RE-BPFT: An Improved PBFT Consensus Algorithm for Consortium Blockchain Based on Node Credibility and ID3-Based Classification

Although the consortium blockchains commonly adopt consensus algorithms with Byzantine fault tolerance (such as practical Byzantine fault tolerance (PBFT)), its consensus efficiency will be degraded by the existence of malicious nodes or behaviors. However, the existing researches mainly focus on the detection of malicious behaviors for public blockchains, but are rare about consortium blockchains. In this paper, an anomaly detection model based on machine learning (ML) classification algorithm is proposed for consortium blockchains that adopt PBFT. Besides, a two-stage process is proposed to reduce the resource consumption for anomaly detection. The data needed for proposed model only has two dimensions and is convenient to obtain. The results of experiment show that ML is very effective in anomaly detection for consortium blockchains. Specifically, the algorithms with the highest accuracy are convolutional neural networks (CNN), k-nearest neighbor (KNN) and support vector machines (SVM) in turn. However, KNN and SVM are more suitable because resource consumption of both algorithms are one third of CNN, and the accuracy rates are above 0.9 which is 0.9% lower than CNN.

With the rapid development of blockchain technology, consensus algorithms have become a significant research focus. Practical Byzantine Fault Tolerance (PBFT), as a widely used consensus mechanism in consortium blockchains, has undergone numerous enhancements in recent years. However, existing review studies primarily emphasize broad comparisons of different consensus algorithms and lack an in-depth exploration of PBFT optimization strategies. The lack of such a review makes it challenging for researchers and practitioners to identify the most effective optimizations for specific application scenarios. In this paper, we review the improvement schemes of PBFT from three key directions: communication complexity optimization, dynamic node management, and incentive mechanism integration. Specifically, we explore hierarchical networking, adaptive node selection, multi-leader view switching, and a hybrid consensus model incorporating staking and penalty mechanisms. Finally, this paper presents a comparative analysis of these optimization strategies, evaluates their applicability across various scenarios, and offers insights into future research directions for consensus algorithm design.

Practical Byzantine Fault Tolerance (PBFT) is a deterministic consensus algorithm, which is widely used in blockchain due to the advantage of no forks. However, PBFT still has some problems, such as not being suitable for dynamic networks, requiring large communication overhead, and not being able to identify Byzantine nodes. Therefore, we propose Extensible-PBFT (EPBFT) consensus algorithm, it can take different steps to reach consensus according to the network environment of the system. Firstly, we add the election of consensus nodes based on verifiable random function (VRF), which makes EPBFT suitable for dynamic networks. Then, we modify the consistency protocol so that EPBFT can reach consensus with less communication in a stable network, and it can also identify Byzantine nodes and reduce confirmation latency. Finally, we simplify the checkpoint protocol and the view-change protocol, reducing the time and communication overhead they require.

DTPBFT:A dynamic and highly trusted blockchain consensus algorithm for UAV swarm

With the popularity of IoT devices and cloud technology in the medical industry. Sharing EHRs (Electronic Health Records) among medical institutions improves the accuracy of medical diagnosis and promotes the development of public medical. However, it is difficult to share EHRs among hospitals, and patients typically don’t know about the usage of their health records. In this paper, we propose a patient-controlled EHRs sharing scheme based on cloud computing collaborating blockchain technology. The medical abstract and the access strategy are stored in the blockchain to avoid being tampered with. To achieve the fine-grained access control, we propose the attribute-based encryption scheme and multi-keyword encryption scheme to encrypt EHRs. Moreover, we proposed a node-state-checkable Practical Byzantine Fault Tolerance consensus algorithm (sc-PBFT) to prevent the Byzantine nodes from sneaking into the consortium blockchain. First, we check the state of the elected master node to avoid the master node having any malicious records. Then, using pre-prepared, prepare, and commit processes to complete the consensus request submitted by the client. At last, the proposed consensus algorithm evaluates the state of the master node according to the completion of the three-stage process to reduce the impact of the malicious node on the whole consortium blockchain. By doing this, the malicious node will be marked and isolated into the isolation area. The experimental results show that the proposed sc-PBFT algorithm has better handling capability and lower consensus latency. Compared with the PBFT algorithm in the case of Byzantine nodes, sc-PBFT not only improves the robustness of the consortium blockchain network but also improves the handling capability.

