Ateeq Ur Rehman, Nargis Tariq, Mian Ahmad Jan, Fazlullah Khan · 6 authors
In recent years, the healthcare industry has undergone a digital transformation, making patient data publicly available and accessible. Healthcare units make a portion of the data public while keeping the rest private, necessitating various mechanisms for security and privacy. Blockchain technology has been widely adopted in the healthcare sector to secure data transactions. However, public blockchains face challenges in scalability and privacy, whereas private blockchains struggle with centralization, interoperability, and complexity. To address these challenges, we propose an Internet of Medical Things (IoMT)-based hybrid blockchain architecture. The proposed architecture combines the decentralized Ethereum and the centralized Hyperledger Fabric blockchain (Eth-Fab) using SQLite to leverage Ethereum smart contracts with the Hyperledger permission model. Moreover, we introduce access control strategies to enhance patient data authentication and authorization. We have employed machine learning algorithms to assist healthcare practitioners in accurately detecting diseases and making time-efficient decisions. Additionally, we modeled the proposed architecture using the M/M/1 queuing model and derived closed-form expressions for latency, throughput, and server utilization. The validity of these expressions was verified through Monte Carlo simulations. The results demonstrate that higher service times (block generation) yield better outcomes in terms of latency, throughput, and utilization, regardless of the arrival time, i.e., transactions in the mining pool.
As the volume of healthcare and medical data increases from diverse sources, real-world scenarios involving data sharing and collaboration have certain challenges, including the risk of privacy leakage, difficulty in data fusion, low reliability of data storage, low effectiveness of data sharing, etc. To guarantee the service quality of data collaboration, this paper presents a privacy-preserving Healthcare and Medical Data Collaboration Service System combining Blockchain with Federated Learning, termed FL-HMChain. This system is composed of three layers: Data extraction and storage, data management, and data application. Focusing on healthcare and medical data, a healthcare and medical blockchain is constructed to realize data storage, transfer, processing, and access with security, real-time, reliability, and integrity. An improved master node selection consensus mechanism is presented to detect and prevent dishonest behavior, ensuring the overall reliability and trustworthiness of the collaborative model training process. Furthermore, healthcare and medical data collaboration services in real-world scenarios have been discussed and developed. To further validate the performance of FL-HMChain, a Convolutional Neural Network-based Federated Learning (FL-CNN-HMChain) model is investigated for medical image identification. This model achieves better performance compared to the baseline Convolutional Neural Network (CNN), having an average improvement of 4.7% on Area Under Curve (AUC) and 7% on Accuracy (ACC), respectively. Furthermore, the probability of privacy leakage can be effectively reduced by the blockchain-based parameter transfer mechanism in federated learning between local and global models.
The metaverse, a collective virtual shared space combining virtual reality, augmented reality, and the internet, presents a new frontier for entrepreneurship and disruptive business opportunities. This paper conducts an in-depth exploration of the metaverse landscape, analyzing the evolution of virtual worlds, major metaverse platforms, and user adoption trends. It identifies and evaluates various entrepreneurial opportunities within the metaverse ecosystem, including virtual real estate development and digital asset trading, virtual commerce and e-commerce, virtual experiences and entertainment, as well as decentralized finance (DeFi) applications leveraging blockchain technology. While the metaverse offers substantial prospects, the paper critically examines the challenges and risks associated with metaverse entrepreneurship. These encompass legal and regulatory complexities surrounding intellectual property, privacy, and taxation; technical hurdles such as interoperability, scalability, and cybersecurity; economic uncertainties regarding volatile asset markets and sustainable revenue models; and social and ethical implications related to potential addiction, inclusivity, and environmental impact. The paper further outlines strategic approaches and best practices for entrepreneurs seeking to navigate the metaverse successfully. These include identifying viable business opportunities, building strong virtual brand identities, leveraging emerging technologies like augmented reality (AR), artificial intelligence (AI), and blockchain, fostering community engagement, pursuing strategic collaborations, and embracing continuous innovation. Through a synthesis of existing literature and case studies, the paper offers actionable recommendations for entrepreneurs and policymakers to foster a responsible and sustainable metaverse ecosystem. It acknowledges limitations and suggests avenues for future research, such as industry-specific studies, ethical frameworks, and longitudinal investigations into the metaverse's societal impacts. Ultimately, this comprehensive analysis aims to provide a thorough understanding of the metaverse's potential for entrepreneurship, while equipping stakeholders with insights and strategies to navigate the opportunities and challenges within this rapidly evolving virtual realm.
