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The existing data transmission methods for industrial Internet of Things (IoT) ignore the tracking of abnormal nodes in the blockchain network, resulting in a low success rate of data transmission in industrial IoT, easy data loss, and low transmission efficiency. Therefore, a blockchain-based optimization method for industrial IoT data transmission is proposed. A B-Markov positioning model is constructed using neural networks to map IoT to consortium chains, and smart contracts are designed to eliminate abnormal nodes. Through dynamic optimization algorithms and centralized transmission models, combined with asymmetric encryption of blockchain, efficient data transmission is achieved. Experimental results show that this method has short-time consumption, high integrity, and a high success rate.

Blockchain, with its features of decentralization, immutability and security, has emerged as a revolutionary technology. However, the rapid growth of distributed ledgers leads to escalating storage costs, high transaction verification overhead and low throughput, limiting its scalability in broader applications. To address these challenges, this study proposes a novel blockchain transaction verification scheme, BBVC, specifically designed for smart contracts. BBVC leverages a vector commitment algorithm to generate transaction commitments and introduces a two-layer aggregation technique to compress node state data, facilitating efficient transaction validity proof aggregation and verification. A versioning mechanism is further incorporated to optimize proof update efficiency to sub-linear levels, while a new contract transaction verification logic accelerates transaction processing without compromising security. Experimental results demonstrate that the BBVC scheme maintains a constant proof size of 48 bytes and achieves millisecond-level proof generation and verification for large-scale transactions. Compared to Hyperproofs, BBVC enhances transaction aggregation efficiency by 250 times and verification efficiency by 22.5–27.5 times, significantly advancing blockchain scalability and performance.

In recent years, blockchain (BC) technologies have been increasing for data secrecy, system reliability and safety. BC is vulnerable to cyberattacks despite its utility. According to the statistics, attacks are rare, which differs greatly from the average. The goal of BC attack detection is to discover insights, patterns and anomalies within massive data repositories, it may benefit from deep learning. In this paper, the Prevention of Insider Attacks using Blockchain with Hierarchical Auto-associative Polynomial Convolutional Neural Network in Cloud Platform (PIS-BCNN-CP) is proposed. Here, the node authentication is handled by the smart contract. The aim of authorizing a node is to confirm that only a particular node has the possibility to submit and recover the information. Then Hierarchical Auto-associative Polynomial Convolutional Neural Network (HAAPCNN) is proposed to detect the Insider Attacks as Malicious and Normal. Generally, HAAPCNN does not agree with any optimization strategies to determine the optimal parameters for guaranteeing the exact detection of insider attacks. Hence, the Bear Smell Search Algorithm (BSSA) is exploited to optimize the weight parameters of a HAAPCNN. The BC Enabled Secure Data Storage depends on Proof of Continuous Work (PoCW) consensus BC algorithm is used. The proposed system is implemented and evaluated using performance metrics. The results provide higher accuracy, and lower False Negative Rate when compared with existing state-of-the-art methods.

Stepping into the era of big data, with more resources shared, the machine learning algorithms are more likely to derive a better solution, and those complicated computations can be finished in a shorter time. The existing works about multiparty computing mainly focus on how to perform the computation when the involved partners are given, but hardly consider the process during which the partners find each other. In this work, we proposed a framework of the multiparty computing network (MPCNet) for the agents propose and collaborate, where R3 Corda is harnessed to establish a blockchain platform where the convener is able to look for some other partners, and a crowdsourcing process is performed to verify the validity of the conveners proposal and the partners applications. Furthermore, a reward mechanism is proposed in order to motivate the verifiers to participate. Once all the agents joining the computing task are confirmed, they communicate with each other to perform the computing task, following the plan that is mentioned in the proposed smart contract. Experimental results demonstrated the feasibility, usability, and scalability of our proposed approach.

