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 rule of law is a critical support for the national governance system and governance capacity. The legalization of public finance construction is the foundation for achieving fiscal fairness, efficiency, and justice, promoting the rational allocation of social resources, maintaining social stability, and promoting sustainable economic growth. It is of great significance for building a rule of law government and improving modern budget systems. The legalization of public finance construction should follow the principles of fairness and justice, rule of law governance, and transparency, providing strong institutional guarantees for the sustainable development of public finance. This study takes public finance construction as the research object and focuses on the rule of law principles and practical paths of public finance construction. It analyzes the rule of law principles from a theoretical perspective and proposes practical paths from a practical perspective. At present, the decentralization of budget preparation entities, chaotic internal relationships within administrative institutions, and slow progress in the rule of law are all practical problems that plague the construction of public finance in accordance with the rule of law. In response to these issues, research explores and proposes a series of specific strategies to promote the legalization of public finance from the dimensions of establishing the principle of rule of law, improving the legal system framework, optimizing law enforcement operation mechanisms, and strengthening the supervision system, to provide theoretical support and practical basis for the reform of China's public finance system.
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.
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.
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.
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.
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.
区块链技术依托多节点协同验证及数据可追溯性特征，通过构建不可篡改的信用评估体系和自动化交易执行系统，能显著降低金融机构服务边际成本，同时提升风险控制效能。这种技术赋能的创新模式通过信息共享透明化机制有效缓解了金融资源配置的区域失衡问题，从而为银行业发展普惠性涉农金融产品体系开辟了具有可操作性的实践路径。本文将首先指出现有技术条件下开展农村普惠金融业务存在的挑战，接着分析区块链技术如何具体到农村金融的应用，最后探索区块链推进农村普惠金融发展的路径。Blockchain technology, leveraging its characteristics of decentralized node verification and traceable data, can significantly reduce the marginal costs of financial services for institutions while enhancing risk control capabilities by establishing a tamper-proof credit evaluation system and an automated transaction execution mechanism. This technology-driven innovation addresses regional imbalances in financial resource allocation through transparent information-sharing mechanisms, thereby providing a practical pathway for the banking industry to develop inclusive financial products tailored to rural areas. This paper first identifies the challenges of implementing inclusive finance in rural regions under existing technological conditions, then analyzes the specific applications of blockchain technology in rural finance, and finally explores pathways for advancing rural inclusive finance through blockchain.
With the government’s emphasis on the blockchain and supply chain industry and increased policy support, the field shows a bright future. Nonetheless, the traditional supply chain finance model faces numerous challenges. This paper aims to explore how blockchain technology can be utilized to mitigate and control credit risk in supply chain finance. It will also detail the principles and characteristics of blockchain technology, including its decentralized architecture, encryption algorithms, resistance to tampering, smart contract functionalities, and more. At the same time, this paper will also analyse the shortcomings of traditional supply chain finance. Distributed ledger technology is utilized through blockchain to ensure the transparency and traceability of information, while smart contracts optimize the credit execution and supervision process, playing a key role in preventing and controlling credit risks. The article concludes by proposing innovative strategies based on blockchain technology, including constructing a credit information sharing platform, improving the credit assessment model, and establishing a risk early warning and monitoring system, with the aim of improving the efficiency and credit level of supply chain management and further promoting the healthy development of supply chain finance.
Aiming at the current problems of cross-institutional mutual recognition, poor traceability and lack of trust in general education credit management, this study proposes a blockchain technology-based credit banking system construction scheme. The decentralised storage and sharing of credit data is achieved through the design of distributed ledger architecture, and smart contract technology is used to automate the execution of credit authentication, accumulation and conversion rules. Construct a standardised model of credit metadata, define the blockchain storage format of course code, credit hours, grades and other data fields, and apply the improved PBFT consensus mechanism to improve the transaction processing efficiency while ensuring data consistency. Zero-knowledge proof technology is used to realise privacy protection and ensure the security of students' sensitive information when it flows across institutions. Experimental results show that the system improves the efficiency of credit verification by 68% compared with the traditional centralised system.
This review paper presents an examination of Blockchain and Smart Contract platforms focusing on their uses in various industries and addressing their implementation challenges. A notable gap exists in current literature: there is no comprehensive review that encompasses blockchain applications, implementation challenges, smart contract development platforms, and publication trends. Our quantitative analysis of publication trends, examining 9,288 papers from IEEE Xplore and Springer databases between 2019 and 2024, provides insights into the trajectory of blockchain research across sectors. It examines platforms like Ethereum, which enables decentralized application development but faces scalability constraints, and Hyperledger Fabric, which offers robust enterprise solutions. The research explores how blockchain revolutionizes industries including healthcare through secure patient data management, supply chain through enhanced traceability, and education through verifiable credentials. This review synthesizes current trends in blockchain platforms and implementation challenges across diverse industries.
