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The agriculture sector stands as one of the most significant sectors sustaining 70 percent of the world’s population. In this sector, the supply consists of a series of interconnected stages, spanning from farming through production to the final delivery of goods to the end customer. A lack of transparency within the supply chain presents the largest gap between suppliers and retailers, such as not ensuring the true value of products or services. This research introduces AgroChain, a Blockchain-based system that is designed to support the Agricultural Supply Chain (ASC) process. For scalability purposes, the proposed AgroChain solution comply with a process model that separates the registry of agricultural records from the record itself. The development of the AgroChain prototype along with its smart contracts that establish a transparent, yet secure, environment within the ASC under Quorum which is Ethereum oriented network is illustrated in this research. This research demonstrates that Blockchain networks offer a solution to manage the ASC ensuring traceability, privacy and integrity. Moreover, the research indicates that there is a pressing need to promote the standardization of ASC smart contracts, incorporating secure and straightforward process. Smart contracts have to ideally be implemented in consortium environments, enabling reliable validation of transactions by independent third parties without necessitating access to their content. Moreover, investigating the accountability for illegal activities become challenging.

Efficient sharing of comprehensive and relevant electronic health records (EHRs) is critical for precise disease research and high-quality, timely diagnoses. Recently, blockchain-based EHR sharing solutions have addressed issues such as single points of failure and data silos. However, decentralized solutions still face challenges in efficiently tracking and sharing dispersed and correlated medical records. Patients, lacking professional medical knowledge, struggle to construct and maintain the lineage of their overall medical records, leading to inefficient and insecure sharing of correlated EHRs with trusted doctors. Doctors from various departments also struggle to access the most relevant EHRs necessary for a precise understanding of patients’ medical histories. This study introduces a blockchain-based EHR system with provenance awareness, collecting data provenance to document traceable patient histories, facilitate rapid authorizations for correlated EHRs in a lineage, and conduct post-authorization audits. Designing a DAG-like data structure, the system efficiently stores the EHR provenance on blockchain and optimizes provenance-specific search. The system introduces a dedicated EHR authorization layer to facilitate dynamic authorization propagation along with the EHR provenance path. Harnessing Nash equilibrium principles, the system establishes an honesty-driven auditing mechanism to scrutinize doctors’ data access provenance and the intricate journey of patient health records. We developed a prototype using Ethereum blockchain smart contracts, verifying the feasibility of our model. The prototype successfully integrates data provenance, operates at expected costs, enhances user-friendliness, and improves access control efficiency.

The emergence of blockchain and smart contracts has revolutionized various industries by enabling automated code execution. However, the development of smart contracts, rooted in programming languages, inherits common challenges in traditional software development, notably concerning efficiency, reliability, and security. The application of deep learning techniques holds promise for addressing these challenges. However, a critical issue in applying deep learning to smart contracts is the lack of extensive datasets, as smart contracts have only recently emerged compared to traditional programming languages. To address this problem, we propose a novel approach called Compiler-Guided Generation Networks (CGGNet) for augmenting smart contract datasets. In contrast to existing methods, CGGNet utilizes a compiler as an oracle in generative networks, ensuring the augmentation of a valid smart contract. By incorporating the Montecarlo tree search, CGGNet significantly enhances the diversity and validity of the generated contracts, overcoming the limitations posed by GAN-based models in code augmentations. To the best of our knowledge, this is the first study on code augmentation targeting smart contracts. Our experiments show that millions of unique and valid smart contracts can be augmented from thousands of valid smart contracts, and augmented datasets can mitigate the underfitting problem in practical deep learning applications.

Resource trading between vehicles, which involves the buying and selling of computing and bandwidth resources, is a promising approach for cost-effectively provisioning services in safety-critical applications such as autonomous driving. These applications require a guarantee and the timely receipt of resources through efficient advance reservations. However, due to uncertainties in future reservation duration and resource costs, vehicles exhibit two distinct patterns: some may have reserved insufficient resources and need to purchase more (acting as vehicle requesters), while others may have overbooked resources and need to sell (acting as vehicle providers). In this paper, we formulate the resource trading problem from both the requester and provider perspectives and propose a resource trading architecture to optimize bandwidth reservation. It utilizes blockchain smart contracts for secure and efficient resource exchange within a mobile network operator (MNO) environment. Two algorithms are introduced: a provider selection algorithm to enhance system efficiency by selecting cost-effective providers, and a decision-making algorithm to assist providers in choosing between selling overbooked bandwidth or canceling it. Through simulations, the results show that these algorithms lead to significant cost reductions for requesters and profit gains for providers, up to 59% and 19%, respectively, compared to reservation schemes without resource trading in such a dynamic environment.

The integration of distributed energy resources (DERs) and digital technologies has accelerated the transition to decentralized energy systems. Among these technologies, blockchain stands out for its ability to facilitate peer-to-peer (P2P) energy trading efficiently and securely. This paper explores the concept of P2P energy trading within community microgrid systems, leveraging blockchain-based smart contracts. The proposed system integrates an incentive-driven demand response program directly into the smart contract framework, offering real-time rewards for load-balancing contributions. By incorporating the microgrid’s Energy Management System (EMS) and transparently recording all transactions on the blockchain, the proposed platform provides detailed data and immediate reward distribution. At the core of our system lies the Supply to Demand Ratio (SDR), ensuring fair energy exchange within the community. Dynamic pricing, enabled by blockchain and Tether (USDT) cryptocurrency, adjusts to real-time market conditions, enhancing transparency and responsiveness in energy trading. This adaptive pricing model fosters a more equitable and efficient trading environment compared to static approaches. Moreover, this system is tailored for community microgrids, emphasizing a community-centric approach. Local prosumers serve as validators in the blockchain network, aligning energy management decisions with community needs and dynamics. This localized engagement promotes efficiency and participation, fostering resilient, sustainable, and user-centric energy landscapes. Through rigorous analysis, we demonstrate the system’s effectiveness in optimizing economic efficiency, reducing operational costs, and increasing compliance rates. By combining blockchain technology with community-focused design principles, the proposed platform represents a significant advancement towards self-sufficiency and resilience in local energy systems.

The implementation of the Know Your Customer (KYC) strategy by banks within the financial sector enhances the operational efficiency of such establishments. The data gathered from the client during the KYC procedure may be applied to deter possible fraudulent activities, money laundering, and other criminal undertakings. The majority of financial institutions implement their own KYC procedures. Furthermore, a centralized system permits collaboration and operation execution by multiple financial institutions. Aside from these two scenarios, KYC processes can also be executed via a blockchain-based system. The blockchain’s decentralized network would be highly transparent, facilitating the validation and verification of customer data in real-time for all relevant stakeholders. In addition, the immutability and cryptography of the blockchain ensure that client information is secure and immutable, thereby eradicating the risk of data breaches. Blockchain-based KYC can further improve the client experience by eliminating the requirement for redundant paperwork and document submissions. After banks grant consumers loans, a blockchain-based KYC system is proposed in this study to collect limit, risk, and collateral information from them. The approach built upon Ethereum grants financial institutions the ability to read and write financial data on the blockchain network. This KYC method establishes a transparent, dynamic, and expeditious framework among financial institutions. In addition, solutions are discussed for the Sybil attack, one of the most severe problems in such networks.