Achieving good performance in terms of throughput and scalability, with high quality of security has always been a challenging problem in all sorts of scheduling. Permissioned blockchain allows multiple contracts of non-trusting peer organization to be deployed for working in consortium. It is the responsibility of the scheduler often called as an ordering service to form block of transactions to get committed through consensus. Practical Byzantine Fault Tolerance (PBFT) is one of the most popular consensus algorithm used in current implementations of blockchain. Most consensus algorithms including PBFT follow FIFO scheduling strategy to create the block of transactions. With block chain being supported for multi-contract environment, scheduling should consider difference in service requirements specifically security requirement for heterogeneous contracts. The current work proposes SAGA-PBFT (Security-Aware Genetic Algorithm based Practical Byzantine fault Tolerance) scheduler, which uses multi objective genetic algorithm for balancing the security requirement and security overhead at the time of block creations. The algorithm assigns the security level to each transaction as per its security requirement but in an unpredictable manner making security attack difficult. It further uses security aware PBFT for consensus. Experimental simulation proves that SAGA-PBFT when compared with PBFT, achieves better commit time and scalability with best possible security.

Traditional intellectual property authentication relies on centralized intermediaries, which makes it difficult to address issues such as forgery, lack of trust, and opaque information. Combined with the characteristics of blockchain, such as decentralization, tampering, and traceability, these challenges can be effectively dealt with. Aiming at the shortcomings of traditional consensus algorithms in intellectual property authentication, such as high communication overhead and low efficiency, the improved PBFT (Practical Byzantine Fault Tolerance) algorithm (MBFT algorithm) is proposed and combined with the distributed database IPFS (Inter Planetary File System) to alleviate the pressure of blockchain data storage and enhance operational efficiency. The algorithm first adopts the evaluation system in the hierarchical mechanism, invokes the Fibonacci series incremental law to update the Score value of the nodes and sort them, and divides the nodes into the classification consensus layer, the consensus confirmation layer, and the supervision layer. Secondly, the Maglev algorithm is used to generate a lookup table and design a classification consensus strategy, which is divided into four consensus groups based on the characteristics of intellectual property categories, namely, the patent authentication consensus group, the trademark authentication consensus group, the copyright authentication consensus group, and the other types of authentication consensus group. Then, the algorithm optimizes the consistency protocol, carries out PBFT consensus once in each of the classification consensus layers and consensus confirmation layers, according to the consensus situation, and realizes the nodes’ dynamic update to ensure the consensus’s accuracy and reliability. The experiments show that the MBFT algorithm performs better in terms of communication complexity and throughput. As the number and size of files increase, the execution time of IPFS progressively lengthens. However, the overall performance still meets the actual demand. Compared with the traditional PBFT, MBFT improves the communication complexity by about 50% or more, the throughput is about 3 times the traditional PBFT, and the scalability and response speed of the system are significantly improved when the number of nodes increases.

Focused on the problem of master node selection and communication overhead in the Practical Byzantine Fault Tolerance (PBFT) consensus algorithm which applied to the consortium blockchain, this paper proposes an Egalitarian Practical Byzantine Fault Tolerance (ePBFT) consensus algorithm based on the PBFT algorithm. First, the concept of the primary node is diluted, so that each node in the chain is equal and efficient. Secondly, the consensus process is optimized to improve the efficiency of the consensus, the communication overhead is reduced to half of the PBFT in the case of less view changes. The experimental results show that the ePBFT algorithm and the PBFT algorithm are compared in the same environment, and the throughput is improved when the communication overhead and delay are reduced.

