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Blockchain technology has several characteristics, including decentralisation, non-tampering, and cryptographic algorithms. These characteristics are the focus of research for distributed group network authentication. However, the existing blockchain has high arithmetic requirements and low efficiency, which limits its application in UAV swarm group networks. Therefore, a lightweight blockchain UAV swarm identity authentication system has been designed. A model for a blockchain-based authentication system for UAV swarms is constructed. The system’s blockchain consensus algorithm, Practical Byzantine Fault Tolerance (PBFT), has been improved. A new lightweight trusted PBFT consensus algorithm, Lightweight Trusted PBFT (LTPBFT), has been proposed. This algorithm reduces the reputation reward and punishment mechanism and the voting mechanism by introducing the probability of Byzantine nodes acting as master nodes. The algorithm achieves this by introducing a reputation reward and punishment mechanism and a voting mechanism. The consistency protocol process has been optimised to simplify both its Prepare and Commit phases. This reduces communication complexity and achieves a lightweight authentication system. Simulation results demonstrate that the LTPBFT consensus algorithm is more efficient and stable than PBFT in terms of communication overhead, throughput, consensus delay and security. [ABSTRACT FROM AUTHOR]

Blockchain is a distributed system that maintains a public ledger using consensus protocols. The practical byzantine fault tolerance (PBFT) protocol is vital in consortium blockchains. However, there are still problems with system centralization, consensus inefficiency, high communication complexity, and other issues in PBFT and its improved algorithms. These restrict its widespread application in realistic environments. In this work, we propose a grouping-classification practical byzantine fault tolerance (GC-PBFT) improvement algorithm based on credit. First, we construct a credit model to dynamically evaluate the credit of nodes and rank them in descending order. Second, a grouping-classification model is built to divide nodes into three subgroups. Then, primary node, supervisory node, and consensus node are selected from these subgroups randomly, ensuring that the node roles are constantly updated to improve the security and fairness of the system. Additionally, the consensus process is simplified to improve the efficiency of the consensus and reduce communication complexity. Finally, experiments show that compared with PBFT and its improved algorithms, the GC-PBFT algorithm reduces communication complexity from O (N 2) to O(N). In addition, active and honest nodes can obtain higher credit, which lowers the possibility of malicious nodes being selected as consensus nodes, leading to higher consensus efficiency and better decentralization characteristics for the system. [ABSTRACT FROM AUTHOR]

In a smart grid, collected electricity consumption periodically from smart meters allow entities to bill the customers, power company to operate the grid successfully, and users to control the use of their appliances. However, energy consumptions of users should be protected since the data provides the user's daily habit that an adversary uses the data to extract useful information about the users. Moreover, users' identities should not be disclosed to untrusted entities since the untrusted entities map identities to their real identities. In this paper, we propose a system that protects users' data privacy using multi-pseudorandom identities and a randomization technique. Moreover, the proposed work provides fast authentication for smart meters to send their readings to data aggregators. Furthermore, the proposed work is based on consortium blockchain to eliminate a single point of failure and provides transparency of messages and operations. In addition, we use dynamic billing and pricing mechanism for the users to see their bills. [ABSTRACT FROM AUTHOR]

Blockchain technology has several characteristics, including decentralisation, non-tampering, and cryptographic algorithms. These characteristics are the focus of research for distributed group network authentication. However, the existing blockchain has high arithmetic requirements and low efficiency, which limits its application in UAV swarm group networks. Therefore, a lightweight blockchain UAV swarm identity authentication system has been designed. A model for a blockchain-based authentication system for UAV swarms is constructed. The system’s blockchain consensus algorithm, Practical Byzantine Fault Tolerance (PBFT), has been improved. A new lightweight trusted PBFT consensus algorithm, Lightweight Trusted PBFT (LTPBFT), has been proposed. This algorithm reduces the reputation reward and punishment mechanism and the voting mechanism by introducing the probability of Byzantine nodes acting as master nodes. The algorithm achieves this by introducing a reputation reward and punishment mechanism and a voting mechanism. The consistency protocol process has been optimised to simplify both its Prepare and Commit phases. This reduces communication complexity and achieves a lightweight authentication system. Simulation results demonstrate that the LTPBFT consensus algorithm is more efficient and stable than PBFT in terms of communication overhead, throughput, consensus delay and security.

Abstract A large number of nodes, and significant system overhead are among the challenges. To tackle these problems, a new PBFT technique known as trace-PBFT (t-PBFT) is being contemplated for adoption in the food supply chain. The PBFT algorithm, short for Practical Byzantine Fault Tolerance, serves as the fundamental algorithm. The linkages throughout the supply chain may be categorized into three primary groups. As a response to the continuing discussion over the amount of data, the status of each node is continuously updated in real time. This metric is utilized to evaluate the dependability of the principal node and to analyze the overall performance of the nodes. To minimize the amount of data transmitted between nodes, we optimized the consensus process of the first algorithm. The distinct attributes of offering collaborative food technology were considered throughout this procedure. Experimental evidence indicates that the t-PBFT approach outperforms the PBFT algorithm in terms of throughput, request delay, and information overhead. An architectural paradigm is proposed by integrating the t-PBFT algorithm with a federated network. This model was developed in response to the distinct demands of the food supply chain. This model effectively captures data at each stage of the food supply chain to ensure information tracking while preserving the safety of the food technology flow process.