Blockchain technology originated alongside Bitcoin as a novel method of conducting financial transactions. It has garnered significant attention from both industry and academia in recent years, emerging as a prominent area of research. It is a decentralized record-keeping system that holds transactional information. The scale of a blockchain network expands according to the growth in the number of nodes and transactions, resulting in issues related to storage capacity, data processing speed, and time delay. These issues have a direct impact on the scalability of a blockchain network. Currently, scalability is one of the prominent concerns in the field of blockchain technology and an active research area. This study conducts a comprehensive survey of the scalability challenges faced by blockchain technology in several sectors. It also examines potential solutions based on consensus mechanisms, smart contracts and directed acyclic graph (DAG). It is observed that the proposed scalability solutions target enhancing system throughput, reducing costs, and improving blockchain efficiency. Therefore, we examine, compare, and evaluate the literature using these specific criteria. Moreover, a survey of existing blockchain based survey papers is presented. A comparative analysis of these survey papers is presented along with their recency score, which is determined by the number of recent publications reviewed in a survey paper. By “recent,” we mean the current year (or the publication year of a survey paper) and the three years prior to it. Additionally, this paper offers an elaborate discussion on the forthcoming open research challenges and applications of blockchain.

This paper introduces a novel dynamic spectrum sharing (DSS) scheme designed for cell-free massive MIMO (CF-mMIMO) networks. The motivation behind this work arises from the urgent need to enhance spectrum utilization in modern wireless communication systems. Traditional spectrum allocation methods often struggle to meet the diverse spectrum demands of different wireless operators. The proposed approach addresses these challenges by enabling the spectrum provider (SP) to flexibly allocate and sell its spectrum resources, empowering wireless virtual operators to acquire bandwidth efficiently based on their specific needs. In our framework, each wireless operator is represented by a CF-mMIMO network, characterized by an average spectral efficiency metric that quantifies the potential value of additional spectrum acquisition. Leveraging a Stackelberg game formulation, our DSS policy achieves an equilibrium point that optimally allocates bandwidths to operators and determines corresponding prices. This approach not only enhances spectrum utilization but also fosters fair competition among operators. A key innovation of our work lies in the utilization of blockchain technology, where all spectrum transactions are managed through a smart contract. This ensures transparency, integrity, and auditability throughout the spectrum trading process. The novel protocol facilitates seamless information exchange, orchestrates the Stackelberg game dynamics, and delivers conclusive outcomes to both the SP and the CF-mMIMO operators.

Non-fungible tokens (NFTs) have become an exciting technology that provides a fresh perspective on asset ownership, provenance, and value exchange. NFTs, a blockchain-based technology, are distinct and indivisible cryptographic tokens used to confirm and record the ownership of digital and physical assets in an immutable and transparent way. The fundamental block of NFT is a smart contract built on a blockchain network. This contract contains specific information about the asset it represents, such as its unique identifier, metadata, and ownership details. The information is kept private and tamper-proof due to the decentralized and distributed structure of the blockchain, boosting faith in the token’s authenticity. The NFT is gaining popularity, but it is still in the developing stage. There is a need for a comprehensive survey to guide future research and development in NFTs. Thus, this paper presents the technical components of NFTs, their features, and the minting process. Further, this survey paper describes different token standards for NFTs. It presents various applications of NFTs in healthcare, supply chain, gaming, identity verification, agriculture, intellectual property, smart cities, charity and donation, and education. The article also emphasizes the significant difficulties faced currently in implementing NFT technology from the viewpoints of ownership, governance, and property rights, as well as security, privacy, and environmental effects. This work also elucidates the future directions to overcome the challenges in adopting NFTs in various applications.

Smart Contracts (SCs) communicate with each other using external calls. Their interactions can be malicious, resulting in the loss of Ether. One can blame the reentrancy attack for this exploitation. Several previous endeavors detected the reentrancy vulnerability by creating testing tools using static analysis like Remix. However, these approaches do not execute the programs. Hence, we cannot confirm their actual results. In this paper, we present TechyTech that detects both reentrancy and ${\mathtt { tx.origin}}$ vulnerabilities using a novel dynamic analysis approach of involuntary transfer (i.e., unintended transfer). Henceforth, we use a tree-based categorization string to distinguish the two vulnerabilities and their variations. Further, our research discusses multiple SC-related issues like the hijackedStack, deployed owner, and non-generation of transaction receipts in connection with reentrant calls, which we could not find in previous work. Through an example, we demonstrate how the actual Ether transfer is greater than the intended due to reentrancy.

The conventional Public Key Infrastructure (PKI) has long been plagued by security issues stemming from its centralized and non-transparent design. In recent years, blockchain-based PKI architectures have emerged as promising solutions to overcome such issues. However, existing research has predominantly focused on SSL certificates, overlooking other certificate types used for purposes such as facilitating electronic signatures/seals, code signing, and S/MIME- all reliant on the foundational PKI infrastructure. In this study, we present a novel blockchain-based PKI architecture designed to accommodate diverse certificate types. Combining the principles of the Web of Trust with a centralized model, our SemiDec-PKI establishes a resilient, distributed infrastructure. This unique synergy minimizes reliance on a single central authority, mitigating the vulnerabilities associated with traditional PKI systems’ single points of failure. With a cross-check mechanism and collective consensus of trusted entities, SemiDec-PKI provides higher fault tolerance, preventing disruptions from certificate misissuance or compromised certificate authorities. Furthermore, it introduces a stake-based reward-punishment mechanism which incentives honest behavior and penalizes malicious actions, serving as a potent deterrent against impersonation attacks.

Industrial Internet of Things (IIoT) applications consist of resource constrained interconnected devices that make them vulnerable to data leak and integrity violation challenges. The mobility, dynamism, and complex structure of the network further make this issue more challenging. To control the information flow in such environments, access control is critical to make collaboration and communication safe. To deal with these challenges, recent studies employ attribute-based access control on top of blockchain technology. However, the attribute-based access control frameworks suffer due to high computational overhead. In this paper, we propose an improved role-based access control framework using hyperledger blockchain to deal with IIoT requirements with less computational overhead making the information control process more efficient and real-time. The proposed framework leverages a layered architecture of chaincodes to implement the improved access control framework that handles the permission delegation and conflict management to deal with the dynamism of the IIoT network. The system uses a Policy Contract, Device Contract, and Access Contract to manage the workflow of the whole access control process. Each chaincode in the proposed framework is isolated in terms of its responsibilities to make the design low coupled. The integration of improved access control with blockchain enables the proposed framework to provide a highly scalable solution, tamper-proof, and flexible to manage conflicting scenarios. The proposed system outperforms the recent studies significantly in computational overhead in extensive simulation results. To verify the scalability and efficiency, the proposed is evaluated against a large number of concurrent virtual clients in simulation and statistical analysis proves that the proposed system is promising for further research in this domain.