Intelligent lighting systems achieve high energy efficiency through precise control and serve as vital tools for reducing carbon emissions, providing essential data for carbon trading. However, data exchange between the lighting system and the carbon trading system presents several challenges. For instance, data may be maliciously tampered with, and frequent unauthorized access threatens the normal operation of carbon trading. Therefore, this paper proposes a security framework for intelligent lighting systems based on blockchain technology. The framework utilizes a dual-chain structure of Hyperledger Fabric and Ethereum to address the issues of blockchain storage expansion and transaction efficiency, employing smart contracts to ensure the effective processing of lighting data. The security requirements for intelligent lighting data are thoroughly studied and analyzed. Additionally, this paper presents a key distribution scheme based on the RSA encryption algorithm to ensure trusted access control within the system. Through detailed analysis and practical verification of the scheme's security and performance, the framework not only effectively prevents data tampering but also ensures data authenticity and the smooth operation of the system during carbon trading, providing robust support for the security and privacy protection of intelligent lighting systems.
Abstract As an important cornerstone of future digital civilization, smart contracts are being increasingly used in blockchain finance in innovative practice, and whether smart contracts have legal effect has become a question that academia must answer. This paper discusses the legal impact and application of smart contracts under the contract layer in the blockchain architecture, with a vision of an administrative legal system. Based on the operation principle of smart contracts, a method for detecting smart contract vulnerabilities that combines Glove word embedding and the Shapelet-Transform algorithm is proposed to improve data security during the fulfillment process. Finally, the smart contract model constructed in this paper is applied to the supply chain of agricultural products, and the legal effects of the smart contract are analyzed using practical examples. The transaction volume of unqualified agricultural products decreased from 19.4545 to 13.4655, which is lower than the production volume. The credit index of the smart contract model has increased, resulting in a shortened node performance time from 0.25s to 0.2s.
Ivan Ivanovich Kiryushin, Igor' Petrovich Ivanov, Viktor Vladimirovich Timofeev, D Yu Zhmurko
This article explores the possibilities of using blockchain technology in police work. Examples of the use of blockchain in various areas of police activity, such as personal data management, control of drug trafficking and other prohibited substances, traffic monitoring and the fight against cybercrime, are considered. The authors note that thanks to the storage of data in the blockchain, it becomes possible to increase the protection of the confidentiality of personal information, ensure transparency and efficiency of police work, as well as prevent fraud and corruption. The conclusion of the article emphasizes that the use of blockchain can improve the work of the police and ensure greater security of citizens. Distributed ledger technology, or blockchain as a service (BaaS) is indeed a relatively new product on the market that allows you to provide blockchain services for corporate clients. This solution allows you to use more reliable and secure methods of data processing and transaction management within the organization. All these economic effects can lead to a reduction in costs and an increase in the efficiency of the police. In general, the use of blockchain technology in the police can have a number of advantages, such as increasing transparency and accountability, reducing data processing time and combating data falsification. However, it is necessary to take into account some risks, such as the possibility of data privacy violations, as well as difficulties in integrating with existing systems and training personnel. In general, the introduction of blockchain technology into the police requires careful analysis and an approach that takes into account all aspects of the use of technology and its impact on the organization.
Open access
Advanced Technologies in Various Fields
Legal, Health, Environmental and COVID-19 Challenges
In the process of technology promoting the transformation towards digitalization, both blockchain technology and supply chain finance emerge as hot topics. Blockchain technology, characterized by decentralization, immutability, transparency, security, and programmability, addresses the risk consider
Shahabeddin Abhari, Plinio Pelegrini Morita, Pedro Augusto Da Silva E. Souza Miranda, Ali Garavand · 6 authors
Introduction: Non-Fungible Tokens (NFTs) are digital assets that are verified using blockchain technology to ensure authenticity and ownership. NFTs have the potential to revolutionize healthcare by addressing various issues in the industry. Method: The goal of this study was to identify the applications of NFTs in healthcare. Our scoping review was conducted in 2023. We searched the Scopus, IEEE, PubMed, Web of Science, Science Direct, and Cochrane scientific databases using related keywords. The article selection process was based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Results: After applying inclusion and exclusion criteria, a total of 13 articles were chosen. Then extracted data was summarized and reported. The most common application of NFTs in healthcare was found to be in health data management with 46% frequency, followed by supply chain management with 31% frequency. Furthermore, Ethereum is the main blockchain platform that is applied in NFTs in healthcare with 70%. Discussion: The findings from this review indicate that the NFTs that are currently used in healthcare could transform it. Also, it appears that researchers have not yet investigated the numerous potentials uses of NFTs in the healthcare field, which could be utilized in the future.
