ethereum Blockchain (Sepolia testnet). The system employs a Hybrid Architecture combining Blockchain for payment or business logic processing and IPFS for decentralized record storage. A novel feature of this research is the integration of "Smart Escrow" and "Automated Penalty" mechanisms directly within the Smart Contract. Experimental results demonstrate that the system ensures data integrity, fully automates the payment process based on actual delivery status, and accurately handles delivery deadline violations without third-party intervention.Keywords: Blockchain, Ethereum, smart contract, IPFS, Logistics, automated Penalty.
AI text-to-video systems, such as OpenAI’s Sora, promise substantial efficiency gains in media production but also pose risks of biased outputs, opaque optimization, and deceptive content. Using the Orientation–Stimulus–Orientation–Response (O-S-O-R) model, we conduct an empirical study with 209 Chinese new media professionals and employ structural equation modeling to examine how information elaboration relates to AI knowledge, perceptions, and adoption intentions. Our findings reveal a knowledge paradox: higher objective AI knowledge negatively moderates elaboration, suggesting that centralized information ecosystems can misguide even well-informed practitioners. Building on these behavioral insights, we propose a blockchain-based governance framework that operationalizes five mechanisms to enhance oversight and trust while maintaining efficiency: Expert Assessment DAOs, Community Validation DAOs, real-time algorithm monitoring, professional integrity protection, and cross-border coordination. While our study focuses on China’s substantial new media market, the observed patterns and design principles generalize to global contexts. This work contributes empirical grounding for Web3-enabled AI governance, specifies implementable smart-contract patterns for multi-stakeholder validation and incentives, and outlines a research agenda spanning longitudinal, cross-cultural, and implementation studies.
Supply chain finance, a critical tool for industrial chain coordination in the digital economy, faces challenges such as centralized identity authentication, data silos, and privacy risks, with traditional models constrained by single-point failures and inefficient data sharing.While blockchain's decentralized and tamper-proof features offer a solution, existing approaches often lack comprehensiveness.To address this, this study proposes two integrated solutions: first, the ZK-SCFI scheme, which leverages Merkle trees for identity storage, Paillier homomorphic encryption for pseudo-identity generation, and zero-knowledge proofs for privacy-preserving verification, effectively avoiding centralized risks and ensuring transaction non-associability; second, the TRU-SABE framework, combining blockchain and IPFS to enhance ciphertext-policy attribute-based encryption (CP-ABE) with keyword search, user revocation, outsourced decryption, and malicious user tracking, addressing traditional limitations like high computational costs and scalability issues.Experiments demonstrate TRU-SABE's superior efficiency, with user-side decryption overhead reduced to 3TE and storage advantages from factor group structures for attribute keys and ciphertexts, while the hybrid architecture alleviates data silos and storage pressure.A prototype system built on Fisco Bcos consortium blockchain, Spring Boot backend, and Vue.js frontend validates core functionalities, including encrypted data sharing and smart contract-based traceability.This work provides a holistic privacy-preserving solution for supply chain finance, with future directions focusing on balancing privacy with regulatory compliance, optimizing multi-authority key management, and expanding system capabilities to enhance security and efficiency.
The diverse potential applications of blockchain technology, or so-called universality, can actually bring fear and a sense of loss to many. This study attributes this to legal uncertainty. For example, while the experience of “The DAO” incident demonstrated the complexity and risks of distributed ledger technology (DLT) and tokens, the potential and legal implications of decentralized and decentralized organizations remain unclear. This has raised serious questions about the future. To analyze the issues, assess applicability, and explore legal directions, it is crucial to understand the technical aspects. First and foremost, it is crucial to understand and examine the structural and operational legal issues surrounding DAOS, establish their legal status, and establish legal regulations.<br/> With this understanding, this study aims to address the following key issues: von Gier) and how it can be viewed from the perspective of corporate law. ii) To conduct a broad comparative legal review, we first analyze the enactment of the DAO Act in Wyoming, USA. This will be followed by a comparative study of other representative legislative examples actively utilizing DAOS. iii) We examine effective legal regulations, including those related to operational management and legal acts, to eliminate legal uncertainties that may arise during the process of establishment, operation, and dissolution of corporations and organizations. iv) As mentioned above, we aim to structure the discussion around corporate law from a macroscopic perspective.<br/> Specific details include the rights and obligations of the parties, various situations related to compensation in the event of damages, matters related to proof of breach of rights and obligations, and the subject and scope of liability. This model also provides a framework for preparing for situations where a legislative vacuum may arise before the law is enacted.