The blueprint of the proposed Decentralized Smart City of Things (DSCoT) has been presented with smart contracts development and deployment for robust security of resources in the context of cyber-physical systems (CPS) for smart cities. Since non-fungibility provided by the ERC721 standard for the cyber-physical systems (CPSs) components such as the admin, user, and IoT-enabled smart device/s in literature is explicitly missing, the proposed DSCoT devised the functionality of identification and authentication of the assets. The proposed identification and authentication mechanism in cyber-physical systems (CPSs) employs smart contracts to generate an authentication access code based on extended non-fungible tokens (NFTs), which are used to authorize access to the corresponding assets. The evaluation and development of the extended NFT protocol for cyber-physical systems have been presented with the public and private blockchain deployments for evaluation comparison. The comparison demonstrated up to 96.69% promising results in terms of execution cost, efficiency, and time complexity compared to other proposed NFT-based solutions.

Today, educational data, controlled centrally by educational institutions and administrative units, may be vulnerable to damage caused by natural disasters, political instability, and wars. Simultaneously, challenges arise in accessing this data for educational activities within the framework of exchange programs or lifelong learning. In the literature, there are numerous blockchain-based studies focusing on storing and sharing data in various fields. While several studies exist on blockchain applications for certification, verification, and data sharing in the education sector, a fully decentralized infrastructure has not yet been presented. To address this issue, it is proposed that data control should shift to the hands of students, who are the rightful owners of the data, rather than being solely in the hands of educational institutions. In alignment with the decentralized internet vision, Web3, public blockchain networks are considered the most suitable infrastructure for this purpose. To meet this need, a framework named PublicEduChain has been introduced within the scope of this study. PublicEduChain allows students to store their data in smart contracts created on the public Ethereum network, making it possible to share this information with any educational institution and administrative units. Educational institutions can access student data stored in smart contracts on the public Ethereum network through Learning Management System (LMS) applications and can add data to these contracts. PublicEduChain ensures that data is managed under student ownership within a fully decentralized infrastructure. The practical steps in PublicEduChain, such as creating a smart contract, logging into LMSs with Ethereum IDs, and allowing LMSs to read and write data in the student contract, are explained in detail.

Smart contracts are rapidly applied in many fields, with their varied types and increasing complexity. A sharp increase in the method development demands seems to be certain. However, this type of development has its unique programming language and security requirements, making it difficult for regular software personnel to adapt quickly. It is important to realize that the development efficiency is application-specific and that getting this application issue solved is critical for its further development. To this end, we propose a new, automatic, and intelligent contract-generation method, based on code annotation. First of all, combined with the semantic annotation information of smart contract code association, a clustering analysis model is built to realize fast and accurate clustering with functions similar to smart contracts. Then, based on the Char-RNN network, a multi-level and automatic generation method of intelligent contract knowledge base is built to realize the automatic generation at different levels, such as the contract layer, function layer, and interface layer. Finally, by using text matching technology and by calculating the semantic similarity of the user text demands as well as the smart contract knowledge base annotation, the relevant contract code is automatically extracted for users to choose, with the aims of improving the method efficiency and to meet the needs of different users. To test the effectiveness of the method, with the aid of bilingual quality assessment BLEU and Mythril, VaaS, and other code security tools for evaluation are used and results are compared with the existing method. The generated code BLEU average score was increased by 27% and the average accuracy was increased by 11.5%. Therefore, the smart contract generated by our method is relatively accurate and reliable.

In response to global efforts to deal with climate change, various renewable energy policies are being implemented. Among these, renewable portfolio standards (RPS) and renewable energy 100 (RE100) regulate the obligated supply of renewable energy to ensure compliance with set quotas by nations and institutions. In this context, the renewable energy certificate (REC) system is employed to assist obligated entities in meeting their renewable energy generation quotas. Obligated entities can purchase REC from renewable energy generators to obtain recognition for their renewable energy allocation. However, the current REC system is insufficient in addressing issues related to procedural complexity and cyber security. This study aims to overcome its limitations by applying blockchain technology. Blockchain, a distributed financial network, serves as a digital ledger, enabling peer-to-peer transactions in a simple, transparent, and secure way. The proposed new REC system based on blockchain moves away from the complex structure of the traditional REC system, simplifying the system into four processes: participation, issuance, transaction, and authentication. Moreover, applying blockchain algorithms can address the cyber security issues of the traditional system. The case study using Hyperledger Besu, or one of the blockchain platforms, demonstrates that the aspects of procedural complexity and cyber security are improved in the proposed system.

In the modern era, the significance of incentive mechanisms spans a variety of fields, including the development of smart cities, the dynamics within social information networks, and the realm of online education. This study introduces an innovative incentive strategy, grounded in the use of blockchain contracts, aimed at cultivating reliable interactions among participants while simultaneously bolstering the security and effectiveness of digital learning resources. By capitalizing on the inherently decentralized architecture of blockchain technology, this research unveils a novel approach to digital learning resources, encompassing both the concept and its associated storage framework. Moreover, the study proposes a dynamic optimization model specifically designed for the blockchain of educational resources. This model is crafted to fit seamlessly within the context of real-world educational settings, taking into careful consideration the diverse viewpoints of all stakeholders engaged with particular educational materials. In the realm of practical education, particularly within the domain of computer science, this approach emphasizes the integration of pertinent learning materials into blockchain nodes, thereby addressing key educational content. By implementing a blockchain smart contract, an incentive mechanism is created that rewards both learners and resource contributors, effectively encouraging active participation in resource development and quality improvement. This mechanism effectively tackles challenges in the learning process, such as inaccurate resource access, reduced learning efficiency, and the scarcity of current, high-quality online resources. Experimental findings show that the smart contract-driven online learning resource incentive mechanism significantly improves teaching effectiveness.

Mobile smart contracts (MSCs) are essential to facilitate quick, safe, and decentralized transactions on mobile blockchain networks. Scalable blockchain solutions facilitate the establishment of a mobile blockchain ecosystem characterized by enhanced resilience and adaptability. This encourages an increase in the number of users and, thus, spreads the adoption of blockchain technology in the mobile domain. With the inception of blockchain technology, a wide range of applications use smart contracts due to their high customizability. However, problems with scalability and resource-intensive consensus procedures prevent their general use. Therefore, this work seeks to identify and analyze these constraints by conducting a systematic survey using Kitchenham’s guidelines for available scalable blockchains and consensus methods. Out of a preliminary pool of 2,073 publications, our study, which consists of 25 selected studies, identifies 12 consensus mechanisms and 13 scalable blockchain systems. Our investigation shows that, despite the wide range of techniques, no blockchain solution provides the scalability and lightweight operating requirements to implement smart contracts on mobile devices. This realization draws attention to a significant gap in academic and industry-driven blockchain research that may have implications for creating MSCs. Our findings encourage academics to explore scalable and energy-efficient blockchain technology, targeting creating more approachable smart contracts designed with mobile devices in mind.