The traditional centralized logistics resources allocation method can no longer adapt to the new business model of decentralized e-commerce, requiring transaction security for all parties involved in the logistics process. Utilizing blockchain and smart contract technologies to build logistics resources allocation network foundation and edge computing technology to assist the resource-constrained transport nodes in implementing complex computation, this paper proposes a distributed logistics resources allocation chain (DLRAChain) concept and designs a DLRAChain network that supports independent decision-making, fair bidding, and secure allocation of interests for all resources allocation participants. The corresponding system models are constructed according to the different roles of DLRAChain participants. Furthermore, the logistics resources requester–provider negotiation process is formulated as a two-stage Stackelberg game. To resolve the optimization problem of the game, the iterative game algorithm (IGA) and distributed logistics resources allocation algorithm (DLRAA) are proposed. Finally, the utility of warehouse and transport nodes and reward of mobile edge computing (MEC) nodes are analyzed with experimental simulation results. The results demonstrate that the proposed models adequately address the DLRA problem, and that the proposed game and corresponding algorithms efficiently achieve the optimal strategy, saving the response time of resources allocation participants.

Blockchain technology apparently is a trivial innovation, but this technology has attracted huge investors in a very short period compared to other technologies, and it is still having a lot of potential applications. Smart contracts are making possible execution in an automated and safe way by using blockchain technology. Therefore, smart contracts are applied in this research for the expert system. This paper is about an expert system working with smart contracts and neural networks as the inference machine to decide on the sensors optimal distribution and taking actions when sensor readings are out of range: control lights, activating fire alarms, temperature alarms, etc. for all spaces (parks, schools, hospitals, etc.) in a smart city based on the needs, and likes of the expert system user. This expert system works using a blockchain structure on the EOSIO ecosystem with all data gathered by the sensors being saved in cloud online making internet of things environment and essential data saved in a blockchain node.

Due to the exponential growth in the use of systems with applications of blockchain technology, this paper develops a funding system, with donations and offers of shares, through the Ethereum platform with blockchain technology. Given the benefits that blockchain provides data protection and has high security, this paper offers a decentralized donation expert system using smart contracts that makes fully reliable donation systems to attract more funds to this urgent global health issue. Smart contracts provide faithful donations and meet the characteristics of being versatile, accessible, and sustainable to combat the COVID-19 pandemic. This expert system found the Merkle grid as an optimum method to work efficiently on the blockchain. The expert system proved to be steady and efficient by using an essential test dataset. A reliable donation system expects more donors and investors since a sustainable and reliable approach is always a milestone. The primary purpose of developing this system is to attract donors to bring down the COVID-19 pandemic by providing a faithful donation system.

Initial Crypto-Token Offering (ICO) strategy has worked so far to fund any project. In this scheme, the ICO launches a token playing the role of a stockholder’s share; the more the people buy tokens, the more the funding for the projects. The stakeholders also earn money if the project gains more reliability and more people buy this token. In other words, an ICO strategy works based on either selling or buying of tokens in the areas of security, utility, equity, etc. However, this paper’s focus is only on using oracles and Hyperledger, which means that there is no need to launch a token, instead it uses the network blockchain benefits, particularly oracles and the Ethereum virtual machine, i.e. not the Ethereum blockchain platform but its virtual machine. Since this is a proposal for governmental or corporate usage, the Hyperledger and oracles strategy fits better for this application. Funds for this use-case are gathered in the healthcare field, specifically to reduce the COVID-19 pandemic. The system’s reliability is the core for attracting investors and donors to fund the system if it guarantees that resources will get to the right destiny. DAPP is based on a smart contract aligned with the smart societies concept to ensure system sustainability.

The current Internet of Things (IoT) technology has entered a relatively mature development stage, and more and more IoT devices can readily access the Internet. However, along with this, the IoT system still faces fragile security of device nodes, easy data tampering, and low system stability. To this end, this paper proposes a smart contract-based security model for IoT systems. The proposal is based on the super ledger Fabric blockchain platform having decentralised, tamper-proof, and programmable features. These features achieve credible authentication of IoT device nodes on the one hand and tamper-proof data storage on the other hand. Further, with these features, we gain a trustworthy environment for enhancing the security of the whole IoT system.