Recently, the smart grid has been proposed as the solution to our sustainable source of electricity. Along with the blockchain network as a tool for the decentralized power generation management platform, we can achieve peer-to-peer energy trading. In this research, we emphasize the design of a blockchain smart contract for searching the closet and available electric vehicle charging stations. In the future, each house with solar cell rooftops can generate enough electric power to provide charging service. Therefore the charging stations will eventually be scattered in both rural and urban areas. If we use blockchain technology, people can generate electricity themselves and turn their homes into charging stations, saving money directly without going through intermediary banks. However, to implement this system, there are still many challenges such as long charging time, the unavailability of charging stations, searching and reserving charging systems, etc. The algorithm design concept is based on the idea of bidding. The proposed smart contract algorithm design and development is used as an application to recommend charging stations that are available and closest to electric vehicles by applying smart contracts and blockchain technology. Each station participates in the bidding process by specifying its location and the length of the queue. The smart contract then calculates the distance between the vehicle and the station and checks the waiting time whether it meets the needs of electric vehicle users. Within the bidding time, the smart contract will automatically return the location of the nearest charging station, similar to winning bidders. The experimental results showed that the distance calculations proposed in the smart contracts matched the actual distances that were actually usable by Google for 84 out of 100 rounds of the experiment.
Against the background of the digital economy, the conventional matching strategy of supply and demand is unable to meet the requirements of matching supply and demand industrial interconnection with digitalization as the core element. To solve the trust problem of supply and demand matching contract of digital industrial interconnection, a decision-making framework of supply and demand matching of industrial interconnection based on smart contract is proposed. Based on the massive resource data, a resource characteristic attribute matrix is constructed, and the Fuzzy C-Means algorithm is used to classify and reduce the dimension of massive resource data. Based on the attribute expectation of supply and demand, the objective function with maximum satisfaction is created to realise bidirectional matching. Finally, the effectiveness of the proposed method is demonstrated by an example.
Minh Tri Le, O. M. Harris, Charlotte Bennett, Fiona Greene
Amid the rapid development of Web3.0 technologies and blockchain infrastructures, the commercial real estate industry is experiencing a significant shift toward digitalization. This study proposes a tokenization framework for commercial real estate assets, grounded in the ERC-1400 standard. The system enables precise asset share registration via smart contracts and ensures regulatory compliance through on-chain KYC authentication and identity mapping mechanisms. To address liquidity challenges, an off-chain valuation oracle and a decentralized finance (DeFi) collateralization model are integrated into the architecture, enhancing the tradability of tokenized real estate assets. Simulation experiments and empirical analyses were conducted to evaluate title confirmation efficiency, asset liquidity, and operational controllability. The results demonstrate that, compared to conventional methods, the proposed system improved title confirmation efficiency by 99.6% (t = 327.4, p < 0.001), increased average daily transaction volume by 327% (χ² = 158.6, p < 0.001), achieved 100% transaction accuracy in 1,500 simulations, and successfully identified and intercepted 47 abnormal transactions via the KYC mechanism. These findings provide both a viable technical approach and theoretical basis for implementing real estate asset tokenization in practice, contributing to the secure and scalable integration of traditional assets into decentralized ecosystems.
This paper is dedicated to addressing the management challenge of fake transaction behavior in recommendation systems and proposes a novel solution that integrates smart contracts and blockchain technology. By delving into the decentralized nature of blockchain, the immutability of its data, and the automatic execution advantages of smart contracts—especially the anonymous transaction environment provided by the latter—it not only effectively protects the personal privacy of participants but also reduces transaction biases caused by differences in identity, thereby promoting a more fair and transparent transaction process. Taking the anti-fake transaction mechanism of e-commerce platforms as an example, this paper demonstrates the significant effectiveness of this technological combination in enhancing data reliability, enabling dynamic rule adjustments, and facilitating cross-platform collaboration. The study finds that this method can reduce the false transaction detection omission rate by 30% to 50%, while also enhancing the fairness of the recommendation system and the level of user trust. In addition, the paper discusses potential future directions for technological integration, such as privacy computing and federated learning, and provides corresponding legal compliance recommendations.