Decentralized finance (DeFi) offers a range of financial instruments and services that leverage the capabilities of web3 technology. Maker protocol, which enables users to obtain loans backed by cryptocurrencies, is one of them. Unlike traditional banks, Maker’s data is transparently recorded on the Ethereum blockchain. In this research paper, we focus on analyzing the lending aspect of Maker from a traditional finance perspective. To achieve this, we create a unique dataset with loan portfolios from the MakerDAO project, making it the first dataset of its kind in the DeFi field. This publicly available dataset contains essential financial characteristics related to borrowing, including balance, loss given default, annual equivalent rate, and probability of default. Additionally, we develop a specialized mathematical model tailored specifically to this project. This model allows us to estimate the probability of default by considering the presence of crypto-collateral and utilizing Brownian motion passage levels. The results of this study provide valuable insights into lending practices in DeFi projects. They also help bridge the gap between traditional finance and blockchain-based financial services.

As it plays a key role in industrial and commercial development, the stock market has significant impacts on a country’s economic growth; the stability of the stock market is therefore very important. However, the current stock-trading system is centralized, and investors have to participate in trading stocks through intermediaries/dealers, consequently causing problems such as high transaction fees, potential manipulation by intermediaries/dealers, long settlement times, and data protection issues. The advantages of blockchain technology, such as immutability, improved security, transparency and efficiency, not only make blockchain and fintech inextricably linked, but also shed light on innovations of existing stock-trading systems. This research aimed to alleviate the transaction costs, data storage security, and centralized system failures caused by the original centralized stock trading system through the blockchain-based stock trading prototype innovation/renovation of stock trading services. Further, it explored the application of blockchain in the field of financial technology. In order to prove the feasibility of a decentralized blockchain-based stock trading service, in the research methodology, this study first drew the architecture of the system through object-oriented analysis, followed by the flowchart of each function and smart contract. Finally, based on each flowchart, a blockchain stock system was developed to replace the centralized stock trading service in a decentralized, transparent, tamper-proof, and secure manner. After proposing the design and implementation details of a blockchain-based system with required service functions, we performed functional/performance tests and theoretical analysis of the system, confirming its feasibility, applicability, and value. The research results showed that our system has the characteristics of blockchain decentralization, which can alleviate the problems of transaction fees, broker manipulation, and data storage security encountered by existing stock trading services.

This paper proposes a novel trust-based cooperative system to facilitate efficient Wi-Fi network access trading to solve the network congestion problem in a beneficial manner for both service providers and customers. The proposed system enables service providers to improve their users’ application performance through a novel cooperative Access Point (AP) association solution. The system is based on a Software-Defined Wireless Network (SDWN) controller, which has a global view of users’ devices, requirements, and APs. The SDWN controller is supported by Smart Contracts (SCs) as code of law, to liaise control among service providers according to the terms of their mutual agreements. Evaluation results in dense Wi-Fi network environments show how the system can significantly improve the overall performance for the cooperating network. Specifically, the results have been compared against the standard AP association approach and other centralised algorithms dealing with the same problem, in terms of the data bit rate provided to the users’ stations (STAs), Quality of Experience (QoE), bandwidth and energy consumed by the APs.

Smart Contract and Blockchain are necessary for transactions in supply chain management. A smart contract is an agreement in the form of a cryptographic code digitally signed by the actors. This technology holds the data transaction transparently and securely. The actors may benefit without intermediaries involved in the transaction. Supply chain management will be easily tracked by decentralized data sharing. Supply chain management involves transactions in agricultural sectors such as farmers, village cooperatives units, distributors, and consumers. The Cooperative is a party that buys goods from farmers and sells them to consumers. A smart contract is a digital signature that can access the system in transactions. The system records log activities that show the origin of transactions. All actors can see the transaction of agricultural products stored in the blockchain ledger in the Blockchain. This paper discusses blockchain-based Smart Contract scenario for supply chain management that is simulated and implemented in the Serious Game. The Game is developed using Unity 3D Development Platform, programming language contract using Solidity, Moralis as Web3 Development Platform and dApp as backend blockchain, Network Environment Polygon Ethereum, and Database that is Redis Enterprise, MongoDB Compass, and Mumbai Testnet.

Due to the resource limitations of Internet of Things (IoT) terminals and the distributed characteristics of edge computing architecture, trustworthy services management in dynamic edge computing is a very large challenge. A general and extensible blockchain-based multidimensional trust management (BMDTM) model suitable for edge computing is proposed in this paper. First, probabilistic linguistic terms sets (PLTSs) are adopted as a trust scaling method to integrate the multicriteria evaluation data of the whole domain to measure the performance of the service provider, and the stability degree of each attribute performance is calculated based on information entropy theory, which enables us to measure the dynamic performance accurately and precisely. Second, the dual characteristic of the associated criteria is utilized to filter out malicious or unprofessional evaluation information of requesting nodes and avoid malicious user collusion, ensuring the credibility of trust management. Third, blockchain technology and smart contracts (SCs) are adopted to store trust evidence, share trust information across domains, and execute multisource trust fusion automatically, avoiding the problems of information opacity and the single point of failure of the traditional centralized trust model. The experimental results demonstrate that our model can well manage trust problems in a dynamically hostile edge computing environment. The first finding is that the introduction of the domain trust value significantly improves the quality of service (QoS) compliance ratio due to an accurate description of the dynamic performance of services. The second finding is that our model performs better in attack resistance by leveraging blockchain technology and the dual characteristic of the associated criteria.

The Internet of Things (IoT) connects many objects and allows continuous communication and data sharing has emerged as a revolutionary technology. However, expanding IoT devices has raised concerns regarding data security and access control. Traditional access control mechanisms face challenges in managing access rights, particularly in scenarios where multiple users with the same roles try to access several resources which may lead to conflicting roles. Additionally, there is also an overhead of system performance using traditional approaches. In existing studies, the main problem of conflict roles is not addressed or not even identified appropriately. This paper proposes a framework to address these challenges using blockchain technology and role-based access control with a smart contract implementation on the hyperledger fabric framework. The proposed methodology introduces a role management system that resolves conflicts based on predefined rules and user preferences. It employs a consensus mechanism to determine access permissions, ensuring fairness and accountability. The findings demonstrate that applying the suggested framework eliminates conflicting problems, improves system security and also provides better results in response times for concurrent user requests.

In view of the significant computational resources required for numerical simulation of electromagnetic comprehensive performance in modern electrical equipment, and the security and transaction fairness issues of existing delegated computation schemes, we propose a delegated computation scheme under the blockchain framework that is suitable for numerical simulation of electromagnetic comprehensive performance. This scheme combines the multi-level data characteristics of electromagnetic field numerical simulations with practical needs. Firstly, we propose a method for handling multi-layered data in delegated computation. Secondly, we design a delegated computation architecture that involves at least three participants and a detailed transaction mechanism, and develop three smart contracts to ensure data privacy protection and transaction fairness in delegated computation. Finally, the feasibility of the proposed scheme is proved by delegated computations for “Solving the Poisson equation of two-dimensional electrostatic field” and “Optimization of amorphous alloy transformer”. The research results have achieved a reliable and credible solution to the large-scale data computing problem in the field of numerical simulation of electromagnetic comprehensive performance, and provided a new theory and solution for data security in this field.