As the core of blockchain technology, the consensus mechanism ensures the safe and stable operation of the blockchain system. According to the more complex traceability of data when sharing cross-system and cross-chain, the paper proposes the Layered Cross-Chain Practical Byzantine Fault Tolerance (LC-PBFT) suitable for cross-chain scenarios to ensure the secure traceability of data in the process of cross-chain data traceability. Firstly, in a single chain, the initial reputation value is set according to the success rate and efficiency of the nodes in the historical transactions in the chain, the reputation ranking of the nodes in the chain is realized by the improved PageRank algorithm, and delegated nodes are selected to participate in the cross-chain consensus based on reputation ranking. Then, the forest topology is sorted according to the contribution of the consensus nodes in the cross-chain system, and the consensus results from the child nodes are quickly verified by aggregation signature, which prevents the parent node from tampering with the consensus results of the child nodes. Meanwhile, the consensus process between the sibling nodes in the same layer and the view switching protocol when the master node fails are given. Finally, the performance of the LC-PBFT consensus algorithm is analyzed, and its advantages in performance such as throughput are verified by simulation. Compared with the Practical Byzantine Fault Tolerance (PBFT) algorithm, the consensus latency of the LC-PBFT consensus algorithm is reduced by 50.17%, and the throughput is improved by 19.37%. [ABSTRACT FROM AUTHOR]

Due to limited communication, computing resources, and unstable environments, traditional cold chain traceability systems are difficult to apply directly to marine cold chain traceability scenarios. Motivated by these challenges, we construct an improved blockchain-based cold chain traceability system for marine fishery vessels. Firstly, an Internet of Vessels system based on the Iridium Satellites (IoV-IMS) is proposed for marine cold chain monitoring. Aiming at the problems of low throughput, long transaction latency, and high communication overhead in traditional cold chain traceability systems, based on the Practical Byzantine Fault Tolerance (PBFT) consensus algorithm, a Node-grouped and Reputation-evaluated PBFT (NR-PBFT) is proposed to improve the reliability and robustness of blockchain system. In NR-PBFT, an improved node grouping scheme is designed, which introduces a consistent hashing algorithm to divide nodes into consensus and candidate sets, reducing the number of nodes participating in the consensus process, to lower communication overhead and transaction latency. Then, a reputation evaluation model is proposed to improve the node selection mechanism of NR-PBFT. It enhances the enthusiasm of nodes to participate in consensus, which considers the distance between fishery vessels, data size, and refrigeration temperature factors of nodes to increase throughput. Finally, we carried out experiments on marine fishery vessels, and the effectiveness of the cold chain traceability system and NR-PBFT were verified. Compared with PBFT, the transaction latency of NR-PBFT shortened by 81.92%, the throughput increased by 84.21%, and the communication overhead decreased by 89.4%. [ABSTRACT FROM AUTHOR]

A large number of nodes, and significant system overhead are among the challenges. To tackle these problems, a new PBFT technique known as trace-PBFT (t-PBFT) is being contemplated for adoption in the food supply chain. The PBFT algorithm, short for Practical Byzantine Fault Tolerance, serves as the fundamental algorithm. The linkages throughout the supply chain may be categorized into three primary groups. As a response to the continuing discussion over the amount of data, the status of each node is continuously updated in real time. This metric is utilized to evaluate the dependability of the principal node and to analyze the overall performance of the nodes. To minimize the amount of data transmitted between nodes, we optimized the consensus process of the first algorithm. The distinct attributes of offering collaborative food technology were considered throughout this procedure. Experimental evidence indicates that the t-PBFT approach outperforms the PBFT algorithm in terms of throughput, request delay, and information overhead. An architectural paradigm is proposed by integrating the t-PBFT algorithm with a federated network. This model was developed in response to the distinct demands of the food supply chain. This model effectively captures data at each stage of the food supply chain to ensure information tracking while preserving the safety of the food technology flow process. [ABSTRACT FROM AUTHOR]

In today's technology landscape, the Internet of Things (IoT) has gained significant momentum due to its wide-ranging applications across diverse devices. However, the integration of IoT faces several daunting challenges, with security emerging as a paramount concern. To address this, blockchain technology has emerged as a decentralized and foundational solution for mitigating these integration obstacles. This research introduces a reliable blockchain-based consensus PIoT (Proof of Internet of Things) specifically for IoT networks, aiming to overcome the attacks encountered during data communication. The proposed blockchain system excels in effectively identifying IoT devices, authenticating their legitimacy, and dynamically assigning addresses based on demand. Additionally, it offers secure communication capabilities among IoT devices, providing robust protection against various attacks. The performance of PIoT is superior than that of certain traditional techniques. As it comes to the efficient use of available time, PIoT displays improvements of 74.7 and 96.8%, respectively, as compared to LPBFT and hybrid blockchain. In addition to this, the level of consensus security offered by PIoT is 15% higher than that offered by DAC4SH. PIoT has impressive scalability in terms of time consumption, the fraction of successful consensus attempts, and transaction throughput even when the network size and the number of malicious nodes face exponential variations. [ABSTRACT FROM AUTHOR]