The digital transformation of finance demands advanced risk control models capable of multimodal analysis while preserving privacy. Existing federated learning approaches lack synthetic data generation capabilities for comprehensive risk assessment. This study proposes a Generative Federated Learning-Driven Multimodal Risk Control (GFL-MRC) model that integrates federated learning with generative adversarial networks (GANs) for privacy-preserving synthetic data generation and cross-modal feature fusion. The framework enables decentralized institutions to collaboratively train models without sharing raw data, employing a cross-modal attention mechanism to correlate structured (transactions), semi-structured (profiles), and unstructured (text/image) data. Experiments on financial datasets show GFL-MRC achieves $12.7 \%$ higher fraud detection accuracy ($F 1=0.892$) than conventional federated learning, reduces false positives by 23.4 % through synthetic augmentation, and ensures GDPR/CCPA compliance via differential privacy. The model particularly enhances detection of emerging fraud patterns in low-data scenarios by generating privacy-compliant training samples. This work advances collaborative risk management by bridging regulatory constraints with AI innovation, offering financial institutions a scalable solution for multimodal risk analysis without compromising data privacy.
Against the backdrop of increasingly severe global climate change and environmental challenges, green finance, as a bridge connecting capital and sustainable development, is facing problems such as information asymmetry, transaction frictions and regulatory challenges. This study systematically explores the innovative applications of blockchain technology in the field of green finance and its economic effects. Through literature research and case analysis, we found that blockchain technology, with its characteristics of decentralization, immutability and smart contracts, has shown significant advantages in improving transparency, reducing transaction costs and alleviating the phenomenon of "greenwashing". Research shows that the application of blockchain in areas such as green bonds, carbon trading, renewable energy certification and green supply chain finance has produced economic benefits such as reduced financing costs, improved market efficiency and enhanced information transparency. This paper constructs a comprehensive assessment framework to provide guidance for policymakers and market participants to promote the innovative development of green finance.
In the context of global cross-border payments exceeding $150 trillion, traditional mediation architectures, such as SWIFT, face challenges due to high costs, inefficiencies, and fraud risks. However, blockchain technology become an important driver of innovation in cross-border payments with the characteristics of decentralization, real-time and immutable. This paper aims to answer two core questions: Blockchain technology how to improve the efficiency of cross-border payments through smart contracts, cross-chain protocols and other technical features? How to identify and prevent key risks such as private key security and regulatory conflicts? Through the logical framework of "technical basis - efficiency analysis - risk identification - prevention and control strategy", combined with case comparison (such as RippleNet and SWIFT) and quantitative data (such as Stellar network $0.01 / transaction cost). This paper systematically analyzes the role of blockchain in disintermediation, cost compression, and transparency optimization. Besides, the risks of technological vulnerabilities, regulatory fragmentation and market volatility are revealed. Then, this paper proposes a collaborative governance scheme of hybrid architecture, zero-knowledge proof and multilateral regulatory sandbox. Research finding, blockchain technology can reduce cross-border payment time to seconds and reduce costs by more than 90%, but it needs to deal with challenges such as throughput constraints, conflicting regulatory standards and the volatility of digital currencies. It is suggested that future research focus technology optimization, multilateral regulatory collaboration and market ecological integration, provide theoretical and practical support for building an efficient and secure global payment system.