With the trend for smart maintenance for the electric multiple unit (EMU), there is a critical need for cross-organisational data sharing amongst multiple stakeholders. Traditional centralised solutions may not ensure sufficient trust for data sharing. In the maintenance field, blockchain technology has been introduced to improve security and privacy. However, the current blockchain solutions for data sharing are solely based on public chain or consortium chain, which may have the limitation of low transaction processing rate. Moreover, multiple levels of decentralisation are required in cross-organisational data sharing. For the purpose of providing multiple types of ledger’s governance and a performance improvement, this paper presents a method for developing EMU maintenance data sharing solution based on double blockchain. The method is validated using a case study in Shanghai EMU depot. The proposed solution adopts practical byzantine fault tolerance (PBFT) as the consensus mechanism. Interplanetary file system (IPFS) is introduced to reduce the payload of big data storage.

The goal of SCM is to apply decisions, which end up with optimal organizational performance. Supply chain (SC) exists in service, manufacturing, and business organizations. Managing the reliability of processes and products in multi-stakeholder SC surroundings is a major challenge nowadays. As it provides protected control and traceability, trust, and immutability establishment among stakeholders with less-expensive solutions, blockchain has recently emerged as a most essential mechanism. This study critically evaluates 65 papers that discuss BCT in SCM, more specifically, an analysis of several performance measurements that are included in various papers is carried out. Additionally, a thorough analysis of the highest performance levels and various technical elements used in each task is conducted. Finally, the survey is extended with the identification of various research challenges, which may help the analysts to support improved future works on BCT in SCM. Chronological analysis is also performed.

The goal of online examination is to ensure convenience, scalability, expanded reach, and customization. Despite the popularity of online exams, there have been some demonstrations against using them. The existing system is vulnerable and faces failures like question paper leakage, answer deception, trying to forge scorecards, difficulty in ensuring the integrity and consistency of scorecards by the exam board, and so on. Blockchain technology is the greatest and unsurpassed option for continuous authentication, confidentiality, and reliability. A blockchain-based framework for an online examination system is proposed to collect, register, and maintain a growing list of records using cryptography. It is also a peer-to-peer system that manages or stores time-stamped transactions such that no one can alter them. The proposed model combines time lock and multi-signature techniques and ensures the encrypted questions are locked till the exam starts, candidates’ answers are not altered, and scorecards are not manipulated. The system is open to the public, and the system’s processes are transparent. The costs associated are analyzed with the suggested solution’s on-chain and off-chain evaluation.

Industrial Internet of Things (IIoT) advances the fault diagnosis of multi-tier edge computing systems into the realm of big data. However, a significant challenge arises in terms of privacy leakage due to the necessity for nodes in edge systems to share local private data. Additionally, a centralized architecture is susceptible to causing single-point failures in edge systems. Moreover, the fault data from nodes in IIoT edge systems are often nonindependent and nonidentically distributed (nonIID), posing difficulties for convergence. Furthermore, there is a lack of corresponding defenses to prevent malicious node fault attacks. To tackle these challenges, this work introduces a fault diagnosis framework and method for multi-tier edge computing systems based on blockchain smart contracts. The framework primarily adopts a decentralized model to ensure the privacy and security of fault data in multi-tier edge systems. Within this framework, a feature comparison loss function is designed to address the nonIID nature of faults. Additionally, a Byzantine fault-tolerant method is developed to prevent fault threats. Furthermore, we design an incentive method based on reputation to assess the rewards that nodes should receive. Experiments demonstrate that the proposed method achieves robust overall performance without compromising the privacy of local data.

The prosperity of Bitcoin has given rise to widespread attention and in-depth research on blockchains. The blockchain provides the fundamental technology for the decentralization, openness, security, independence, anonymity, integrity, and authenticity of diversified applications. The literature selected are mainly from IEEE papers and conference proceedings. This paper deeply analyzes the basic features and categories of blockchain and delineates the practical applications. The aim is to find the development prospects of blockchains through analysis of existing applications and technologies.

Smart Contracts are commonly considered to be an important component or even a key to many business solutions in an immense variety of sectors and promises to securely increase their individual efficiency in an ever more digitized environment. Introduced in the early 1990s, the technology has gained a lot of attention with its application to blockchain technology to an extent, that can be considered a veritable hype. Reflecting the growing institutional interest, this intertwined exploratory study between statistics, information technology, and law contrasts these idealistic stories with the data reality and provides a mandatory step of understanding the matter, before any further relevant applications are discussed as being ‘factually’ able to replace traditional constructions. Besides fundamental flaws and application difficulties of currently employed Smart Contracts, the technological drive and enthusiasm backing it may however serve as a jump-off board for future developments thrusting well in the presently unshakeable traditional structures.