An auction is commonly used to sell limited resources in modern society. M+1st-price auction sells M identical goods to B bidders. The top M winners can buy the goods at the M+1st-price. Each bidder sends their bids secretly as a bit-slice bidding vector to a trusted manager. Bit-slice is commonly used to compare secret values without revealing them. However, the bit-slice bidding vector also limits the upper bound of a bid as the length of the bidding vector. A binary format bidding vector was proposed to increase the bid upper bound to an exponential scale. For example, given a bidding vector with length 32, a binary format bidding vector can increase the bid upper bound from 32 to two to the power of 32. However, previous protocols that use binary format bidding vectors require a somewhat homomorphic encryption (SHE) and a trusted manager. To make sure no party except the bidder itself knows its bid, our protocol does not have any managers. Instead, each bidder interacts with the Smart Contract independently. We propose a zero-knowledge proof that allows our protocol only requires partially homomorphic encryption such as an ElGamal encryption. To our best knowledge, our protocol is the first secure M+1st-price auction protocol that can reach an exponential bid upper bound without a manager and SHE.

Traditional techniques for smart contract vulnerability detection rely on fixed expert criteria to discover vulnerabilities, which are less generalizable, scalable, and accurate. Deep learning algorithms help to address these issues, but most fail to encode true expert knowledge and remain interpretable. In this paper, we present a smart contract vulnerability detection mechanism that operates in phases with graph neural networks and expert patterns in deep learning to mutually address the deficiencies of the two detection approaches and improve smart contract vulnerability detection capabilities. Experiments show that our vulnerability detection mechanism outperforms the original deep learning model by an average of 6 points in detecting vulnerabilities and that the second stage of the checking mechanism can also block contract transactions containing dangerous actions at the Ethernet Virtual Machine (EVM) level and generate error reports for submission. This strategy helps to construct more stable smart contracts and to create a secure environment for smart contracts.

Purpose: With the advancement and modernization of Information and Communication Technology, electronic voting (e-voting) has been adopted across the globe for conducting a secure and efficient voting procedure. However, e-voting can be easily exposed to various malicious attacks such as denial-of-service, malware, insider, compromised credentials, etc., that can risk the voter’s privacy and affect the final voting results. Thus, we have considered the decentralized and immutable blockchain technology for completing the voting procedure securely. Nevertheless, many researchers have considered blockchain to mitigate the security and privacy issues of the voting procedure, but they ignored the aspect of cost-efficiency, latency, and response time while voting. Method: The idea of the proposed mechanism is to deploy and implement the smart contract in the Remix Integrated Development Environment (IDE) involving number of voters electing the candidate with various functionalities. Moreover, we considered the amalgamation of blockchain and IPFS to overcome the data storage cost issues of blockchain for voters and candidates communicating through 5G wireless network. The 5G network, with its low latency, high availability, and high reliability facilitates high data rate and reliable communication between voters and candidates to complete the voting procedure efficiently. Results: The deployed smart contract of the proposed voting mechanism highlight various functionalities required for electing the candidate by the voters. Moreover, the deployed smart contract is evaluated and analyzed considering various performance metrics such as gas consumption analysis for smart contract functions and number of voters, cost analysis for smart contract functions, bit error rate, and storage cost comparison with the traditional scheme. We have also verified the security of the proposed voting mechanism using Echidna security tool which shows the election of candidate without any threat. Conclusion: Finally, we have presented a blockchain-based voting mechanism in which IPFS and 5G is employed to avail the cost-efficient, reliable, and secure candidate election by the voters. Moreover, the voters and candidates can communicate with lower response time and high reliability using 5G network so that smart contract consisting of all the functionalities related to the candidate election can be executed efficiently in the Remix IDE.

This paper addresses the issue of sustainability in retail sales, where the composition of the products themselves, their production and packaging process, and their transport to the point of sale play an important role. We propose a solution to apply a unified system of environmental product rating in different retail chains where trust is ensured through a distributed ledger. The system allows fair and transparent rewards for customers who purchase eco-friendly products while also maintaining their privacy. The prototype of the decentralized application for the uniform loyalty system based on the Algorand blockchain has shown promising results in terms of throughput and cost efficiency. We believe that the prototype has the potential to revolutionize loyalty systems and promote sustainable practices. This study provides key insights into how to interconnect retailers and customers into a uniform reward program, how to motivate customers to purchase sustainable and eco-friendly goods, and how retailers can manage the amount of reward for the given Eco-score categories.

Supervision of Livelihood Issues (SLI) refers to the supervision and participation of the general public in government actions and public affairs, with a particular focus on issues closely related to people’s lives. However, current regulatory systems often suffers from information imbalances, low authenticity, and credibility. To address these challenges, this study proposes a blockchain-based SLI framework that leverages the decentralized, tamper-proof, traceable, and transparent nature of blockchain technology to provide a reliable platform for SLI. Furthermore, we designed an information data structure on the blockchain and presented the information flow process. We developed smart contracts that utilize automation capability to automatically aggregate, analyze, and publish warnings based on on-chain data, enabling the evaluation of relevant departments’ performance. Moreover, in the context of SLI applications, we propose an optimized consensus algorithm called the SLI-PBFT. This algorithm is based on the PBFT consensus protocol and incorporates dynamic scalability mechanisms, scoring models, and simplified consistency protocols to enhance the consensus efficiency of SLI applications. Finally, the experiments were conducted. We developed an SLI prototype system and compared and analyzed the performance of SLI-PBFT with other PBFT-based consensus algorithms within the SLI prototype system. The experimental results demonstrated the feasibility of the SLI framework. Moreover, SLI-PBFT exhibits significant improvements in throughput and reduced latency compared to other algorithms in the context of SLI applications. In addition, they possess strong fault tolerances and security capabilities. This study provides theoretical and practical guidance for the SLI in real-world scenarios.

Currently, many companies and institutions use centralized or distributed databases to store massive amounts of data. However, the use of untrusted centralized third-party auditors can result in security issues because these auditors may be malicious and tamper with or delete user data. This poses a significant challenge for ensuring the reliability of the data verification results. Although introducing a third-party auditor can help address this issue, it may also be untrustworthy and collude with the database service provider to forge false data verification results. In this study, we propose a data integrity verification scheme using smart contracts (DIV-SC) to address this challenge in a centralized database environment. Our approach utilizes blockchain technology as a decentralized third-party auditor, ensuring that the information stored on the blockchain is immutable and cannot be tampered with maliciously. In addition, smart contracts deployed on the blockchain can ensure that the verification procedures are correct and are not affected by any malicious party. We also leverage game theory to improve the reliability of multiple verifications, reduce verification time and improve overall performance. Our proposed scheme reduces the total verification time consumption by up to 53.44% while increasing the number of verifiable times by nearly 3.8 times, compared to conventional data integrity verification schemes.

