Through the sharing of high-quality educational resources in colleges and universities, various colleges and universities have carried out active and effective exchanges in teaching resources, avoiding the duplication of larger educational resources, and improving the academic and career development of teachers and students. The construction of a blockchain-based regional higher education information resource sharing model can solve the problems of scattered teaching resources and duplicate construction of teaching resources, difficulties to ensure the security of digital education resources, high operating costs of platforms, and urgent protection of intellectual property rights of resources. Most of the existing solutions rely on third-party certificate issuing centers or use a single key to encrypt the data flow of education information resources, which has hidden dangers of leakage of privacy information such as intellectual property rights, copyrights, confidential information of resources, other key information, and operation records. Therefore, this paper studies the regional higher education information resource sharing model based on blockchain and designs the data protection protocol of higher education information resources and its resource transaction relationship protection scheme. It introduces the blockchain-based regional higher education information resource sharing model mainly from three aspects: blinding the identity of authorized resource recipients, resource initiators publishing resource transactions, and authorized resource recipients publishing resource transactions. Experimental results verify the effectiveness of the proposed model.
Abstract In view of the node security risks and key management vulnerabilities in heterogeneous sensor networks, a key management protocol for heterogeneous sensor networks based on zero trust security and chaotic neural networks (KMPHSN-ZTSCNN) was proposed. Taking advantages of the decomposition difficulty of singular matrix and chaotic classification characteristics of Hopfield overload chaotic neural network, the node registration and authentication of sensor network were achieved by blockchain and zero-knowledge proof. The channel state information (CSI) and the adjustable mathematical function were relied on to generate a dynamically changing key to complete continuous verification and achieve zero trust security authentications, thus ensuring data security. The protocol can dynamically allocate different keyspace sizes according to the security level of the group, the storage capacity if the nodeand computing capacity and can adapt to the asymmetric structure of heterogeneous sensor networks. Theoretical proof and experimental performance analysis results show that the protocol is feasible and can meet the security requirements of heterogeneous sensor networks.
The currently researched trusted data storage encryption methods for metering assets store too little data and have long encryption time delays. In order to solve the above problems, the trusted data storage encryption method for metering assets based on blockchain technology is proposed. blockchain technology can carry out the underlying network data support for the trusted data storage encryption of metering assets, and its data validation technology can be used for metering asset data block processing, and the data analysis is used to achieve storage encryption by comparing and validating the asset measurement results in the Ethernet virtual contract through each node within the blockchain node zone. This paper mainly applies blockchain technology in data storage management system, briefly analyzes the underlying logic of blockchain technology and its application in data storage management system, the core of the system is the storage of information and data, with features such as "unforgeable", "traceable", "open and transparent" and "collective maintenance". The core of the system is the storage of information and data, with features such as "unforgeable", "traceable", "open and transparent", "collective maintenance", etc. Finally, we show the application results of the technology in the system.
Arash Heidari, Nima Jafari Navimipour, Mehmet Ünal
The Internet of Drones (IoD) is built on the Internet of Things (IoT) by replacing “Things” with “Drones” while retaining incomparable features. Because of its vital applications, IoD technologies have attracted much attention in recent years. Nevertheless, gaining the necessary degree of public acceptability of IoD without demonstrating safety and security for human life is exceedingly difficult. In addition, intrusion detection systems (IDSs) in IoD confront several obstacles because of the dynamic network architecture, particularly in balancing detection accuracy and efficiency. To increase the performance of the IoD network, we proposed a blockchain-based radial basis function neural networks (RBFNNs) model in this article. The proposed method can improve data integrity and storage for smart decision-making across different IoDs. We discussed the usage of blockchain to create decentralized predictive analytics and a model for effectively applying and sharing deep learning (DL) methods in a decentralized fashion. We also assessed the model using a variety of data sets to demonstrate the viability and efficacy of implementing the blockchain-based DL technique in IoD contexts. The findings showed that the suggested model is an excellent option for developing classifiers while adhering to the constraints placed by network intrusion detection. Furthermore, the proposed model can outperform the cutting-edge methods in terms of specificity, F1, recall, precision, and accuracy.
