Performance Evaluation of Hyperledger Fabric with Malicious Behavior

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.

Aiming at the challenges of low throughput, excessive consensus latency and high communication complexity in the Practical Byzantine Fault Tolerance (PBFT) algorithm in blockchain networks, its application in identity verification for distributed networking of a drone cluster is limited. Therefore, a lightweight blockchain-based identity authentication model for UAV swarms is designed, and a Credit-score and Grouping-mechanism Practical Byzantine Fault Tolerance (CG-PBFT) algorithm is proposed. CG-PBFT introduces a reputation score evaluation mechanism, classifies the reputation levels of nodes in the network, and optimizes the consensus process based on grouping consensus and BLS aggregate signature technology. Experimental results demonstrate that under identical experimental conditions, compared with the PBFT algorithm, CG-PBFT achieves a 250% increase in average throughput, a 70% reduction in average latency, and simultaneous enhancement in security, thus making it more suitable for UAV swarm networks.

The Practical Byzantine Fault Tolerance algorithm (PBFT)has been highly applied in consortium blockchain systems, however, this kind of consensus algorithm can hardly identify and remove faulty nodes in time, and also vulnerable to many attacks against the primary node of PBFT. The equality of consortium members' discourse rights is inapplicable to some real scenarios where dominating members are likely to have a larger discourse rights in the voting process. To address these problems, this paper presents Reputation-based Byzantine Fault Tolerance (RBFT)algorithm that incorporates a reputation model to evaluate the operations of each node in the consensus process. The faulty nodes will get lower discourse rights in the voting process if any malicious behavior is detected, with their reputation decreased. Furthermore, this paper presents an innovative reputation-based primary change scheme. The node with higher reputation obtains greater opportunities to be a primary to generate new valid blocks, which reduces the security risk of the primary. The experimental results demonstrate that RBFT gains better performance and ensures system security and reliability. Compared with PBFT, it increases the average throughput by 15% and reduces delay by 10%, and the faulty node rate of the system can continue to decrease over time.

With the development of Intelligent Transportation Systems (ITS) and 5G communication technology, Vehicular Ad-Hoc Networks (VANETs) are playing an increasingly important role in enhancing road safety, improving traffic efficiency and providing online entertainment experience [1]. However, the information insecurity brought by the traditional centralized mode of VANETs is still a very challenging problem. To solve this problem, a 5G-enabled hierarchical network in VANETs is proposed through the research of blockchain and 5G technology. On this basis, a data sharing scheme based on Practical Byzantine Fault Tolerance (PBFT) algorithm is proposed, which realizes data storage and transmission effectively with its characteristics of data immutability and decentralization. The ideal expected result is that the scheme realizes data storage effectively and the security of data transmission and ensures the reliable transmission of data with lower computing time.

Blockchain technology, renowned for its decentralized, immutable, and transparent features, offers a reliable framework for trust in distributed systems. The growing popularity of consortium blockchains, which include public, private, hybrid, and consortium chains, stems from their balance of privacy and collaboration. A significant challenge in these systems is the scalability of consensus mechanisms, particularly when employing the Practical Byzantine Fault Tolerance (PBFT) algorithm. This review focuses on enhancing PBFT's scalability, a critical factor in the effectiveness of consortium chains. Innovations such as Boneh–Lynn–Shacham (BLS) signatures and Verifiable Random Functions (VRF) are highlighted for their ability to reduce algorithmic complexity and increase transaction throughput. The discussion extends to real-world applications, particularly in platforms like Hyperledger Fabric, showcasing the practical benefits of these advancements. This paper provides a concise overview of the latest methodologies that enhance the performance scalability of PBFT-based consortium chains, serving as a valuable resource for researchers and practitioners aiming to optimize these systems for high-performance demands.

In order to improve the security performance and accuracy of the Internet of things in the use process, it is necessary to use the Internet of things intrusion detection method. At present, the problem of inconsistency between the accuracy of detection results and nodes is more prominent when the Internet of things intrusion detection methods are running. This paper proposes a practical Byzantine fault‐tolerant intrusion detection method for the use process of the Internet of things. This method introduces the intrusion detection method and the operation function of foreign attackers on the basis of practical Byzantine fault tolerance; using the expected utility function to the corresponding benefit function of practical Byzantine fault tolerance, the results of Internet of things intrusion detection model can be effectively calculated. Finally, the experimental results show that compared with the existing intrusion detection methods, the proposed method can effectively reduce the energy consumption of the Internet of things in the operation process, can effectively reduce 14.3% and 7.8%, and can effectively reduce the energy consumption of the Internet of things in the operation process.

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.