在社交媒体营销蓬勃发展的当下，社群经济作为一种新的商业模式正在受到企业的重视，小红书以“种草”模式成为极具影响力的社群营销平台。本研究以新4C理论为基础，深入剖析小红书“种草”社群营销策略。研究发现，小红书通过构建符号化场景、输出情感化内容、打造圈层化社群以及实现社交货币驱动的连接，形成独特营销模式。然而，目前存在场景失真、价值稀释、社群区隔和信任消解等问题。为实现范式升维，需构建真实性符号认证体系、植入信息熵平衡评估模型、建立赋权机制以及推动DAO协同生产范式转型。本研究旨在为小红书及相关从业者提供理论与实践指导，助力提升营销效果，推动行业健康发展。In the booming era of social media marketing, community economy, as an emerging business model, is gaining increasing attention from enterprises. rednote has become an influential community marketing platform with its “seed-planting” model. Based on the new 4C theory, this study delves into rednote’s “seed-planting” community marketing strategy. It is found that rednote has developed a unique marketing model by constructing symbolic scenarios, delivering emotional content, creating community circles, and establishing connections driven by social currency. However, there are existing problems such as scene distortion, value dilution, community segregation, and trust erosion. To achieve paradigm upgrading, it is necessary to build a realness symbol certification system, embed an information entropy balance evaluation model, establish an empowerment mechanism, and promote the transformation to a DAO (Decentralized Autonomous Organization) collaborative production paradigm. This study aims to provide theoretical and practical guidance for rednote and relevant practitioners, helping to enhance marketing effectiveness and promote the healthy development of the industry.
Blockchain technology has garnered widespread attention across various sectors such as finance, healthcare, and government services due to its decentralized, tamper-resistant, and traceable nature. However, the conflict between privacy protection and regulatory compliance has emerged as a key barrier to its further development. Zero-Knowledge Proof (ZKP), as a next-generation privacy-enhancing technology, offers unique advantages in achieving "verifiability without disclosure." This paper systematically reviews the core technologies of blockchain and existing privacy protection methods, providing an in-depth comparison of mainstream ZKP protocols (e.g., zk-SNARK, zk-STARK, and PLONK) in terms of efficiency, security, and generality. It highlights how ZKP has become a technological pillar for privacy-compliant blockchain systems. The paper then explores practical application models of ZKP in cross-domain scenarios such as healthcare, finance, e-government, and supply chains, and further analyzes potential mechanisms through which ZKP can fulfill regulatory requirements such as AML, KYC, and auditing while preserving privacy. Finally, it discusses current technical bottlenecks and future development trends, including the integration of ZKP with AI, secure hardware, and post-quantum cryptography, as well as strategic frameworks for building a scalable and regulation-friendly blockchain ecosystem.
To address many issues with conventional credit assessment techniques, this article suggests an international credit evaluation system for trading firms built on blockchain technology and a grey correlation model. Blockchain technology improves the transparency and security of data processing with its distributed ledger and anti-tamper feature. Combined with ring signature technology, users can maintain anonymity during the evaluation process, protecting user privacy and preventing information leakage. The grey correlation model can still provide effective evaluation results in the case of incomplete data or insufficient information by analyzing the correlation between indicators. This paper constructs an evaluation index system containing three main dimensions, namely corporate characteristics, corporate credit, and corporate finance, and verifies the effectiveness of the evaluation system by analyzing the data of five representative international enterprises during the period from 2013 to 2023. The results show that the system can accurately reveal the comprehensive strength and credit risk, provide valuable references for the international trading industry and regulators, and improve credit management and risk control ability in international trade. The research is not only of great significance in theory but also shows a broad prospect in practical application, providing a scientific and reliable evaluation tool for credit management of international trade enterprises.
In the context of the digital age, data privacy and security issues are increasingly prominent. Blockchain technology plays an important role in data sharing due to its transparency and immutability, but it also brings the risk of privacy leakage. Zero knowledge proof technology provides a solution for verifying data correctness without exposing data content, which is particularly important for blockchain as it can ensure the validity and compliance of transactions while protecting user privacy. Although zero knowledge proof is quite mature in theory, its application in blockchain systems still faces challenges such as computational efficiency, complexity of smart contracts, and system compatibility. This study aims to propose a privacy protection scheme that supports interactive zero knowledge proof by improving the homomorphic encryption Paillier algorithm, in order to enhance the privacy protection capability of blockchain systems and maintain system efficiency and security. The study will adopt an interdisciplinary approach, combining cryptography, computer science, and network security theory, to deeply analyze the application effect of zero knowledge proof technology in blockchain, explore its optimization space and applicability.