Finance, supply chains, healthcare, and energy have an increasing demand for secure transactions and data exchange. Permissioned blockchains fulfilled this need thanks to the consensus protocol that ensures that participants agree on a common value. One of the most widely used protocols in private blockchains is the Practical Byzantine Fault Tolerance (PBFT), which tolerates up to one-third of Byzantine nodes, performs within partially synchronous systems, and has superior throughput compared to other protocols. It has, however, an important bandwidth consumption: 2N(N−1) messages are exchanged in a system composed of N nodes to validate only one block.It is possible to reduce the number of consensus participants by restricting the validation process to nodes that have demonstrated high levels of security, rapidity, and availability. In this paper, we propose the first database that traces the behavior of nodes within a system that performs PBFT consensus. It reflects their level of security, rapidity, and availability throughout the consensus. We first investigate different Single-Task Learning (STL) techniques to classify the nodes within our dataset. Then, using Multi-Task Learning (MTL) techniques, the results are much more interesting, with classification accuracies over 98%. Integrating node classification as a preliminary step to the PBFT protocol optimizes the consensus. In the best cases, it is able to reduce the latency by up to 94% and the communication traffic by up to 99%.

Considering the malicious risks associated with diverse terminals in the industrial Internet of things (IIoT), a practical Byzantine fault tolerant (PBFT) efficient consensus algorithm based on credit score and dynamic double layer (CD-PBFT) was proposed to meet the requirements of high efficiency and security fault tolerance in the consensus process. The participation of good nodes in the consensus and the removal of faulty nodes were ensured by the credit score model. The parallelism of transaction verification and read write operations was achieved through the implementation of a double layer architecture. Nodes with high credit were randomly selected as the master node by the adaptive master node algorithm, ensuring its security. Experimental results show that CD-PBFT not only can maintain the safety and liveness of the consensus algorithm but also can reduce network delay by 34.8% and increase throughput by 25.2% compared with PBFT, which meets the double requirements of efficiency and security fault tolerance.

A blockchain is a decentralized digital network system consisting of multiple blocks connected in a chain. Each block comprises multiple transactions and is linked to the previous block through its hash value. The hash values are calculated using the active transactions within each block and the hash value of the preceding block. A positive impact can be made by combining blockchain technology with the healthcare sector. The consensus mechanism is the key protocol for implementing agreements in the blockchain. This paper proposes a combined RSA (Rivest–Shamir–Adleman) cryptography algorithm with a novel consensus protocol IPBFT (Improved Practical Byzantine Fault Tolerance) in the Hyperledger Fabric platform, for a patient-centered approach using blockchain technology in the healthcare sector. It ensures the reliability and integrity of transactions and prevents malicious nodes from disrupting the network. The Hyperledger Fabric platform is used to provide transparency, security, and trust in the blockchain. Performance metrics such as latency, throughput, scalability, and comparative analysis for the proposed algorithm Improved Practical Byzantine Fault Tolerance (IPBFT) and existing Practical Byzantine Fault Tolerance (PBFT) algorithms have been evaluated to achieve enhanced results. The proposed algorithm solves many problems associated with existing Practical Byzantine Fault Tolerance solutions and improves efficiency and security in the healthcare sector. [ABSTRACT FROM AUTHOR]

In recent years, cloud manufacturing has brought both opportunities and challenges to the manufacturing industry. Cloud manufacturing enables global manufacturing resources to be unified and shared, thus breaking down geographical constraints to enhance the level and efficiency of manufacturing. However, with the explosive growth of manufacturing resources and user demands, traditional cloud manufacturing platforms will face problems of insufficient computility, lack of real‐time data and difficulties in securing user privacy during the service selection process. In this article, a blockchain‐based decentralized cloud manufacturing service selection method is proposed, where the computility resource is deployed in multiple distributed nodes rather than the traditional centralized cloud manufacturing platform to solve the problem of insufficient computility. The credibility of the users is evaluated based on their performance on the contract and the PBFT consensus algorithm is improved based on the credibility of the users. In addition, a tri‐chain blockchain data storage model is designed to ensure the security, real‐time and transparency of data in the cloud manufacturing service selection process. The experimental results show that the method both speeds up service selection process and improves the quality of service selection results, and achieves a significant increase in manufacturing efficiency. [ABSTRACT FROM AUTHOR]

This paper proposed a dual-layer consensus algorithm (DL_RBFT) based on the enhanced Raft and practical Byzantine fault tolerance (PBFT) consensus algorithms to address scalability issues, excessive communication overhead, and challenges in large-scale network node environments in use within consortium blockchains. Initially, it divided blockchain nodes into several groups to form a lower-layer consensus network. Then, leaders from these groups constituted an upper-layer consensus network, creating a dual-layer consensus structure. In the lower-layer consensus network, it improved Raft consensus algorithm by introducing supervision and reputation mechanisms, while the leader election process introduced ant colony optimization to maintain high efficiency. In the upper-layer consensus network, it utilized the PBFT consensus algorithm for consensus. The enhanced Raft consensus algorithm exhibited resistance to Byzantine node attacks, enhancing the algorithm’s security. Experimental results indicate that compared to traditional PBFT consensus algorithms, DL_RBFT reduces consensus latency by two orders of magnitude and improves throughput by one order of magnitude in a 100-node scenario. In comparison to other enhanced algorithms, DL_RBFT demonstrates significant advantages. Therefore, DL_RBFT consensus algorithm exhibits strong scalability and can be widely applied in various consortium blockchain scenarios. [ABSTRACT FROM AUTHOR]