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

Vehicular networks are constructed for efficient and secure data flow to make intelligent transportation system. It works by using central storage system which is inefficient as large amount of data is difficult to handle and also becomes the target of malicious activity. The flow of sensitive data on wireless channels for communication of vehicles with other nodes can also be chosen by attackers for attack. These challenges are tackled using blockchain solutions. The blockchain, a farfetched decentralized technology which is undoubtedly going to change overall trends of entire business and professional networking environment in the world to release the burden of centralization on the organizations even on the individuals and several developed countries have started to adopt this trend. This technology would be as dynamic, vibrant, efficient and secure as the category of consensus algorithms is used for the agreement and decision of joining the new block among network nodes. Security and efficiency of vehicular network is maintained through consortium blockchain boasting with Practical Byzantine Fault tolerance (PBFT) algorithm.

Internet of Vehicles (IoV) has developed into a useful service platform between vehicles and other vehicles, vehicles and roadways, and vehicles and pedestrians as a result of advancements in communication technology. However, along with the intelligent and networked IoV, IoV security issues are increasingly emerging, which often lead to extremely serious consequences. For example, when a vehicle is remotely attacked and maliciously controlled, it can lead to user privacy leakage. Attackers can also control the driving of vehicles through attacks, and there may even be a large number of connected cars being controlled in bulk, ultimately causing major social security incidents. In the Internet of Vehicles, authentication technology is one of the main solutions to address the security issues of the Internet of Vehicles. Many researchers have conducted some research on the authentication technology of vehicular network, but the traditional authentication scheme under the centralized system has problems such as frequent single-point failures and high overhead. When blockchain technology is properly implemented to the vehicle network environment, its security outperforms that of centralized systems due to features like decentralization, tamper-proof, security, and traceability. Because of this, we construct an optimization technique based on the Practical Byzantine Fault Tolerance (PBFT) algorithm in this work and present an efficient IoV decentralized authentication scheme based on the consensus algorithm of blockchain technology. After performance analysis, it is proved that our scheme has better performance and higher security.

The Chinese art market fostered the advancement of culture and spirituality. Nevertheless, false and counterfeit artwork is not uncommon. The art technology and security introduce the innovative method to determine Artwork Traceability and Anti-Counterfeiting. The aim of the work is to prevent the creation and circulation of fake or unauthorized copies of artworks. Because of the cryptographic security and immutability of block chains, it would be challenging to falsify artwork records or make accurate duplicates. This would foster confidence in the art market and shield collectors and artists from monetary losses and harm to their reputations. The data on mobile Application Data Center (ADC) platform and the cleansing the data using sub-aperture keystone transform matched filtering (SAKTMF) and the preprocessed data is fed into the Hierarchically Gated Recurrent Neural Network (HGRNN) classify the art work and Anti-Counterfeiting. The Bald Eagle Search Optimization (BES) Algorithm is used to optimize the weight parameter of HGRNN. The proposed model is implemented in MATLAB/ Simulink platform and the accuracy is compared to various existing approaches such as Dual-Branch Multi-Scale Feature Fusion network (DMF-Net), Region Convolutional Neural Network (R-CNN) and practical Byzantine fault tolerance (PBFT) algorithm. The gained results of the proposed HGRNN-BES method attains higher accuracy 97%, 96%, and 99%, higher precision 98%, 99%, and 97%.

A Prototype Model of Zero Trust Architecture Blockchain with EigenTrust-Based Practical Byzantine Fault Tolerance Protocol to Manage Decentralized Clinical Trials

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.

Since Bitcoin's inception, the non-custodial financial and programmable aspects of blockchain technology have garnered significant global attention, akin to other groundbreaking innovations. Blockchain is a transparent and decentralized ledger that prioritizes immutability, transparency, decentralization, and privacy. Its potential extends to large-scale, beneficial applications across various sectors, encompassing healthcare, supply chain management, logistics, the Internet of Things (IoT), and more. Many industrial applications make use of permissioned blockchains. However, blockchain still faces inherent and external challenges. While permissioned blockchains are suitable for many use cases, they do have limitations, especially in terms of scalability and throughput. In this paper, the authors propose implementing the proposed method by Swathi and Venkatesan using tPBFT (trust Practical Byzantine Fault Tolerance) instead of PBFT (Practical Byzantine Fault Tolerance) to improve the scalability and performance of the blockchain. The Hyperledger Fabric framework is conducted for the proposed method within the assessment of scalability, considering varying transaction volumes, and it demonstrates an enhancement in scalability. This work addresses the need for blockchain systems to evolve and adapt to meet the demands of various industries and applications, acknowledging that scalability is a key factor in their success.