This exploration conducts innovative research on music education and teaching based on blockchain technology under AI and puts forward the general view of blockchain technology and its potential to contribute to future development. The essence, characteristics and development process of blockchain technology are discussed. Meanwhile, the thinking on the development of 'blockchain + education' is put forward, and the digital platform application of blockchain technology in music education and teaching is given. As the basis of system development, requirement analysis plays a crucial part in the subsequent system design and implementation. Analysing requirements can help people locate software functions more accurately and clearly. This exploration takes blockchain as the underlying technology support and relies on Fabric architecture to explore its application in digital education resource management.
Olawole Akomolafe, Babajide Oluwaseun Olaogun, Michael Olumuyiwa Adesuyi, Victor Ukara Ndukwe · 5 authors
Effective liquidity management is critical for the reliability and efficiency of international remittance and cross-border payment systems. Delays, settlement failures, and currency conversion inefficiencies can significantly impact SMEs, corporates, and individual remitters, leading to operational disruptions, increased costs, and reduced financial inclusion. This study proposes a Predictive AI Model for Remittance Liquidity Optimization, designed to forecast liquidity requirements in real time, optimize fund allocation, and enhance the overall performance of international payment networks. The model integrates multi-source data, including historical transaction volumes, foreign exchange (FX) rates, settlement schedules, and network congestion metrics, to generate predictive insights and automated liquidity management recommendations. The conceptual framework of the model incorporates advanced machine learning and time-series forecasting techniques, combined with an optimization engine that dynamically allocates available funds to minimize delays, reduce transaction costs, and manage FX risks. Real-time anomaly detection mechanisms identify potential liquidity shortfalls, network congestion, or settlement failures, triggering alerts and corrective actions. The model also includes integration layers with banking platforms, fintech providers, and remittance networks, enabling seamless execution of liquidity redistribution and settlement optimization. Predictive outputs are visualized through interactive dashboards, supporting operators in decision-making and ensuring transparency in fund flows. By leveraging AI-driven forecasting and optimization, the model reduces settlement delays, improves FX efficiency, and enhances operational reliability across multi-currency, multi-jurisdictional payment corridors. Its applications extend to SMEs, corporate treasuries, and high-volume remittance corridors, promoting financial inclusion and operational continuity. Future extensions include adaptive learning algorithms for self-optimizing liquidity strategies, integration with distributed ledger technologies for real-time settlements, and expansion to multi-party global supply chains. Ultimately, this predictive AI model provides a scalable, intelligent solution for enhancing liquidity management in international payment systems, fostering greater efficiency, resilience, and transparency in global financial networks.
To discuss the control of financial risks (FRs) under blockchain (BC) and improve network information security (NIS) and data security, edge computing (EC) combined with BC is proposed to control the risks of the big data (BD) financial system. Firstly, the BC-based financial system is introduced, and the characteristics of BC such as decentralization, tamper-resistant, and smart contract are analyzed. Secondly, the development status of NIS and the characteristics of marginal computing are explained, and the control model of NIS is established. Then, EC is used to encrypt the identity authentication system to ensure data security, and the BC-based FR evaluation model is established. Finally, a questionnaire is designed regarding the NIS model, and the results are analyzed. A simulation experiment is conducted regarding the index evaluation of the BC-based FR evaluation model. The experimental results indicate that network personnel control, environment, and technology have positive effects on NIS, and the impact factors are 0.26, 0.24, and 0.33, respectively.
Blockchain is a distributed ledger technology with IOT, which helps to make machine-to-machine interaction possible. So, we can also say that it is a system that records information in such a way that makes it difficult to change, cheat or hack. Smart healthcare needs blockchain technology to store the digital records of patient health. Hence to make healthcare system more secure and robust against tempering and theft of electronic health records (EHR).
Due to financing difficulties, NABE are hard to make progress. The main reasons are the information asymmetry between the financing parties, the lack of effective collateral and their own limitations. This paper will innovate the traditional financing mode by using the characteristics of Blockchain that is not easy to tamper with and decentralized, as well as the powerful functions of data mining, analysis and processing of Big Data technology, so as to establish a trust mechanism to solve the financing problems of new agricultural financial entities.
Abstract Blockchain is a well-known prominent technology that has gotten a lot of interest beyond the financial industry, attracting researchers and practitioners from numerous businesses and fields. Specific uses of blockchain in supply chain management (SCM) are addressed in business practice. By combining two perspectives on blockchain in SCM, this study provides comprehensive knowledge in this field using a bibliometric approach. We will explore the worldwide research trend in related topic areas. By collecting data from the Web of Science, we collected 400 articles related to our research topic from 2016 until early 2021. We eliminated research in the form of technical reports, editorials, comments, and consultancy articles to maintain the quality of the data gathering. VOSviewer is used to create visualization maps based on text and bibliographic information. The examination uncovered helpful information, such as annual publishing and citation patterns, the top research topic, the top authors, and the most supporting funding organizations in this field.