Blockchain technology has been hailed as the technology of the future, not only for banking and finance but also for supply chain management and logistics. As lack of transparency in global supply chains is a major risk for sustainability, blockchain offers an attractive solution in the form of a reliable platform to create transparency and risk management. Not considering the nascent stage of the technology, companies are investing millions of dollars into blockchain solutions for many business problems including that of supply chains. However, blockchain-enabled networkwide transparency and visibility also inject new dynamics into supply chains through introduction of structural changes like redefining what is organizational boundary, creating new resources, and a new transactional economy for supply chain management. The structural changes also create a fundamental need for organizations in a supply network to adapt their supply chain processes to this new and emerging supply chain structural dynamics for organizational and network-level efficiency and sustainability. For efficient restructuring of the supply chain processes, organizations need clarity regarding what should be the focus of their processes for creating sources of competitive advantage.

Using topic modeling, a text mining technique, this work finds the focus areas of supply chain processes in organizations with examples of successful application of blockchain technology. Apart from how these organizations have integrated the strengths of blockchain in their supply chain processes, we also provide an exhaustive theoretical explanation about how firms can create sources of competitive advantage from blockchain technology. Identification of the focus areas will also help operations and supply chain managers planning to implement blockchain technology and devise plans for data-centric decision-making for their SCM processes for efficiency.

Traditional paying methods require the execution of payments before services, which may not satisfy the needs of modern consumers anymore. In this paper, a novel service payment system (SPS) is proposed for supporting different kinds of customers, including people, machines or devices, where paying for a service will not take place until its completion. The SPS operates by using smart contracts, which are self-executing programs fulfilling the underlying contract terms between a buyer and a seller without involving any third party. The execution of smart contracts takes place on a blockchain platform, using both in- and outbound events. In addition, the use of Internet of Things (IoT) together with the blockchain technologies allows us to do interactive data exchange through sensors without human interventions. Benefiting from the strengths of cryptography and hash functions, the SPS can hence meet the requirements of the consumers, resulting in an improved payment system. The book of a train ticket is taken as an example to demonstrate that the combination of smart contracts, a blockchain platform and cryptography will create an upgraded payment system capable of serving and satisfying the mindset and requirements of current and future customers in the Big and Fast Data era.

The explosion of NFT artwork has enabled it to start a high-speed development model. As an emerging thing, NFT artwork has attracted widespread attention at home and abroad. This article sorts out the development of NFT artworks, analyzes the technical advantages of blockchain, and also reveals that there are still existing problems such as hype and institutional irregularity in the NFT artwork market. And based on the development status of NFT artworks, it will think and look forward to its future development trend towards the Metaverse.

In order to solve the trust problem in China’s online shared mobility, blockchain technology is used to build a trust mechanism to guide and encourage users’ honest transactions through smart contracts. Then, the agent model is built by AnyLogic software to simulate the behavior of users participating in the transaction. The results show that the willingness of users to perform the contract can be effectively improved under the incentive of the trust mechanism. Finally, some suggestions are put forward to ensure that the trust mechanism can be effectively applied.

Traditional transaction systems within auto service chains exhibit several shortcomings, which are untraceable, opaque, and inefficient. To mitigate these challenges, a transaction system based on a consortium blockchain for the auto service value chain is devised to guarantee transaction authenticity and reliability. Initially, a smart contract is a computer protocol that is automatically executed. It integrates into the Byzantine fault-tolerant IBFT consensus algorithm to accomplish transactions in real time and enhance a higher degree of security. Subsequently, the IBFT is fine-tuned to enhance the consortium blockchain performance. In addition, multiple primary nodes execute the IBFT algorithm concurrently via multithreading to mitigate latency and improve throughput. Lastly, experimental results demonstrate that IBFT notably surpasses other consensus algorithms in both throughput and latency.