Land serves as a crucial repository of resource elements, and enhancing the green use efficiency of urban land (GUEUL) is essential for attaining sustainable development. Based on 296 cities in China from 2006 to 2022, this study explored the relationship between land system innovation and GUEUL by integrating multi-source data, ArcGIS analysis, the EBM-DEA model, and the DID model, and elucidating the temporal trend and spatial utilization characteristics of GUEUL in China. Based on the natural experimental scenario of the pilot reform of China’s urban construction land use approval system, this study finds through in-depth analysis of the double-difference model that the vertical transfer of land approval authority has fundamentally optimized the development pattern of GUEUL, and that this positive impact is mainly reflected in two dimensions: on the one hand, it reduces the systematic transaction costs, and on the other hand, it enhances the density of industrial spatial agglomeration. Second, the lower the initial level of infrastructure and the lower the degree of dependence on land finance, the more significant the decentralization of land approval power in the promotion of GUEUL. Currently, China is undergoing a swift phase of urbanization and industrialization, and this study provides policy support for improving the comprehensive efficiency of green land use and promoting high-quality and sustainable development of the region.
This research investigates privacy protection mechanisms and data security policy optimization for blockchain-based digital rights management platforms to balance transparency with robust privacy protection. A comprehensive experimental framework was developed, integrating advanced cryptographic techniques with intelligent policy management systems. A multi-layered validation methodology employed formal verification, black-box/white-box testing, and stress tests to validate performance across security, efficiency, and usability dimensions. The implemented solution provided 99.99% security assurance while achieving a 47% improvement in processing efficiency through zero-knowledge proofs and homomorphic encryption. Transaction processing reached 3,750 TPS (peaking at 4,200 TPS), with 99.8% regulatory compliance and 99.9% automated policy conflict resolution. The research demonstrates significant advancements in blockchain-based privacy protection through novel cryptographic implementation and automated policy management, establishing a robust framework for secure digital rights management. This solution offers substantial value for content delivery networks, digital asset management systems, financial institutions, and government services where the balance between transparency and privacy is critical, while reducing compliance management costs.
With the widespread application of drones in military, logistics, agriculture and other fields, their security issues have become increasingly prominent, especially the reliability and efficiency of identity authentication have become key challenges. This article proposes a drone identity authentication and key negotiation scheme based on blockchain technology, aiming to solve the problems of single point of failure, high computational overhead, and easy leakage of secrets in physical capture that exist in traditional authentication methods. This scheme combines the distributed ledger and smart contract technology of blockchain to design an efficient and secure two-way authentication mechanism, and generates three session keys through one authentication, achieving efficient key negotiation. Compared with existing lightweight identity authentication and key negotiation schemes for drones, this scheme significantly improves authentication efficiency while ensuring security, making it suitable for large-scale drone swarm application environments with strong real-time performance and insufficient computing resources.
Blockchain technology, characterized by its immutability, decentralization, transparency, security, and traceability, has shown vast potential for applications in secure IoT communications and data protection through its deployed smart contracts. While machine learning-based code generation systems aim to automate high-quality programming solutions, they face significant challenges when addressing blockchain-related issues. This paper analyzes the limitations of machine learning in identifying vulnerabilities within blockchain smart contracts and proposes robust solutions. To achieve this, this paper suggests organizing multiple security experts for labeling, developing efficient labeling tools, employing semi-supervised learning to reduce dependency on labeled data, and establishing a continuous update mechanism for labeled datasets to adapt to evolving threat landscapes. To address the scarcity of training samples in the blockchain domain, this paper introduces a method for generating additional Solidity smart contract training samples using data augmentation techniques. Given that traditional data augmentation methods are not suitable for Solidity, the approach involves converting Solidity contracts into Python code for processing, then reverting them back to Solidity post-augmentation, with provided code examples. Furthermore, leveraging established non-blockchain code to train blockchain-related models enhances model performance and generalization capabilities. These strategies effectively tackle the issue of insufficient training samples in the blockchain field and offer new perspectives on the conversion between Solidity and Python.
This paper comprehensively discusses the security mechanism of blockchain-based digital currency transactions, from the application of distributed ledgers, consensus algorithms, smart contracts, to the implementation of multiple signatures and cold storage schemes, to advanced privacy protection technologies, such as zero-knowledge proofs and homomorphic encryption. In particular, we delve into innovative mechanisms for attack prevention, including the fusion of heterogeneous multi-chain architectures with PoW+PoS hybrid consensus models. The article also details the practice of performance evaluation and security testing through a series of carefully designed experiments such as throughput and latency testing under different loads, resource utilization monitoring, and security reviews and comparisons with competitors. Experimental results show that the system exhibits good throughput growth under high load, but with the increase of latency, resource utilization is efficient and tends to saturation, most of the security protection mechanisms meet the standards, but access control problems that need to be optimized and high-risk vulnerabilities to be repaired are also found.