Blockchain technology, as an emerging distributed ledger technology, has gradually shown great potential in the field of information traceability due to its characteristics of decentralization, non-tamperability, and transparency. Through blockchain technology, the production, circulation, and consumption of products can be recorded and verified to ensure the authenticity and credibility of the data. This article reviews the application of blockchain in information traceability, focusing on analyzing its practice and effects in food safety, drug traceability, supply chain management, and energy industry traceability. Through a systematic review of existing literature, this article summarizes the research status, main results, and technical challenges of blockchain information traceability, points out its significant advantages in improving transparency and trust, and also discusses the implementation complexity, limitations in terms of cost, and performance. Finally, this article proposes future development trends, including multi-chain integration and the combination of blockchain with other technologies. The research in this article provides important reference and guidance for the further development of blockchain technology in information traceability.
While smart farming is becoming increasingly popular as a way to improve the efficiency and sustainability of agroecosystems and global food security, its vulnerability to cyber-attacks is rapidly increasing. A distributed reputation system can help detect and prevent malicious activities by tracking the reputation of IP addresses of devices, products, and entities in a smart farming system, thereby enhancing its security and trust. In this paper, we propose a blockchain-based reputation system for IP addresses in smart farms for real-time intrusion detection and prevention. The study uses the Ethereum blockchain smart contracts, Oracles, Intrusion Detection System (IDS), and a Proof-of-Reputation (PoR) consensus mechanism. The system was evaluated on two datasets, the Spamhaus Blocklist, and the Malware Domain List datasets. It achieved high accuracy, recall, and precision rates, F1 score, as well as low false positive and false negative rates. This shows that the proposed system has high potential to be an effective tool for improving malware detection and prevention in real-time, creating a trusted supply chain for a smart farming ecosystem against a wide range of attack types, including denial-of-service attacks, probe attacks, and user-to-root attacks.
With the rapid development of information technology, blockchain technology, as an innovative distributed ledger technology, has begun to be applied in many fields such as finance, supply chain management, and the Internet of Things. As an important part of economic management, accounting faces the challenge of transforming from traditional manual operation to intelligent and automated direction. The characteristics of blockchain technology, such as decentralization, data immutability and transparency, provide new solutions for the authenticity, accuracy and completeness of accounting information. Based on this, this paper mainly discusses and analyzes how to reform accounting teaching in colleges and universities through blockchain.
As the main power supply mode of new energy, photovoltaic system has the characteristics of wide distribution and scattered energy collection Traditional management methods cannot realize the effective processing of distributed energy storage. Therefore, finding an effective intelligent method is the focus of current research, and the design of blockchain smart contracts can theoretically realize the centralized processing of photovoltaic energy storage systems. In this paper, the blockchain smart contract system is taken as the research object, and the energy storage management of the photovoltaic system is quantified through mapping, so as to realize the massive quantitative processing of data. Then, the reduction function is used to differentially reduce the distributed functional energy storage system, complete the centralized management of energy storage, and simplify the unnecessary data. Finally, combined with the hybrid energy storage situation, the key indicators in the data are mined, and the completion rate of the contract and the stability analysis of energy storage management are calculated. The results show that blockchain can mine the characteristics of hybrid energy storage, reduce the impact of distributed features on energy storage, improve the energy storage efficiency by 20%, and make the energy storage stability reach more than 90%. At the same time, the completion rate of smart energy storage contracts can be enhanced, the fitting degree can reach 90%, and the grid connection with the thermal grid can be effectively connected, the utilization rate of distributed energy resources will reach 85%, and the cost saving rate will be increased by 10%. Therefore, blockchain can solve the problem of hybrid energy storage in integrated systems, improve the completion rate of smart contracts, and promote the development of new energy.
This paper focuses on the empirical analysis of personal credit assessment of online lending platform from the perspective of personal credit, and the security of credit privacy data can be guaranteed by blockchain classification model. This paper is mainly based on the chain security encryption operation and decentralized data classifier training model, blockchain storage credit data between the ecological nodes through the transmission of transaction decision data return beacons, to achieve the data retrieval, use, confirm the rights and rewards, and at the same time the use of clustering learning algorithms combined with the decentralized training model to build a unique algorithmic training system, through the machine learning to backtrack all the transaction records, the sharing of the After data processing of credit data information, the fiducial correction fitting model using feedback from data samples, thus opening the modeling method of blockchain and clustering algorithm combined application in the field of credit. In the final analysis, the research on the application of blockchain technology in the credit collection industry should not stop at guaranteeing the security and traceability of data, but rather apply the "pre-credit review", "credit monitoring" and "post-credit management" to the entire credit collection industry. "Instead, it should be applied to the entire credit collection process, and used to guide Internet credit bureaus in their daily credit collection activities. Blockchain technology mainly solves the problem of credit trust and security, for this reason, it is necessary to construct a complete set of methods for analyzing, verifying and measuring Internet credit data. This paper combines the blockchain and the clustering algorithm in machine learning, and empirically analyzes the credit data of Internet consumer financial institutions under this framework.