Cloud storage is an essential method for data storage. Verifying the integrity of data in the cloud is critical for the client. Traditional cloud storage approaches rely on third-party auditors (TPAs) to accomplish auditing tasks. However, third-party auditors are often not trusted. To eliminate over-reliance on third-party auditors, this paper designs a blockchain-based auditing scheme that uses blockchain instead of third-party auditors to ensure the reliability of data auditing. Meanwhile, our scheme is based on the audit method of the quad Merkle hash tree, using the root of the quad Merkle hash tree to verify the integrity of data, which significantly improves computing and storage efficiency. Automated verification of auditing activities by deploying smart contracts on the blockchain allows us to have a more up-to-date picture of data integrity. The performance of the scheme is evaluated through security analysis and experiments, which prove that the proposed scheme is secure and effective.

In this paper, we propose a new digital signature primitive, called expander signature, and discuss its application in blockchain. The most promising advantage of expander signature is that a signer can generate all signatures at once using a powerful computer, and stores expander keys personally. Each time the signer wants some of his signatures to be verified, he releases the related expander key. No matter when or where, the signer can do this via a resource-limited device, for example, a personal portable terminal. We formally define the syntax and security of expander signature. Under our precisely defined security model, we give generic constructions of expander signature from both public key infrastructure-based and identity-based signature schemes. The security of our constructed expander signature schemes rigorously depends on the underlying public key signature schemes. The expander keys do not leak any information about the signer’s secret key and the size of the expander keys is constant no matter how many times the expander has been occurred. Finally, we give an application example of expander signature in blockchain.

Healthcare data is highly sensitive and must be safeguarded. Personal and sensitive data, such as names and addresses, is stored in Encrypted Electronic Health Records (EHRs). This paper proposes a Blockchain-based distributed application platform for Bangladesh’s public and private healthcare service providers. The proposed application framework enables users to create secure digital agreements for commerce or collaboration by leveraging data immutability and smart contracts. As a result, all stakeholders can collaborate securely over the same Blockchain network, taking advantage of their data’s openness and read/write nature. The proposed application is made up of various application interfaces for various stakeholders. The proposed solution employs Hyperledger Fabric and Blockchain to ensure data integrity, privacy, permissions, and service availability. In the application portal, each user has a profile. The creation of a unique identity for each user, as well as the establishment of digital information centers across the country, has greatly aided the process. This application collects health data from each user in a systematic manner, which is useful for research institutes and healthcare-related organizations. For this application, a national data warehouse in Bangladesh is feasible, and various healthcare-related analyses can be performed using the collected data, assisting the strategy and planning department in making informed decisions regarding the healthcare sector in Bangladesh. Because Bangladesh has both public and private healthcare providers, a simple digital strategy is essential for all organizations to accomplish their services. This study proposes a solution to achieve this goal.

Energy markets are being transformed rapidly all over the world due to an increased integration of renewable energy sources. Blockchain technology is emerging as a prime contender, as it can provide a secure and efficient transactional platform for such markets. In a typical microgrid energy market, the consumers and prosumers belonging to the microgrid have the ability to trade energy in a peer-to-peer fashion. However, the existing energy markets suffer from multiple issues security and privacy issues. To handle the aforementioned issues, this research work proposes a blockchain based secure Decentralized Transaction System (DTS) for energy trading in microgrids. The proposed system comprises of a secure market model that facilitates energy trade between energy users. A simplistic energy exchange mechanism has been formulated that ensures data integrity and privacy of the participating energy users. A prosumer centric consensus mechanism has been employed to incentivize the prosumers and ensure the availability of energy in the microgrid at all times. An efficient and dynamic pricing mechanism has been used to reduce the supply and demand disparity. A comprehensive trust model based on commitments has been adopted for ensuring the reliability of the participating energy user. Additionally, a hardware based access control mechanism has been utilized to make the proposed DTS a physical and cyber secure system. Other than this, a framework of smart contracts has been deployed to provide a comprehensive solution that ensures privacy, security, anonymity, auditability and confidentiality of the generated energy information. To demonstrate its practicality, the system has been implemented on Ethereum platform. The proposed DTS is validated using realistic data with the Ethereum Virtual Machine (EVM) environment of Goerli Test Network.

Visual object detection is a computer vision technique based on deep learning. However, due to privacy issues, it is highly challenging to build an object detection model according to the current methods on the centrally stored training dataset. Federated learning is an effective approach to solving the challenge of training data collection by using distributed training. We propose FedVisionBC, a blockchain-based federated learning system for visual object detection that addresses the challenges of single point of failure, model poisoning attacks, and membership inference attacks in traditional federated learning. In the FedVisionBC system, we set up an aggregation node and a verification node instead of a central server to solve the single point of failure problem. We establish a security mechanism that uses encryption techniques, verification nodes, and smart contracts to resist model poisoning attacks. Experimental results show that FedVisionBC can accomplish the object detection task when the percentage of malicious clients is less than 60%. We also propose a new algorithm, ADPFedAvg, to prevent membership inference attacks, which relies on user-level differential privacy technology and the federated average algorithm. Experimental results indicate that ADPFedAvg can achieve a large-scale visual object detection model with differential privacy protection, while only a negligible cost in predictive accuracy.

Despite the maturity of cloud services (e.g., outsourcing of computational tasks), a number of operational challenges remain. For example, how do we ensure trust between outsourcers and workers in a zero-trust environment? While a number of blockchain-based solutions that eliminate the reliance on trusted third parties have been presented, many of these existing approaches do not achieve robust fairness and/or support compatibility with other systems. In this paper, we propose an efficient fair payment system using blockchain (EFPB), designed to achieve robust fairness and compatibility. Specifically, EFPB comprises a number of cryptographic building blocks, mainly: one-way accumulator (RSA-based construction), stealth address and symmetric encryption. We then evaluate the performance of EFPB to demonstrate that it is more efficient and low-cost than other competing schemes, as well as presenting a comparative summary of functionalities.

Ranking systems have proven to improve the quality of education and help build the reputation of academic institutions. Each of the current academic ranking systems is based on different methodologies, criteria, and standards of measurement. Academic and employer reputations are subjective indicators of some rankings determined through surveying that is neither transparent nor traceable. The current academic ranking systems fall short of providing transparency and traceability features for both subjective and objective indicators that are used to calculate the ranking. Also, the ranking systems are managed and controlled in a centralized manner by specific entities. This raises concerns about fairness and trust. In this paper, we propose a blockchain-based solution to enable transparent, traceable, trusted, and decentralized academic ranking systems. We develop smart contracts to automatically govern entity interactions according to set policies. We leverage decentralized storage, oracles, and threshold encryption to securely fetch, store, and share institutions’ ranking data. We present algorithms along with their implementation and testing details, as well as validate smart contracts. The proposed solution is evaluated in terms of cost, throughput and latency, and security to show its affordability, resiliency against attacks, and superiority. All developed smart contract codes are made publicly available on GitHub.