Haomiao Wang, Yan Guan, Tianbo Wang, Shuang Yang · 8 authors
In order to cope with the problems of imperfect trading system in the current renewable energy trading, and the poor effect of green certificate system in encouraging renewable energy to connect to the grid and alleviating the pressure of financial subsidies, in the context of carbon emission reduction in the power industry and the development of renewable energy, we put forward a multi-subjects gaming trading model under the blockchain architecture considering the carbon-green certificates and categorize the system participants into four groups. The participants of the system are divided into four categories to form a cooperative gaming alliance, and through the introduction of the concept of “green pass” and the consensus mechanism based on POC-GT, combined with the key features of blockchain such as distributed ledger and smart contract, we construct an innovative trading market structure and operation mechanism. By integrating blockchain technology and multi-subject game theory, an efficient, fair and transparent trading model is designed to optimize the allocation of carbon emission resources, promote the development of green energy, and achieve synergistic sustainability of the economy and the environment.
This study constructs an innovative credit assessment model, combining blockchain technology with a credit scoring system to focus on solving data security and privacy protection issues. The model achieves security and transparency in the credit assessment process by designing a series of advanced algorithms and system architectures. The model uses zero-knowledge proof technology to allow users to verify their identities without revealing specific data information, thereby ensuring that privacy is not leaked. The model also introduces a distributed storage mechanism to store data on multiple nodes in a dispersed manner, preventing single point failures and improving the immutability of data. This study verifies the superiority of the model in data processing speed, assessment accuracy and system security through simulation tests. The results show that the accuracy of the model is about 15% higher than that of traditional methods, and the risk of data leakage is significantly reduced by about 20%. The blockchain credit assessment model achieves efficient and reliable credit assessment while meeting user privacy protection, providing a reference with practical value for the construction of the future credit system.
Utilizing the Ethereum Geth client, we constructed a consortium blockchain and developed a smart contract in the Solidity programming language.The smart contract encompasses three primary modules: system initialization,anti-counterfeiting information upload, and anti-counterfeiting information retrieval.Through the Remix Integrated Development Environment (IDE), the smart contract was successfully deployed onto the Ethereum blockchain network.To ascertain the robustness and security of the smart contract, we conducted exhaustive deployment and invocation tests using the Ganache testing software in conjunction with the MetaMask lightweight Ethereum wallet, thereby validating the reliability and efficacy of the functions for uploading and querying anti-counterfeiting information.
In response to the mandatory requirements of the EU Carbon Tariff and the New Battery Law for the full life cycle carbon management of Chinese battery enterprises, this paper takes CATL as a case to explore the construction path of a carbon footprint account driven by blockchain technology. Based on CATL's "Times Carbon Chain" platform, a three-layer technical architecture was constructed by adopting distributed ledger, perspective life cycle assessment and smart contract technologies: data layer, accounting layer and application layer. By comparing the full life cycle carbon footprint of the 1kwh lithium iron phosphate battery of BYD's subsidiary FinDreams Battery, the research found that the carbon emissions in the transportation link of CATL were significantly higher than those of the benchmark enterprises. Based on this, a multimodal transportation optimization plan was proposed. This work provides a reusable carbon management technology paradigm for Chinese enterprises to deal with international carbon barriers, which has practical value for promoting the implementation of China's carbon neutrality goal.
This paper discusses the application of blockchain technology in document management for the library. With the characteristics of encryption algorithm, distributed ledger, distributed architecture and traceability, this technology is of great significance in enhancing the security of document resources, optimizing the copyright protection, improving the efficiency of resource sharing and collaboration, and optimizing the experience of reader services. Its application covers the joint collection and edit system of document resources based on blockchain, decentralized storage and distribution platform, knowledge graph co-construction and sharing, and evaluation and contribution incentive mechanism participated by readers, so as to promote more efficient and intelligent library services.