Mazin Abed Mohammed, Abdullah Lakhan, Karrar Hameed Abdulkareem, Mohd Khanapi Abd Ghani · 9 authors
INTRODUCTION: The Industrial Internet of Water Things (IIoWT) has recently emerged as a leading architecture for efficient water distribution in smart cities. Its primary purpose is to ensure high-quality drinking water for various institutions and households. However, existing IIoWT architecture has many challenges. One of the paramount challenges in achieving data standardization and data fusion across multiple monitoring institutions responsible for assessing water quality and quantity. OBJECTIVE: This paper introduces the Industrial Internet of Water Things System for Data Standardization based on Blockchain and Digital Twin Technology. The main objective of this study is to design a new IIoWT architecture where data standardization, interoperability, and data security among different water institutions must be met. METHODS: We devise the digital twin-enabled cross-platform environment using the Message Queuing Telemetry Transport (MQTT) protocol to achieve seamless interoperability in heterogeneous computing. In water management, we encounter different types of data from various sensors. Therefore, we propose a CNN-LSTM and blockchain data transactional (BCDT) scheme for processing valid data across different nodes. RESULTS: Through simulation results, we demonstrate that the proposed IIoWT architecture significantly reduces processing time while improving the accuracy of data standardization within the water distribution management system. CONCLUSION: Overall, this paper presents a comprehensive approach to tackle the challenges of data standardization and security in the IIoWT architecture.
We consider the problem of researcher output identification and its verification.Nowadays, researcher outputs verification is a challenging problem faced by institutions that want, for example, employ such a researcher.Usually, there is no verification, and the aforementioned institutions rely on trust that the received documents are authentic.Our solution is a based on blockchain technology, a public ledger with smart contracts, that is the root of emerging web3.We use the public wallet address as the researcher identification number and the wallet as the store of all researcher credentials.This paper presents ERC-721 standard-based solution and addresses the conference certification case.The solution proposed in this paper addresses two challenges that arise in collecting and verifying data on research output for managing, monitoring, and evaluating purposes.We show that the public wallet address can be successfully used as the researcher identification number, and the wallet can be used as a vault of all the researcher credentials.
The maritime industry has faced several challenges related to inefficiency, fraud, and compliance in both marine engineering and shipping logistics. Blockchain technology, with its decentralized and immutable nature, offers a transformative solution for enhancing transparency, security, and operational efficiency across these sectors. This paper explores the integration of blockchain technology into marine engineering practices, such as vessel maintenance, and shipping logistics, including cargo tracking and document management. Through blockchain’s distributed ledger system, stakeholders can ensure real-time, transparent data sharing, reducing human errors and delays while improving the security of maritime transactions. This research evaluates current blockchain applications, identifies barriers to adoption, and discusses the potential of blockchain to drive future innovations in maritime operations.
With the continuous expansion of educational view, blockchain technology develops into the cutting-edge applied science and technology of educational information construction. Blockchain technology can effectively solve such problems as information security and trust crisis in the current application of big data in online education by virtue of its characteristics of decentralization, traceability, multi-party consensus mechanism, and high trust. Blockchain technology is conducive to protecting online educational resources, strengthening the transparency of online teaching resources, simplifying the copyright transaction process, and thus enhancing the scientific and technological innovation ability of teachers. Studies regarding the blockchain technology application in education were analyzed, and the influences of the four aspects of the blockchain technology application in education on online teaching resource sharing were explored. Results showed that the Cronbach α coefficient of the questionnaire designed in this research was 0.856, and the KMO value was 0.859, indicating its good reliability and validity. The cross-institutional learning record storage space, learning certificate management mechanism, and collaboratively developed educational ecosystem of the blockchain technology application in education obviously promoted online teaching resource sharing at a significance level of 5%. The results are important reference values for strengthening the integration of educational resources under blockchain technology, improving the application mechanism of online digital educational resources, and improving the accurate service quality of online educational resources.
Decentralization, autonomy, integrity, immutability, verification, fault-tolerance, anonymity, auditability, and transparency are desirable characteristics of blockchain technology. Blockchain technology originated from Bitcoin which is one of the applications of digital currency. From a financial point of view, it is a distributed data storage system. Therefore, it is very important to analyze the current research status in this field, and further sort out the deficiencies of current research and future development direction. This article describes the definition of blockchain technology and hash algorithm first. Besides, it also shows some applications including supply chain finance, digital ticket, and digital currency in the financial field. Privacy and risk are the key points to worry about. This article also introduces how to protect user privacy in supply chain finance. This article analyzes how blockchain effectively protects user privacy from banks and non-banks. It is difficult to take into account all three features of blockchain: security, scalability, and decentralization. However, the integration of finance and technology is an increasingly strong trend.
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.
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.
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.