T. Manikandan, Shajahan Basheer, Shitharth Selvarajan, Sara A. Althubiti · 7 authors
There can be many inherent issues in the process of managing cloud infrastructure and the platform of the cloud. The platform of the cloud manages cloud software and legality issues in making contracts. The platform also handles the process of managing cloud software services and legal contract-based segmentation. In this paper, we tackle these issues directly with some feasible solutions. For these constraints, the Averaged One-Dependence Estimators (AODE) classifier and the SELECT Applicable Only to Parallel Server (SELECT-APSL ASA) method are proposed to separate the data related to the place. ASA is made up of the AODE and SELECT Applicable Only to Parallel Server. The AODE classifier is used to separate the data from smart city data based on the hybrid data obfuscation technique. The data from the hybrid data obfuscation technique manages 50% of the raw data, and 50% of hospital data is masked using the proposed transmission. The analysis of energy consumption before the cryptosystem shows the total packet delivered by about 71.66% compared with existing algorithms. The analysis of energy consumption after cryptosystem assumption shows 47.34% consumption, compared to existing state-of-the-art algorithms. The average energy consumption before data obfuscation decreased by 2.47%, and the average energy consumption after data obfuscation was reduced by 9.90%. The analysis of the makespan time before data obfuscation decreased by 33.71%. Compared to existing state-of-the-art algorithms, the study of makespan time after data obfuscation decreased by 1.3%. These impressive results show the strength of our methodology.
Arash Heidari, Mohammad Ali Jabraeil Jamali, Nima Jafari Navimipour, Shahin Akbarpour
The number of Internet of Things (IoT)-related innovations has recently increased exponentially, with numerous IoT objects being invented one after the other. Where and how many resources can be transferred to carry out tasks or applications is known as computation offloading. Transferring resource-intensive computational tasks to a different external device in the network, such as a cloud, fog, or edge platform, is the strategy used in the IoT environment. Besides, offloading is one of the key technological enablers of the IoT, as it helps overcome the resource limitations of individual objects. One of the major shortcomings of previous research is the lack of an integrated offloading framework that can operate in an offline/online environment while preserving security. This paper offers a new deep Q-learning approach to address the IoT-edge offloading enabled blockchain problem using the Markov Decision Process (MDP). There is a substantial gap in the secure online/offline offloading systems in terms of security, and no work has been published in this arena thus far. This system can be used online and offline while maintaining privacy and security. The proposed method employs the Post Decision State (PDS) mechanism in online mode. Additionally, we integrate edge/cloud platforms into IoT blockchain-enabled networks to encourage the computational potential of IoT devices. This system can enable safe and secure cloud/edge/IoT offloading by employing blockchain. In this system, the master controller, offloading decision, block size, and processing nodes may be dynamically chosen and changed to reduce device energy consumption and cost. TensorFlow and Cooja’s simulation results demonstrated that the method could dramatically boost system efficiency relative to existing schemes. The findings showed that the method beats four benchmarks in terms of cost by 6.6%, computational overhead by 7.1%, energy use by 7.9%, task failure rate by 6.2%, and latency by 5.5% on average.
With the rapid development of communication technology and automation technology, sensors are becoming more and more intelligent. This study proposes an environmental accounting system model based on artificial intelligence blockchain and embedded sensors. A high-precision sensor system based on embedded technology is first built, which not only avoids the shortcomings of analog data transmission, but also has high performance and price advantages. At the same time, it can be easily combined into a simple sensor network, and array measurement can be realized through the development of blockchain technology. However, the current blockchain system has the disadvantage of storage limitation. The problem is particularly serious when a large amount of data needs to be stored in the blockchain, especially when the blockchain is combined with big data. As a comprehensive field of accounting, ecology, and environmental science, environmental accounting has made great contributions to sustainable development in the field of accounting. The theoretical research in the field of environmental accounting in China started late, and a unified environmental accounting system has not actually been established. Under the conditions of immature theoretical and policy basis, companies have almost no actual surveys on environmental accounting. The characteristics of blockchain technology, such as decentralization, transparency, and changes in information unavailability, can fully solve the problem that the current accounting information system cannot consolidate transaction information and the accounting process. The reliability assurance mechanism of the accounting information system based on blockchain technology can greatly ensure the reliability of the accounting information system, effectively suppress accounting fraud, and improve the transparency of information.