The integration of blockchain technology into medical billing systems presents a transformative approach to addressing long-standing challenges in data security, transparency, and transaction integrity within healthcare finance. This quantitative study examines the implementation and performance of blockchain-enabled medical billing frameworks, focusing on their capacity to ensure immutability, traceability, and fraud prevention in electronic health payment transactions. By employing a mixed-method analytical model that integrates transaction latency metrics, cryptographic hash validation rates, and decentralized ledger consistency indices across 152 sampled healthcare billing networks, the study quantifies the impact of blockchain on billing accuracy and system resilience. Results indicate that blockchain-driven systems demonstrate a statistically significant 38% reduction in billing discrepancies and a 45% improvement in data reconciliation efficiency compared to traditional electronic billing infrastructures. Furthermore, smart contract automation within Ethereum-based frameworks reduced claim-processing times by up to 62%, mitigating human error and unauthorized modifications. The research also highlights how consensus algorithms, particularly Proof of Authority (PoA) and Practical Byzantine Fault Tolerance (PBFT), enhance the verification process for medical transactions without compromising processing speed. These findings underscore blockchain’s potential to redefine financial trust structures within healthcare ecosystems by ensuring end-to-end transactional integrity, auditability, and compliance with data privacy regulations such as HIPAA and GDPR. The study concludes that blockchain-enabled secure billing systems can significantly strengthen institutional accountability and patient trust while establishing a robust foundation for interoperable, tamper-proof financial data management across global healthcare networks.

An improved practical Byzantine fault tolerance (Practical Byzantine Fault Tolerant consensus algorithm based on reputation, RPBFT) algorithm based on grouping and reputation value voting is proposed for the problems of high communication complexity, poor scalability, and random selection of master nodes of the practical Byzantine fault tolerance (PBFT) consensus algorithm of the consortium chain. First, the consistency process is optimized to take the response speed of nodes to each group leader as the basis of grouping, and the intragroup consensus is performed. The group leader then takes the result of intragroup consensus and participates in extra-group consensus to reduce the frequency and time of internode communication. Second, the reputation model and voting mechanism are proposed, and the group leader is generated by node reputation value voting, which enhances the initiative and reliability of trusted nodes and reduces the abnormal nodes as group leader. Finally, a simulation and performance testing system based on this improved scheme is built to prove the effectiveness as well as the usability of the scheme through simulation experiments. The experimental results show that when the number of network nodes is 36, the throughput of the RPBFT algorithm is six times that of PBFT. Therefore, the consensus delay is reduced by 91.7%, and the communication overhead is reduced by 37.8%.

The conventional architecture of vehicular ad hoc networks (VANETs) with a centralized approach has difficulty overcoming the increasing complexity of intelligent transportation system (ITS) applications as well as challenges in providing large amounts of data storage, trust management, and information security. Therefore, vehicular edge computing networks (VECNets) have emerged to provide massive storage resources with powerful computing on network edges. However, a centralized server in VECNets is insufficient due to potential data leakage and security risks as it can still allow a single point of failure (SPoF). We propose consortium blockchain and smart contracts to ensure a trustworthy environment for secure data storage and sharing in the system to address these challenges. Practical byzantine fault tolerance (PBFT) is utilized because it is suitable for consortium blockchain to audit publicly, store data sharing, and records the whole consensus process. It can defend against system failures with or without symptoms to reach an agreement among consensus participants. Furthermore, we use an incentive mechanism to motivate the vehicle to contribute and honestly share their data. The simulation results satisfy the proposed model’s design goals by increasing vehicular networks’ performance in general.

Blockchain technology relies on decentralized data management across various applications to ensure secure transactions. Consensus algorithms play a critical role in maintaining consistency and trust within decentralized environments, laying the groundwork for further exploration. This paper presents a simulation-based benchmarking framework for evaluating major consensus mechanisms Proof of Work (PoW), Proof of Stake (PoS), Proof of Authority (PoA), Proof of Capacity (PoC), Practical Byzantine Fault Tolerance (PBFT), Directed Acyclic Graph (DAG), and Proof of Biometric Uniqueness (PoBU). A MATLAB-based simulation environment integrated with Docker-emulated blockchain nodes was developed to measure performance across several parameters, including throughput, latency, energy consumption, finality probability, fault tolerance, and resource requirements. Results show that DAG achieves the highest throughput (1600 TPS) and lowest latency (0.8 s), while PoBU offers strong fault tolerance (50%) and energy efficiency (60 J/tx). PBFT and PoA provide ultra-fast confirmations with limited decentralization, whereas PoW demonstrate poor scalability and energy efficiency. These findings highlight the potential for a unified benchmarking framework for consensus mechanisms and provide practical insights for selecting consensus protocols for specific blockchain applications.

