Security-Aware GA Based Practical Byzantine Fault Tolerance for Permissioned Blockchain

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

This all-encompassing strategy for improving the pharmaceutical supply chain management process places a strong emphasis on responsibility, transparency, and traceability. Role-based access control, secure hashing algorithms, and blockchain (Hyperledger Fabric) technologies work together to reduce the risk of counterfeit medications and guarantee accurate drug monitoring. In a drug traceability system made possible by blockchain technology, every participant in a supply chain is assigned a unique identity and has access to a shared, decentralized database that follows the transit of pharmaceuticals along the supply chain. To ensure data security and integrity, MedGuard uses the SHA-256 hashing technique for data validation and the PBFT (Practical Byzantine Fault Tolerance) consensus algorithm for network node consensus. To maintain the integrity and security of the data, each participant is only permitted to add new records to the database; they are not permitted to edit or remove alreadyexisting records. All things considered, a blockchain-based drug traceability system might greatly improve the quality and safety of pharmaceutical products and help protect patients and the public from the risks associated with fake or tainted drugs. The complete solution is currently accessible as the “MedGuard” online application.”

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.

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.

Practical Byzantine Fault Tolerance (PBFT) has been widely used in consortium blockchain systems; however, it suffers from performance degradation and susceptibility to Byzantine faults in complex environments. To overcome these limitations, this paper proposes RE-BPFT, an enhanced consensus algorithm that integrates a nuanced node credibility model considering direct interactions, indirect reputations, and historical behavior. Additionally, we adopt an optimized ID3 decision-tree method for node classification, dynamically identifying high-performing, trustworthy, ordinary, and malicious nodes based on real-time data. To address issues related to centralization risk in leader selection, we introduce a weighted random primary node election mechanism. We implemented a prototype of the RE-BPFT algorithm in Python and conducted extensive evaluations across diverse network scales and transaction scenarios. Experimental results indicate that RE-BPFT markedly reduces consensus latency and communication costs while achieving higher throughput and better scalability than classical PBFT, RBFT, and PPoR algorithms. Thus, RE-BPFT demonstrates significant advantages for large-scale and high-demand consortium blockchain use cases, particularly in areas like digital traceability and forensic data management. The insights gained from this study offer valuable improvements for ensuring node reliability, consensus performance, and overall system resilience.

The challenge of collecting large scale environmental data lies in reducing the cost of allocating data sensors while improving the data quality. Compared with traditional centralized data collecting methods, obtaining environmental data by distributed "crowds" can largely reduce the cost. However, designing such crowdsourcing systems requires an appropriate incentive mechanism to encourage providing accurate and rare environmental data. In this paper, we propose to utilize blockchain-based incentive mechanisms to address the problem. We design and evaluate a blockchain-based system for large scale environmental data acquisition, which consists of a sensor layer to collect distributed environmental data, a valuation layer to evaluate the quality of the data collected, a consensus layer to incentive and motivate high quality data collection, and a ledger layer to record the incentive transactions and the qualified environmental data. The incentive mechanism in the consensus layer is achieved with a Proof-of-Data-Value (PODV) protocol adapted from the Practical Byzantine Fault Tolerance (PBFT) [11] consensus algorithm. We carry out experiments to compare the PODV with contemporary blockchain census protocols including Proof-of-Work (POW) [16] and Proof-of-Stake (POS)[18]. The experimental results show that the proposed system outperforms in encouraging crowds to provide accurate and rare environmental data, and imply that the PODV are superior in terms of throughput and environmental friendliness.

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%.

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.

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.

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.

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.

The Practical Byzantine Fault-Tolerant (PBFT) consensus algorithm faces challenges such as random master node selection, high communication overhead, and a lack of incentive and penalty mechanisms, which undermine its efficiency and security in large-scale network environments. To address these issues, this paper proposes an improved PBFT consensus algorithm, RF-PBFT, which integrates a random forest-based node grouping mechanism with a dynamic reputation system. The algorithm leverages key behavioral data of nodes during the consensus process to train a random forest model, partitioning nodes into a consensus set and a candidate set. Nodes with superior predictive performance are selected to participate in the consensus process, thereby reducing redundant communication overhead. Furthermore, a differentiated reputation mechanism is established for the consensus group and the candidate group to encourage positive behavior and deter malicious actions. The master node is elected through a combination of prediction results and voting, enhancing system reliability and security. Simulation results demonstrate that, compared with traditional PBFT and other state-of-the-art variants, RF-PBFT significantly reduces communication overhead, decreases consensus latency, and improves throughput, validating its effectiveness in multi-node blockchain systems.

As smart cities become more decentralized, the need for reliable and secure cyber-physical systems (CPS) that guarantee safe interactions and secure data storage without loss of privacy is continuously increasing. Blockchain is a rapidly emerging technology in this domain. It demonstrated effectiveness thanks to the cryptographic mechanisms it utilizes and to its immutability. Private blockchains are the most suited to applications that require privacy and confidentiality when data is very sensitive. In this case, the most commonly used consensus protocol is Practical Byzantine Fault Tolerance (PBFT). However, PBFT requires the participation of all nodes in the consensus process, which increases bandwidth consumption and consensus delay significantly. In this paper, we propose an adaptive PBFT protocol called APBFT that optimizes the number of nodes participating in the consensus based on their response time and credibility. Therefore, we reduce the amount of communication and the response delays. We maintain the asynchrony of the algorithm so that it remains resilient to DoS attacks. The simulation results show that our algorithm outperforms the original PBFT in terms of delays and message traffic.

Introduction to the special section on blockchain techniques for the internet of vehicles security (VSI-bciov)