Practical Byzantine Fault Tolerance (PBFT), the widest-used consensus algorithm in the alliance blockchain, suffers from high communications complexity and relatively low scalability, making it difficult to support large-scale networks. To overcome these limitations, we propose a secure and scalable consensus algorithm, Vague Sets-based Double Layer PBFT (VSDL-PBFT). Roles and tasks of consensus nodes are redesigned. Three-phase consensus process of the original PBFT is optimized. Through these approaches, the communication complexity of the algorithm is significantly reduced. In order to better fit the complexity of voting in the real world, we use a vague set to select primary nodes of consensus groups. This can greatly reduce the likelihood of malicious nodes being selected as the primary nodes. The experimental results show that the VSDL-PBFT consensus algorithm improves the system’s fault tolerance, it also achieves better performance in algorithm security, communications complexity, and transaction throughput compared to the baseline consensus algorithms. [ABSTRACT FROM AUTHOR]

In a blockchain network, a rule set called consensus mechanism is used to create and finalize a block. In a proof-of-stake (PoS), consensus-based blockchain network, nodes become validators, minters, or stakeholders' nodes to complete the consensus mechanism. In these networks, when a node becomes a validator node, its details need to be saved because the details of the validators are used in the network for many important decisions, such as selecting block proposers for the consensus process. In this paper, we present Sea Shield, which uses a validator chain to save a node's information when it becomes a validator or leaves its responsibility as a validator in the PoS-based blockchain network. The validator chain is a blockchain that can run with the main chain of a PoS-based blockchain. The internal features of the validator chain are similar to those of the blockchain. We designed and simulated a consensus mechanism to create and finalize the block for the validator chain with no forks. We present a process by which a node may join or unjoin as a validator in a PoS-based blockchain network to improve the overall security of the main chain-consensus process. [ABSTRACT FROM AUTHOR]

Aiming at the problems in the Practical Byzantine Fault Tolerance Algorithm (PBFT), such as large communication overhead, high delay and inability to reasonably divide according to the differences of scenarios and devices to meet the multi-scenario application of Internet of Things (IoT) in the integration of IoT and blockchain, this paper proposed an improved Practical Byzantine Fault Tolerance consensus algorithm based on Comprehensive Evaluation (CE-PBFT). Firstly, it conducted comprehensive evaluation of nodes based on the weighted performance and reputation value to screen out nodes that meet the needs of specific scenarios; after that, it conducted clustering based on the comprehensive evaluation of nodes to form a two-layer network architecture; finally, it divided the consensus process into sub-cluster consensus and main cluster consensus. The experimental results show that CE-PBFT has high fault tolerance and scenario adaptability, and when the number of scenario nodes reaches 100, it respectively has 93.9% and 87.8% performance optimisation over PBFT in terms of communication overhead and consensus delay. [ABSTRACT FROM AUTHOR]

This paper addresses scalability limitations in blockchain systems for supporting multi-asset transactions by proposing a master-slave multi-chain architecture. The underlying consensus protocol, called MS-PBFT, utilizes pre-broadcast and threshold signatures to reduce communication overhead. Experimental results demonstrate that MS-PBFT achieves substantially higher transaction throughput and lower latency compared to PBFT consensus, showcasing efficiency gains. This work provides a useful blockchain structure and consensus approach to enable classification of digital assets and concurrent processing across chains.

Blockchain has shown significant potential as a key enabler in privacy and security in the forthcoming 6G wireless network, due to its distributed and decentralized characteristics. Practical Byzantine fault tolerance (PBFT) emerges as a prominent technology for deployment in wireless networks due to its attributes of low latency, high throughput, and minimal computational requirements. However, the high complexity of communication is the bottleneck of PBFT for achieving high scalability. To tackle this problem, this paper proposes a novel framework of PBFT, where the inter-node communication during the normal case operation is completed through base stations. The uplink and downlink communication between the base station and nodes are modelled based on the signal-to-interference-plus-noise ratio (SINR) threshold. A novel ‘timeout’ mechanism is incorporated to reduce the communication complexity. The performance is evaluated by metrics including consensus success probability, communication complexity, view change delay, view change occurrence probability, consensus delay, consensus throughput and energy consumption. The numerical results show that the proposed scheme achieves higher consensus success probability and throughput, lower communication complexity and consensus delay compared to the conventional PBFT. The results of view change delay and view change occurrence probability and the optimal configuration provide analytical guidance for the deployment of wireless PBFT networks.