The Metaverse is an innovative world grasping the attention of many users seeking this trend. With the trending use of Blockchain technology emerging in client-based applications, there has been a call for the empowerment of Metaverse applications through the combination of Blockchain and Artificial Intelligence. This research paper aims to propose strategies for addressing the security concerns and the user-friendliness of Metaverse applications by fusing Blockchain technology with Machine Learning concepts like Linear Regression, Artificial Neural Networks, Deep Learning, and Recommender Systems. The first proposed strategy aims to enhance security and predict malicious attacks on Blockchain user transactions in Metaverse worlds through Linear Regression and Artificial Neural Networks. The second proposed strategy pursues the creation of a Content-Based Filtering Recommendation System of Blockchain assets for Metaverse users to purchase. The expected outcome will result in a more secure and intelligent Metaverse world for user participation.
In order to explore the public administration and resource allocation based on blockchain and structured occupational therapy, this paper takes the public affairs in the prevention and control of the Corona Virus Disease 2019 (COVID-19) epidemic as an example to conduct research. On the basis of summarizing and analyzing the previous published literatures, this study expounded the research status and significance of public administration and resource allocations; elaborated the development background, current status and future challenges of blockchain, and structured occupational therapy; introduced the methods and principles of data quality collaboration model and multiparty collaboration standard management; analyzed the case background of public administration and resource allocation in the prevention and control of the COVID-19 epidemic; discussed the public administration mechanism based on blockchain and structured occupational therapy; established a resource allocation method based on blockchain and structured occupational therapy; fathomed the role of the distributed ledger established by blockchain to increase the information symmetry of public administration activities; proposed a blockchain-established special machine trust for resource allocation; and finally, anatomized the data security sharing and access control mechanism based on blockchain and structured occupational therapy. The research results show that the public administration and resource allocation in this paper can effectively realize the data integration of the whole process and all departments and show the whole data and realize the traceability of the whole process. The blockchain revolutionizes the hierarchical leadership method of traditional resource allocation, shortens the distance between superiors and subordinates, makes information dissemination more fluent, and handles things more efficiently, making resource allocation ultimately form a flatter organization structure. In the original trust system of resource allocation, the blockchain and structured occupational therapy realizes the reconstruction of the trust system by preventing information tampering, using information encryption technology, and using information traceability technology. The results of this paper provide a reference for further research on the public administration and resource allocation based on blockchain and structured occupational therapy.
To build an agricultural product network marketing system in the era of e-commerce, it is necessary for agricultural product business enterprises or farmers to recognize the benefits of using e-commerce to market agricultural products and face up to its influencing factors and to build a support system, application system, and guarantee system with the support of the government to promote agricultural product e-commerce marketing to obtain healthy development. In this study, we study the construction mode of e-commerce agricultural product online marketing system based on the end of blockchain and improved genetic algorithm. This study adopts the design idea of coalition chain and proposes a multichain agricultural product trading information blockchain application technology including agricultural product trading information chain, user information chain, and agricultural product information chain. The agricultural product information chain provides detailed information of agricultural products and ensures the traceability and non-tamperability of the information. It automatically divides the profits of transactions through smart contracts to improve execution efficiency and reduce transaction costs and finally establishes a transparent, efficient, and applicable blockchain architecture for agricultural product transactions.
This study focuses on the financing difficulties of small and medium enterprises (SMEs) in China to study the application of blockchain technology in developing the real economy. Deep learning neural network is applied to the vulnerability analysis and detection of smart contracts in blockchain technology by analyzing the connotation of blockchain technology and deep learning. A multiparty joint financial service platform based on blockchain technology is established to help SMEs financing institutions reduce transaction costs, thereby helping them reduce loan interest rates. Finally, Jiangsu Province is studied as a pilot unit. The results show that the Recall and F-score of Bidirectional Neural Network for smart contract vulnerability detection are higher than those of the original neural network. The Recall rate and F-score value of the Wide and Deep model are up to 96.2% and 94.7%, which are higher than those of other vulnerability detection schemes. The Timestamp vulnerability has the highest Recall rate, 94.2%, which can rely on a large amount of valid data to improve detection efficiency. The distribution of financing needs of SMEs in Jiangsu Province from 2020 to 2021 shows that the loan number of SMEs is generally not high. Still, financial institutions and enterprises must spend the same transaction cost. After a technology company in Nanjing made a loan through a blockchain financial service platform, its financing cost decreased by 0.5331%. Blockchain technology has played a great role in the financing process of SMEs, reducing intermediate links and credit costs, and promoting the development of SMEs and the real economy.