Dynamic spectrum access (DSA) and network slicing are some of the principal concepts to realize the emerging applications in Beyond 5th Generation (B5G) and 6th Generation (6G) networks. The frequency spectrum remains scarce and underutilized, while the performance requirements in terms of data throughput and latency of the network tenants have diversified. DSA allows for the efficient utilization of spectrum resources, while network slicing aims to serve network users with highly distinctive service needs. Lack of incentivization, sharing of spectrum resources among multiple operators, and lack of trust between operators are some of the challenges faced by centralized DSA approaches. Similarly, secure network slice orchestration, slice-isolation, secure access to network resources, privacy of user sensitive data, assuring the provision of Service Level Agreements (SLAs), are some of the challenges in existing network slicing techniques. Blockchain due to its innate capabilities can be a promising technology to solve the key issues pertaining to current DSA and network slicing approaches. Blockchain through smart contracts, provides traceability of network resources, auditability and accountability of network operators and service providers. Smart contracts facilitate the automation of resource sharing and network slice orchestration, while ensuring that SLAs are met, and network operators are compensated. This paper first provides a comprehensive overview of the DSA concept, the existing DSA techniques, and the challenges posed by these techniques. This is followed by a detailed description of network slicing, its key elements and architecture, various network slicing parameters, existing network slicing techniques and their challenges. Then an in- depth review on blockchain, its working principle, factors that affect blockchain implementation, and a comparison of various open-source blockchain platforms that support smart contracts is presented. This discussion is summarized by presenting the state-of-the-art in the blockchain-enabled DSA and network slicing, challenges and trade-offs of these techniques, and the gaps and future directions in this research area. Finally, we conclude by providing some future research directions.

The growing popularity of online news has prompted concerns regarding (i) the socio-political influence over news dissemination, (ii) the waning freedom of news media, (iii) and a facile news evaluation process. A piece of news having the power to capture a large audience and sow the seed of bizarre consequences on a national scale should be prudently evaluated before reaching the mass. In quest of making a substantial profit, and sometimes due to inevitable socio-political influence, news with biased heading outpours mass media, resulting in ambiguity and mass manipulation. In this paper, we suggest a blockchain, smart contract, and incremental machine learning-based news evaluation procedure for the Bengali language to overcome these challenges. Weighted synthesis of machine classification and human expert opinion in a decentralized platform are synthesized to evaluate news. With continuous data, the Natural Language Processing (NLP) model is incrementally trained, and the best version of the model is used to detect deprived fake news. During experiments, the NLP model with initial training and testing accuracy of 84.94% and 84.99% was increased to 93.75% and 93.80% after nine rounds of incremental model training. On the Ethereum test network, the protocols have been installed and tested. The simulation demonstrates successful implementation of our proposed system.

The Augmented Intelligence of Things enables many edge or end devices in the Internet of Things (IoT) to perform machine reasoning to make decisions, thus become more intelligent. For healthcare enterprises, huge physical data generated by smart devices facilitate to iterate their products. However, traditional data sharing models based on cloud outsourcing meet many security challenges, such as data confidentiality, reliability, and privacy protection, and most existing schemes have high computational complexity for the utilization of time-consuming cryptographic operations, such as bilinear pairing, which is not suitable for those resource-constrained IoT devices. To tackle the abovementioned issues, we present Double Rainbows, a promising data sharing scheme based on pairing-free searchable encryption. It is constructed on the cloud-edge-end architecture, supporting computing task transfer and reliable data storage and retrieval. The experimental results show that it outperforms in efficiency and exhibit more security functionalities. [ABSTRACT FROM AUTHOR]

Blockchain performance cannot meet the requirement nowadays. One of the crucial ways to improve performance is sharding. However, most blockchain sharding research focuses on the public blockchain. As for consortium blockchain, previous studies cannot support high cross-shard efficiency, multiple-shard contract calling, strict transaction atomicity, and shard availability, which are essential requirements but also challenges in consortium blockchain systems. Facing these challenges, we propose Meepo, a systematic study on sharded consortium blockchain. Meepo enhances cross-shard efficiency via the cross-epoch and cross-call. Moreover, a partial cross-call merging strategy is designed to handle the multi-state dependency in contract calls, achieving flexible multiple-shard contract calling. Meepo employs a replay-epoch to ensure strict transaction atomicity, and it also uses a backup algorithm called shadow shard based recovery to improve the shard robustness. On a test-bed of 128 AliCloud servers, setting 32 shards and 4 consortium members, Meepo-OpenEtheruem can achieve more than 140,000 cross-shard TPS under the workload of 100,000,000 asset transactions. It also shows more than 50,000 TPS under the transactions of real-world shopping behaviors. [ABSTRACT FROM AUTHOR]

Leveraging watchtowers to monitor payment channel networks (PCNs) is regarded to be a promising option to ensure off-chain transaction security and boost cryptocurrency scalability. However, existing solutions have two major limitations: First, since the watchtower’s inaction or collusion with counterparties, the deposits in off-chain transactions will be threatened; Second, due to occasional false positives, the efficiency of the single watchtower in monitoring the payment channels for fraud is questionable. To solve this, we present anti-collusion multiparty smart contracts for distributed watchtowers in PCNs. Specifically, we first design the distributed watchtower mechanism to solve the false positive problem in regulating PCNs. In addition, we utilize smart contracts to constrain and force counterparties to relinquish collusion in the distributed watchtower mechanism, thus making collusion impossible for rational parties. We further offer a mathematical proof and contract implementation in Solidity. Finally, extensive experiments and contracts executed on Ethereum under various benchmarks with baseline comparison demonstrate the validity of our proposals. Specifically, our scheme can both improve the throughput and accuracy by up to 20-25% and 10-15%, respectively, and reduce the false positive rate by up to 10% compared with existing single watchtower mechanism. [ABSTRACT FROM AUTHOR]

Although the emergence of the programmable smart contract makes blockchain systems easily embrace a wide range of industrial services, how to execute smart contracts efficiently becomes a big challenge nowadays. Due to the existence of Byzantine nodes, existing mature concurrency control protocols in database cannot be employed directly, since the mechanism of executing smart contracts varies a lot. Furthermore, even though smart contract execution follows a two-phase style, i.e., the primary node executes a batch of smart contracts in the first phase and the validators replay them in the second phase, existing parallel solutions merely focus on the optimization for the first phase, rather than the second phase. In this paper, we propose a novel two-phase concurrency control protocol to optimize both phases for the first time. First, the primary executes transactions in parallel and generates a transaction dependency graph with high parallelism for validators. Then, a graph partition algorithm is devised to divide the original graph into several sub-graphs to preserve parallelism and reduce communication cost remarkably. Finally, we propose a deterministic replay protocol to re-execute the primary’s parallel schedule concurrently. Moreover, this two-phase protocol is further optimized by integrating with PBFT. Theoretical analysis and extensive experimental results illustrate that the proposed scheme outperforms state-of-art solutions significantly. [ABSTRACT FROM AUTHOR]