Voice over Internet Protocol (VoIP) networks are vulnerable to caller-ID (caller-identification) spoofing attacks due to the open nature of Session Initiation Protocol (SIP) signaling. Caller-ID spoofing is a critical security threat in modern telecommunication systems, allowing attackers to impersonate legitimate callers and gain access to sensitive information. While these attacks pose a significant threat to the telecom and financial industries, the existing solutions are limited to only closed-circuit options for subscribers of the same service provider. In this paper, we present a novel blockchain-based solution to effectively prevent caller-ID spoofing attacks in real time. Our approach employs a low-latency consensus algorithm to manage and verify end-to-end the caller-ID information of Internet Service Providers (ISPs) and institutions. We propose a two-step verification process, in which the accuracy and integrity of Automatic Number Identification (ANI) information is verified at different stages of the call. The proposed solution initiates a renewal of the ISP registration on every caller-ID change, making it unaffected by unusual situations such as roaming, the use of an IP-PBX (Internet Protocol Private Branch Exchange), or the use of a VPN (Virtual Private Network). We also discuss the proposed solution’s feasibility and potential deployment issues, including its integration into existing RFC (Request for Comments) efforts and the necessary regulations for service providers to demonstrate compliance. Furthermore, we address future research directions, such as handling complex call scenarios such as call forwarding and teleconference calls. Our approach not only improves the security of telecommunication systems but also provides an efficient and scalable solution to prevent caller-ID spoofing attacks.

Practical Byzantine Fault Tolerance (PBFT), a classic consensus algorithm in blockchain technology, is extensively used in consortium blockchain networks. However, it is challenged by issues such as low consensus efficiency, poor scalability, inability to guarantee throughput with large-scale node access, and complex communication processes. To solve these problems, this paper proposes an improved PBFT consensus mechanism based on credit scoring and aggregated signatures, i.e., the CA-PBFT algorithm. First, the algorithm designs the node credit scoring mechanism, adds the coordination node in the original algorithm model, stipulates the node state and functional limitations, and realizes the dynamic joining and exiting of the nodes, to solve the low efficiency of the PBFT algorithm during the consensus process and the problem of not supporting the dynamic joining and exiting of the nodes; at the same time, the signature scheme based on the BLS aggregated signature is designed, which reduces the length of the signature and simplifies the signing process, to solve the problem of the node’s signature taking up too much space during the consensus process, which affects the efficiency of the signature validation as well as the efficiency of the signature construction. Experimental results show that this consensus mechanism enables an efficient, secure, and scalable consensus process with low resource and computational costs.

Medical data are an intangible asset and an important resource for the entire society. The mining and application of medical data can generate enormous value. Currently, medical data management is mostly centralized and heavily relies on central servers, which are prone to malfunctions or malicious attacks, making it difficult to form a consensus among multiple parties and achieve secure sharing. Blockchain technology offers a solution to enhance medical data security. However, in medical data security sharing schemes based on blockchain, the widely adopted Practical Byzantine Fault-Tolerant (PBFT) algorithm encounters challenges, including intricate communication, limited scalability, and the inability to dynamically add or remove nodes. These issues make it challenging to address practical requirements effectively. In this paper, we implement an efficient and scalable consensus algorithm based on the PBFT consensus algorithm, referred to as Me-PBFT, which is more suitable for the field of medical data security. First, we design a reputation evaluation model to select more trusted nodes to participate in the system consensus, which is implemented based on a sigmoid function with adjustable difficulty. Second, we implement the division of node roles to construct a dual consensus layer structure. Finally, we design a node dynamic join and exit mechanism on the overall framework of the algorithm. Analysis shows that compared to PBFT and RAFT, ME-PBFT can reduce communication complexity, improve fault tolerance, and have good scalability. It can meet the need for consensus and secure sharing of medical data among multiple parties. [ABSTRACT FROM AUTHOR]

Due to limited communication, computing resources, and unstable environments, traditional cold chain traceability systems are difficult to apply directly to marine cold chain traceability scenarios. Motivated by these challenges, we construct an improved blockchain-based cold chain traceability system for marine fishery vessels. Firstly, an Internet of Vessels system based on the Iridium Satellites (IoV-IMS) is proposed for marine cold chain monitoring. Aiming at the problems of low throughput, long transaction latency, and high communication overhead in traditional cold chain traceability systems, based on the Practical Byzantine Fault Tolerance (PBFT) consensus algorithm, a Node-grouped and Reputation-evaluated PBFT (NR-PBFT) is proposed to improve the reliability and robustness of blockchain system. In NR-PBFT, an improved node grouping scheme is designed, which introduces a consistent hashing algorithm to divide nodes into consensus and candidate sets, reducing the number of nodes participating in the consensus process, to lower communication overhead and transaction latency. Then, a reputation evaluation model is proposed to improve the node selection mechanism of NR-PBFT. It enhances the enthusiasm of nodes to participate in consensus, which considers the distance between fishery vessels, data size, and refrigeration temperature factors of nodes to increase throughput. Finally, we carried out experiments on marine fishery vessels, and the effectiveness of the cold chain traceability system and NR-PBFT were verified. Compared with PBFT, the transaction latency of NR-PBFT shortened by 81.92%, the throughput increased by 84.21%, and the communication overhead decreased by 89.4%.