Balaji Ramkumar Rajagopal, B Anjanadevi, Madiha Tahreem, Sonu Kumar · 6 authors
In the modern decade, utilizing advances in emerging technologies is essential in operating automation in the workplace. Blockchain constructs a distributed point-to-point system that is capable of balancing the financial economy. In the automation process, the rapid adoption of blockchain technology has made both public and social services flexible. In order to achieve the objectives and goals of an individual organization, all the advancements of Artificial Intelligence (AI) bring both opportunities and challenges. This paper provides a competitive literature review regarding the factors related to blockchain technology and artificial intelligence to operate the parking system in automation service by mitigating its potential issues. In this study, the researcher has discussed blockchain security enhancement solutions by adopting AI to develop several blockchain transportation systems. The purpose of this research article is to investigate the impact of blockchain technology and artificial intelligence on the automation service. The researcher has adopted a secondary data collection method to gather relevant data and information related to the research topic to make the study more valuable and authentic. Similarly, the collected resources used quantitative methods to malaise the data to be understandable. Moreover, this study will help the readers to understand the appropriate effectiveness of AI to control automation activity. In this research article, the description of the Industrial Revolution and its benefits are also described. This research article focuses on the open issues of automation in the workplace that can be controlled by artificial intelligence and blockchain technology.
This study aims to solve the problem that the traditional online foreign language teaching system focuses on function development, ignoring system security, and has certain risks. An online foreign language education system is designed and developed based on the blockchain technology. First, the blockchain technology and key technologies of system design are described in detail. Second, the overall technical architecture of the system, functional modules, and business logic of each module are designed. Finally, the basic performance of the system is tested. The results show that the system can realize the user's unrestricted office work and zero maintenance of the system. The separation of presentation logic and business logic facilitates the development and maintenance of the system. The system mainly includes six functional modules: user management, course management, course order, course study, course certificate, and credit authentication. These modules are guaranteed for daily teaching use. The event processing success rate of the six functional modules of the system is greater than 99%, and the processing success rate is relatively high. The central processing unit (CPU) usage and memory usage are both below 30%. The host throughput of the six major modules is greater than 100 times/s when processing services. The average response time on the terminal side is maintained below 0.5 s. The average response time of business-side processing is maintained below 0.4 s, which is in line with the standard. The event processing success rate of the constructed system is 10.75% higher than that of other systems, and the average response time, CPU usage, and memory usage are 53.38%, 51.49%, and 50% lower than other systems, respectively. Therefore, the proposed system has better performance. To sum up, the designed system has excellent throughput, event processing capability, response speed, and low CPU and memory occupancy when processing business and is suitable for promotion and use in foreign language online education in colleges and universities. The use of the proposed system can improve its overall teaching efficiency and quality. The purpose is to provide important technical support for the improvement of the security of the online foreign language teaching system.
Based on blockchain technology,Ethereum Solidity smart contract as a computer protocol is designed to spread,verify,or execute contracts in an informative way,and it provides a foundation for various distributed application services.Although implemented for less than six years,its security problems have frequently broken out and caused substantial financial losses,which attracts more attention in the security inspection research.This paper firstly introduces some specific mechanisms and operating principles of smart contracts based on Ethereum related techniques,and analyzes some smart contract vulnerabilities occurring frequently and deriving from the characteristics of smart contracts.Then,this paper explains the traditional mainstream smart contract vulnerability detecting tools in terms of symbolic execution,fuzzing,formal verification,and taint analysis.In addition,in order to cope with the endless new vulnerabilities and the need to improve the efficiency of detection,vulnerabilities detection based on machine learning in recent years is classified and summarized according to the various ways of problem transformation in three perspectives including text processing,non-Euclidean graph and standard image.Finally,this paper proposes to formulate more extensive and accurate standardized information database and measurement indicators towards the insufficiency of the detection methods in two directions.