Blockchain is a new technology for processing complex and disordered information with respect to business and other industrial applications. This work is aimed at studying the consensus algorithm of blockchain to improve the performance of blockchain. Despite their advantages, the proof of stake (POS) algorithm and the practical Byzantine fault tolerance (PBFT) algorithm have high latency, low throughput, and poor scalability. In this paper, a blockchain hybrid consensus algorithm which combines advantages of the POS and PBFT algorithms is proposed, and the algorithm is divided into two stages: sortition and witness. The proposed algorithm reduces the number of consensus nodes to a constant value by verifiable pseudorandom sortition and performs transaction witness between nodes. The algorithm is improved and optimized from three dimensions: throughput, latency, and scalability. The experimental results show that the improved hybrid consensus algorithm is significantly superior to the previous single algorithms for its excellent scalability, high throughput, and low latency.

Because of its excellent properties of fault tolerance, efficiency and availability, the practical Byzantine fault tolerance (PBFT) algorithm has become the mainstream consensus algorithm in blockchain. However, current PBFT algorithms have problems such as inadequate security of primary node selection, high communication overhead and network delay in the process of consensus. To address these problems, we design a novel efficient Byzantine fault tolerance algorithm based on credit grouping, called CG-PBFT. First, we propose a new credit evaluation model to obtain nodes’ credit values and introduce an optimized three-way quick sorting algorithm to divide nodes into the master-node group, the consensus-node group and the observation-node group, which have different privileges. The nodes in the observation-node group are restricted from participating in consensus, which reduces the communication overhead and improves consensus efficiency. Second, we propose an optimized selection method for the primary node based on a voting mechanism whereby the consensus-node group and observation-node group vote to produce the primary node, which reduces the probability of malicious nodes acting as the primary node and improves the security of primary node selection. Finally, the identity conversion mechanism between node groups is designed, and the actual behavior of nodes within different groups is given credit rewards or punishment, so as to keep an incentive for nodes to participate in appropriate system behavior and improve the working enthusiasm of nodes. The experimental simulation results show that compared with existing PBFT algorithms, the CG-PBFT algorithm improves the average throughput by 51.3% and reduces the average delay by 64.5%; it greatly improves the operating efficiency of the system and can be more suitable for application in the consortium blockchain scenarios.

Purpose Problems such as data security and trustworthy interactivity bring new challenges to the development and application of service ecosystems. As a decentralized ledger, blockchain has characteristics such as non-tamperability, unforgeability, traceability, global consistency, so that the integration between blockchain and service ecosystems can ensure data integrity and service availability. The purpose of this paper is to investigate problems of efficient consensus algorithm in service ecosystems alliance chain scenarios. Design/methodology/approach This method consists of two core modules: bubble sort and reputation mechanism. The bubble sort algorithm can reduce the number of consensus nodes, thereby reducing communication overhead and improving throughput. The reputation mechanism can improve the correctness of consensus nodes, thereby solving the problem of random selection of the primary in the PBFT algorithm and improving its security and efficiency. Findings Comparative experiments and analysis have been conducted between the practical Byzantine fault-tolerant algorithm combined with bubble sort and reputation mechanism (BR-PBFT) scheme proposed in this paper and existing similar PBFT algorithms in terms of communication complexity, transaction confirmation delay and throughput. The experimental results demonstrate that BR-PBFT maintains 1/3 fault tolerance of PBFT, effectively reduces communication overhead, lowers transaction confirmation delay and improves throughput. Originality/value The practical Byzantine fault tolerance (PBFT) algorithm used in the alliance chain still has the problems of high communication complexity and low throughput. Aiming at application scenarios of alliance chains in service ecosystems, an improved is proposed. It provides valuable insights into future research and practical applications in service ecosystems.