The decentralization feature of public and private blockchain-based applications is achieved by selecting different nodes as validators or Certificate Authority ( $CA$ ) for each transaction. Public blockchain uses Proof of Work ( $PoW$ ) to search for the validator. $PoW$ causes an enormous amount of energy. Therefore, Proof of Stake ( $PoS$ ), and Proof of Authority ( $PoA$ ) emerged as alternate solutions. Selection of a new $CA$ using $PoS$ or $PoA$ algorithms for each transaction may improve transaction security. However, a network may have a large number of transactions and participants. Selecting a $CA$ for each transaction using $PoS$ or $PoA$ may cause a significant amount of block propagation delay, which can reduce network efficiency drastically. This paper proposes a different approach to increase the efficiency of Blockchain-based Public Key Infrastructure ( $BC-PKI$ ). The proposed approach creates clusters of participant nodes based on their validation time, response time, and trust. This method selects a cluster based on the budget of response time and validation time given by the node that intends to start a transaction. Thereafter, the node which has the highest trust in that cluster is chosen as a $CA$ for the next transaction. Instead of searching on all participant nodes, our approach searches on the nodes of the chosen cluster which reduces the searching space of the $CA$ selection process. This research work adopts a trust evaluation approach where the trust factor is quantified based on its experience and reputation. The node trust is reevaluated after every successful and unsuccessful transaction. A node that performs more successful transactions has more trust value. The node that has a higher trust value has a higher probability to be selected as a $CA$ for a transaction. The trust reevaluation process is followed by the clustering process. The result shows the proposed approach can reduce ~38.5% response time and ~2.2% validation time as compared to infrastructure which does not implement clustering. Additionally, the proposed $CTB-PKI$ can be used in Blockchain 2.0 and Blockchain 3.0-related applications.

With the rapid transformation of the energy sector towards modern power systems represented by smart grids (SGs), microgrids (MG), and distributed generation, blockchain (BC) technology has shown the capability for solving security, privacy, and reliability challenges that hinder progress. Currently, the energy structure is forming a decentralized system that prioritizes customer satisfaction. BC technology undertakes power network stockholders in a secure energy market, transparent transactions, and fair competition and offers promising energy solutions. This paper is a comprehensive review of energy applications using BC integration. Firstly, we introduce the drivers of BC leverage that make it a potentially important component of the power network. Following that, we provide background information on BC and its application in areas other than the energy sector. Subsequently, we discuss studies and sort potential energy applications from various recent papers and surveys that have already adopted BC technology in the energy sector. Then, we summarize the pricing infrastructure for applying BC in the energy sector and identify the requirements to build it. Finally, energy security and privacy challenges based on BC are highlighted, along with potential drawbacks and concerns related to the pricing infrastructure.

Financial fraud cases are on the rise even with the current technological advancements. Due to the lack of inter-organization synergy and because of privacy concerns, authentic financial transaction data is rarely available. On the other hand, data-driven technologies like machine learning need authentic data to perform precisely in real-world systems. This study proposes a blockchain and smart contract-based approach to achieve robust Machine Learning (ML) algorithm for e-commerce fraud detection by facilitating inter-organizational collaboration. The proposed method uses blockchain to secure the privacy of the data. Smart contract deployed inside the network fully automates the system. An ML model is incrementally upgraded from collaborative data provided by the organizations connected to the blockchain. To incentivize the organizations, we have introduced an incentive mechanism that is adaptive to the difficulty level in updating a model. The organizations receive incentives based on the difficulty faced in updating the ML model. A mining criterion has been proposed to mine the block efficiently. And finally, the blockchain network is tested under different difficulty levels and under different volumes of data to test its efficiency. The model achieved 98.93% testing accuracy and 98.22% Fbeta score (recall-biased f measure) over eight incremental updates. Our experiment shows that both data volume and difficulty level of blockchain impacts the mining time. For difficulty level less than five, mining time and difficulty level has a positive correlation. For difficulty level two and three, less than a second is required to mine a block in our system. Difficulty level five poses much more difficulties to mine the blocks.

Owing to the sensitive nature of healthcare data, the aforementioned approach to transferring patient data to central servers creates serious security and privacy issues. In addition, blockchain distributed ledger technology has introduced immutable storage and decentralized data management capability, which handles a large number of distributed nodes of E-Healthcare transactions via a serverless network, but in a limited manner because of blockchain-enabled resources. In this scenario, the medical industries are concerned about constituting an innovation in health information preservation and exchanging service delivery protocols without the connectivity of an untrusted third-party infrastructure. In this study, we proposed a blockchain hyperledger fabric-enabled consortium architecture called BIoMT, which provides security, integrity, transparency, and provenance to health-related transactions and exchanges sensitive clinical information in a serverless peer-to-peer (P2P) secure network environment. A consensus is designed and created to reduce the rate of blockchain resource constraints on the Internet of Medical Things (IoMT). The privacy of individual health transactions before sharing is protected using the NuCypher Re-Encryption mechanism, which increases security and provides medical ledger integrity and transparency. Smart contracts are created and deployed to automate device registration, exchange transactions, and ledger preservation in immutable storage (filecoin) after cross verification and validation. The experimental results show that the proposed BIoMT reduces the computational cost by 26.13%, and the robust medical node generation increases to 60.37%. Thus, only 31.79% and 74.21% of IoMT-related information and serverless P2P network usage are maintained and saved, respectively.

With the proliferation of the blockchain technology ecosystems such as mining pools, crypto exchanges, full Bitcoin nodes, wallets, and pool protocol servers in recent years, the denial of service (DoS) attack vector has become more prevalent, and the attacks are targeted to the peer-to-peer networks and blockchain users. Despite blockchain enhancing security with decentralized design, secured distributed storage, and privacy, it is still vulnerable to new attack threats. If an attempted DoS is successful on blockchain, the impact is most likely massive given the fact that it is predominantly used for finance applications. An extensive account of the current state-of-the-art for possible DoS and corresponding mitigation techniques is not discussed in the existing research. This paper analyzes and categorizes the existing state-of-the-art DoS attack methods, detection techniques, and mitigation solutions targeting blockchain peer-to-peer networks as well as conventional network crypto exchanges. The review of the prior research shows that the blockchain ecosystem can be a target to successfully perform DoS attacks in the future, and technological advancements in blockchain are needed to mitigate potential attacks.

Random numbers are widely used in numerical computing, statistical simulation, random sampling, etc. At present, the mechanism for generating random numbers by computers is at risk of being attacked. The generated random numbers may be predicted in some cases,. However, current RNGs used in blockchain are not sufficient enough to handle attacks. Therefore, it is necessary to improve the security of random numbers. This paper improves the random number generator and designs a secure random number generator based on blockchain (BCsRNG). In practice, an encapsulated function algorithm of the secure random number is developed with the smart contract. Moreover, an API is provided to facilitate input and output. The experimental results show that the random numbers generated by BCsRNG are difficult to decipher and have higher randomness and security.