The consortium blockchain has been widely applied in various fields such as agricultural product traceability, supply chain management, and logistics transportation. As an indispensable component of a consortium blockchain, the consensus algorithm ensures the consistency and trustworthiness of each node in the network. However, existing consensus algorithms in large-scale consortium blockchain scenarios suffer from low system throughput and high latency due to the complexity of communication processes, rendering them impractical for real-world use. To address these issues, this paper proposes a novel consensus algorithm called credit evaluation-based practical Byzantine fault tolerance (CE-PBFT). This algorithm designs a new node credit evaluation model that considers node completion rate, consensus decay, and node behavior. It effectively measures and reflects the specific reliability status of nodes during system operation, thereby enhancing system reliability and security. Additionally, the paper introduces the innovative use of decision tree algorithms to analyze network node behavior and simplifies the existing consensus protocol. Nodes are categorized as excellent, good, ordinary, or poor based on the classification results, and non-Byzantine nodes are dynamically selected accordingly. This greatly improves the overall efficiency of the system. The performance of CE-PBFT is validated through experiments and compared with PBFT, G-PBFT, RBFT, WBFT and PPoR. Experimental results demonstrate that in large-scale consortium scenarios, CE-PBFT significantly improves system throughput, effectively reduces transaction latency and communication overhead, and outperforms the compared protocols.

Since the Practical Byzantine Fault Tolerance (PBFT) consensus mechanism can avoid the performance bottleneck of blockchain systems caused by Proof of Work (PoW), it has been widely used in many scenarios. However, in the blockchain system, each node is required to back up all transactions and block data of the system, which will waste a lot of storage resources. It is difficult to apply to scenarios with limited storage resources such as unmanned aerial vehicle networks and smart security protection; thus, it is often used in small-scale networks. In order to deploy PBFT-based blockchain systems in large-scale network scenarios, we propose an ultra-low storage overhead PBFT consensus (ULS-PBFT), which groups nodes hierarchically to limit the storage overhead within the group. In this paper, we first propose an optimal double-layer PBFT consensus from the perspective of minimizing the storage overhead, and prove that this consensus can significantly reduce the storage overhead. In addition, we also investigate the superiority of ULS-PBFT in terms of communication overhead while setting the security threshold in the presence of the possibility of Byzantine nodes. The simulation results demonstrate the advantages of ULS-PBFT. Then, we extend such grouping idea to the blockchain system with X-layer PBFT and analyze its storage and communication overhead. Finally, the node grouping strategy of double-layer PBFT is studied for four application scenarios when the performance of storage overhead, communication overhead, and security are considered comprehensively.

Based on the practical Byzantine fault tolerance algorithm (PBFT), a grouped multilayer PBFT consensus algorithm (GM-PBFT) is proposed to be applied to digital asset transactions in view of the problems with excessive communication complexity and low consensus efficiency found in the current consensus mechanism for digital asset transactions. Firstly, the transaction nodes are grouped by type, and each group can handle different types of consensus requests at the same time, which improves the consensus efficiency as well as the accuracy of digital asset transactions. Second, the group develops techniques like validation, auditing, and re-election to enhance Byzantine fault tolerance by thwarting malicious node attacks. This supervisory mechanism is implemented through the Raft consensus algorithm. Finally, the consensus is stratified for the nodes in the group, and the consensus nodes in the upper layer recursively send consensus requests to the lower layer until the consensus request reaches the end layer to ensure the consistency of the block ledger in the group. Based on the results of the experiment, the approach may significantly outperform the PBFT consensus algorithm when it comes to accuracy, efficiency, and preserving the security and reliability of transactions in large-scale network node digital transaction situations. [ABSTRACT FROM AUTHOR]

In today's data-driven world, efficient and secure cross-institution information-sharing is an urgent challenge. Traditional information-sharing methods based on access controlling often suffer from issues such as privacy breaches and high communication complexity. To address this issue, this paper proposes a cross-institution information-sharing solution based on a consortium blockchain, in which it combines on-chain transaction consensus with off-chain institution storage, thereby facilitating collaboration among nodes from different institutions on the blockchain. To enhance the efficiency and security of transactions on the blockchain, we also introduce a dynamic and adaptive Practical Byzantine Fault Tolerance (DA-PBFT) consensus protocol, which permits nodes to dynamically join and exit the blockchain network, consequently improving network scalability. Through a reputation mechanism, we swiftly identify and remove faulty and malicious nodes, enhancing the trustworthiness of nodes in the information-sharing network based on consortium blockchain, thereby improving consensus efficiency. We have also employed encryption techniques to enhance the privacy and integrity of data during the process of cross-institution information sharing. A comprehensive analysis of the communication complexity in the information-sharing network confirms the effectiveness and security of our proposed solution. We offer a unique solution to improve the efficiency and security of cross-institution information-sharing while ensuring data integrity and privacy. By addressing the challenges of privacy breaches and high communication complexity in information sharing, we establish a foundation for secure cross-institution data exchange. [ABSTRACT FROM AUTHOR]

The consensus algorithm, as one of the cores of blockchain technology, plays a very critical role. As one of the mainstream consensus methods, PBFT has the advantages such as low energy consumption and large throughput. However, the traditional PBFT algorithm also has disadvantages, such as high network bandwidth occupation, for PBFT needs broadcasting information for all nodes in stage 3 and 4; limited expandability. With the increase of nodes, the bandwidth overhead of the blockchain network will increase significantly, which leads to a decrease in throughput, so that cause a crash of the blockchain network. We proposed an improved PBFT consensus based on a credit value bidirectionally waning, named BW-PBFT. The algorithm first elects some nodes to form a committee according to the ballot and the credit value, and then the committee nodes use the PBFT algorithm for consensus, and calculate the credit value of the nodes according to the performance in the consensus process. If nodes do not get punishment anymore, their credit value will approach 50 with the increase of the blockchain height. Theoretical analysis and experiments prove that the proposed algorithm can effectively improve the quality of the nodes involved in the consensus. [ABSTRACT FROM AUTHOR]

As blockchain technology plays an increasingly important role in the Internet of Vehicles, how to further enhance the data consensus between the areas of the Internet of Vehicles has become a key issue in blockchain design. The traditional blockchain-based vehicle networking consensus mechanism adopts the double-layer PBFT architecture, through the grouping of nodes for first intra-group consensus, and then global consensus. To further reduce delay, we propose a CRMWSL-PBFT algorithm (C-PBFT) for vehicle networking. Firstly, in order to ensure the security of RSU nodes in the network of vehicles and reduce the probability of malicious nodes participating in the consensus, we propose to calculate the reputation of RSU nodes based on multi-weighted subjective logic (CRMWSL) model. Secondly, in order to ensure the efficiency of blockchain data consensus, we improve the consensus protocol of traditional double-layer PBFT, change the election method of the committee and the PBFT consensus process, and improve throughput by reducing the number of consensus nodes. For the committee, we combine the credibility value and hash method to ensure the credibility of nodes, but also to ensure a certain degree of election randomness. For the PBFT consensus process, the regional committee consensus is carried out first, and then the regional master node carries out the global consensus. Through experimental comparison, we show that the C-PBFT significantly reduces consensus time, network overhead, and is scalable for Internet of Vehicles. [ABSTRACT FROM AUTHOR]

In a blockchain network, a rule set called consensus mechanism is used to create and finalize a block. In a proof-of-stake (PoS), consensus-based blockchain network, nodes become validators, minters, or stakeholders’ nodes to complete the consensus mechanism. In these networks, when a node becomes a validator node, its details need to be saved because the details of the validators are used in the network for many important decisions, such as selecting block proposers for the consensus process. In this paper, we present Sea Shield, which uses a validator chain to save a node’s information when it becomes a validator or leaves its responsibility as a validator in the PoS-based blockchain network. The validator chain is a blockchain that can run with the main chain of a PoS-based blockchain. The internal features of the validator chain are similar to those of the blockchain. We designed and simulated a consensus mechanism to create and finalize the block for the validator chain with no forks. We present a process by which a node may join or unjoin as a validator in a PoS-based blockchain network to improve the overall security of the main chain-consensus process.

Currently, blockchain technology is not only gaining momentum in the financial industry but also showing promising developments in other sectors. Due to its suitability for various societal needs, an increasing number of non-financial institutions are expanding the scope of blockchain services beyond finance to areas such as healthcare service management and enterprise governance. The core of a blockchain system lies in consensus, which plays a crucial role in its performance and security. The PBFT algorithm is a widely used fault-tolerant consensus algorithm. However, it suffers from issues like high consensus latency, low throughput, and poor performance. In recent years, the HBFT algorithm has addressed these concerns. This paper proposes an improved HBFT blockchain consensus algorithm tailored for large enterprises and non-financial institutions with multiple independent functions. The goal is to achieve more efficient data management and election strategies that are both more secure than PBFT and more efficient than HBFT. Leveraging the enhanced HBFT consensus algorithm ensures stability and efficiency in the consensus and verification processes between organizations. Additionally, it enables the efficient management of data and value creation in the application context. [ABSTRACT FROM AUTHOR]

With the increasing demand for electric vehicle (EV) charging, there are cases of complicated trading between EV users and charging operators or electrical utilities. This paper proposes a new trading model based on consortium blockchain. Firstly, mutual trust interconnected transaction networks and channels between charging operators are established. The PBFT consensus algorithm is used to verify EV charging transactions, and smart contracts are used to complete the process. In this model, charging station nodes of each company can verify transactions, the interconnection and independent management of charging transactions are realized, users' charging methods are enriched, and the flexibility of charging services is improved. Finally, this paper uses hyperledger fabric to build an experimental environment. The feasibility of the above method is verified with an actual distribution scenario of some charging stations in Beijing. [ABSTRACT FROM AUTHOR]

Industry and research communities have widely studied Blockchain technology, and the consortium blockchain is currently the most used category with a wide range of applications. However, issues, such as the performance of consensus mechanisms, have become essential constraints on promoting and applying the consortium blockchain. To improve the performance of the consortium blockchain consensus, we use the practical Byzantine fault tolerance (PBFT) consensus widely used in consortium blockchains to reduce the number of consensus nodes to optimize performance. Using the PBFT consensus, we screen high-performance nodes and obtain a reliable and limited number of consensus nodes. We propose a genetic algorithm-based blockchain consensus algorithm improvement scheme, design the fitness function of blockchain nodes and the genetic algorithm to iterate out consensus node groups with excellent indicators continuously, and finally iterate the nodes participating in the consensus. This algorithm can increase the speed and efficiency of the consensus, block generation, and computation. The algorithm in this article is tested on the FISCO BCOS (i.e., a consortium blockchain platform built by the FISCO open-source working group), and controlled experiments and the experimental results illustrate the safety and practicability of the method. [ABSTRACT FROM AUTHOR]

PBFT algorithm has some problems such as high communication complexity and performance decrease with the increase of nodes.This paper introduces multicast communication applied to RPBFT(role-based Byzantine consensus mechanism),this paper proposes a WRPBFT consensus algorithm with low communication complexity, which can allocate consensus nodes dynamically and does not degrade with the increase of the number of nodes.WRPBF divides nodes into consensus nodes and candidate nodes, and dynamically selects consensus nodes participating in consensus for multicast communication.Experiments and analysis show that WRPBFT consensus algorithm can dynamically achieve node partitioning and selection, and WRPBFT algorithm has higher throughput, lower delay and lower communication complexity compared with traditional PBFT algorithm.

In order to solve the problem of data security and sharing efficiency caused by the complex and uncertain environment faced by swarm robotic systems in emergency scenarios, this paper designs a data security consensus algorithm based on blockchain technology. Aiming at the problems of high communication overhead, long consensus delay and low throughput when the traditional Practical Byzantine Fault Tolerance (PBFT) algorithm is applied to this scenario, a grouped practical Byzantine Fault Tolerance consensus algorithm based on K-means clustering is proposed. Firstly, the K-means clustering algorithm is used to group robotic nodes according to the location distribution of robotics in the emergency scenario. Secondly, a reputation mechanism is designed to dynamically evaluate the behaviour of robotic nodes in each group during the consensus process. Each consensus node is divided into master and slave chains according to its reputation score. The consensus task is firstly decomposed, and slave chains participate in the consensus in parallel. Finally, the master chain completes the global consensus, so as to reduce the communication times between nodes. The experimental results show that compared with the traditional PBFT, SG-PBFT and P-PBFT consensus algorithm, the proposed consensus algorithm effectively improves the system throughput, reduces the delay, reduces the communication overhead, and has a higher success rate of consensus.

With the improvement of people's awareness of environmental protection, electric vehicles (EVs) are becoming more and more popular, and the issue of vehicle to grid (V2G) energy trading is also put on the agenda. To protect the security and privacy of EVs when they trade energy with the grid, many scholars have introduced the emerging blockchain technology. However, there are few studies on the blockchain consensus algorithm for the EVs charging scenario, while the consensus is exactly the core technology in blockchain for reaching agreement in distributed systems, which to some extent determines the efficiency of V2G. Therefore, aiming at the above scenario, this paper proposes two low-complexity consensus algorithms, namely (PBFT-enabled RAFT) PRAFT and (RAFT-enable PBFT) RPBFT, which are combined the typical blockchain consensus PBFT and RAFT, and can be respectively applied to two EVs charging scenarios. In our V2G model, charging piles (CPs) and charging stations (CSs) will participate in the blockchain consensus as nodes. Through theoretical analysis and simulation, and compared with other methods, these two consensus algorithms have high scalability, low communication complexity, low storage overhead, high throughput, and low latency. Meanwhile they can also avoid the risk of Byzantine leader in RAFT. Finally, we demonstrate the two consensus algorithms in a real charging scenario, which show their transaction latency and energy consumption can well adapt to the EVs charging scenario in V2G networks.

The consortium chain is the main form of application of blockchain technology in the actual industry, and its consensus mechanism mostly adopts the practical Byzantine fault tolerance (PBFT) algorithm. The traditional PBFT algorithm is only suitable for small-scale local area networks, but in large-scale wide area network environments, its scalability bottleneck has a serious impact on the performance of the system. Therefore, in this paper, a scalable Byzantine fault tolerance algorithm based on a tree topology network is proposed (STBFT), which can take different steps to reach consensus according to the abnormal situation of the system. First, the STBFT algorithm divides the consensus nodes into different layers and groups based on the tree topology network structure, which transforms from global consensus to local consensus and drastically reduces communication consumption. Then, the division method of the group is based on a verifiable random function (VRF), with the purpose of preventing targeted attacks and colluding Byzantine nodes from affecting the normal consensus of the system. Finally, a feedback mechanism is proposed for the first time to reduce the influence of Byzantine failure on hierarchical network systems. The simulation results show that the proposed algorithm reduces the communication complexity and improves the fault tolerance of the system, and the scalability of the tree topology network structure can be better applied in large-scale scenarios such as IoT and health care.

The Industrial Internet of Things (IIoT) is the key technology of Industry 4.0. The combination of machine learning and IIoT has spawned a thriving smart industry. Machine learning models are trained and predicted based on raw data that contains sensitive information, and data sharing leads to information leakage. Data security and privacy protection in IIoT face serious challenges. Therefore, we propose a federated learning-based privacy-preserving data aggregation scheme (FLPDA) for IIoT. Data aggregation to protect individual user model changes in federated learning against reverse analysis attacks from industry administration centers. Each round of data aggregation uses the PBFT consensus algorithm to select an IIoT device from the aggregation area as the initialization and aggregation node. Paillier cryptosystem and secret sharing are combined to realize data fault tolerance and secure sharing. Security analysis and performance evaluation show that the scheme can effectively protect data privacy and resist various attacks. It has lower communication, computational, and storage overhead than existing schemes.