Byzantine Fault Tolerance Consensus Research Articles

Joint Reputation Based Grouping and Hierarchical Byzantine Fault Tolerance Consensus Protocol

Joint Reputation Based Grouping and Hierarchical Byzantine Fault Tolerance Consensus Protocol

Contract-Theory-Based Secure Spectrum Sharing Framework in Internet of Vehicles

Internet of vehicles (IoV) enables a large number of applications for consumers by integrating massive electronics, which aggravates the spectrum scarcity and data security, and degrades the quality of services (QoS) and experiences of consumers obviously. Focusing on enhancing the security and improving spectrum utilization, this article proposes a contract-theory-based secure spectrum sharing framework, which adopts the consortium blockchain to guarantee security of spectrum sharing and utilizes the practical Byzantine fault tolerant consensus algorithm to achieve consensus in IoV. Smart contracts are then formed based on insurance contracts to promote primary users to share their idle spectrum resources. A preference-based spectrum allocation algorithm is designed to maximize the total utility of secondary users (SUs). Simulation results show that, compared with the existing schemes, the proposed scheme achieves better performance in terms of the utility of SUs and the spectrum utilization greatly, which provides more access opportunities to consumers in IoV.

Improvement of the PBFT Algorithm Based on Grouping and Reputation Value Voting

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%.

Game theory based compatible incentive mechanism design for non-cryptocurrency blockchain systems

With the success of Bitcoin, nowadays, both academia and industry have been focusing on the expansion of blockchain in non-cryptocurrency applications to facilitate the development of Industry 4.0. The incentive mechanism in blockchain, which encourages miners to participate in validation processes, is important to the maintenance of the system. However, the techniques, which are widely applied in existing blockchain systems, are not suitable for non-cryptocurrency applications with business models and have become a major issue that undermines the adoption of blockchain. In this paper, we propose a compatible incentive mechanism for non-cryptocurrency applications to encourage validators’ actions to align with consensus algorithm. The compatible incentive mechanism works with a consensus algorithm to make the blockchain technology more adaptable in industry applications. The proposed design matches with the voting-based Practical Byzantine Fault Tolerance (PBFT) consensus algorithm which is adopted by most non-cryptocurrency applications. Game theory-based analysis is conducted to identify the problems caused by participants’ misbehaviours. Meanwhile, a mechanism design based on game theory analysis is adopted to develop our incentive mechanism which satisfies the compatibility requirement. Both mathematical proof and simulation experiments are used to evaluate our mechanism design. The results demonstrate that our compatible incentive mechanism encourages the desired honest behaviour among validators so that the blockchain can be maintained to align with the consensus algorithm.

Practical Byzantine fault tolerance consensus based on comprehensive reputation

Practical Byzantine fault tolerance consensus based on comprehensive reputation

Votes-as-a-Proof (VaaP): Permissioned Blockchain Consensus Protocol Made Simple

With the development of Blockchain technology, permissioned Blockchains are getting more and more attention from researchers because applications based on permissioned Blockchains are more practical and easier to be carried out. This paper aims to design a dedicated consensus protocol for permissioned Blockchains. The existing consensus protocols applied to permissioned Blockchains are either derived from public Blockchains such as Proof of Work (PoW) or Proof of Stake (PoS), with full decentralization, resulting in low transaction processing efficiency; or derived from traditional Byzantine fault-tolerant (BFT) consensus protocols such as Practical BFT (PBFT) or HoneyBadgerBFT, with high communication complexity of the consensus process, resulting in low scalability. Therefore, we propose a dedicated consensus protocol for permissioned Blockchains called Votes-as-a-Proof (VaaP) with high transaction processing efficiency while ensuring high scalability. Every node in VaaP runs a simple consensus process based on voting in parallel. Faulty nodes will only deprive themselves of using consensus service. We present the comparison of VaaP and Sphinx, one of the state-of-the-art consensus protocols, analytically and experimentally (up to 500 nodes). The results indicate that VaaP outperforms Sphinx in throughput, latency and scalability.

A Trusted Paradigm of Data Management for Blockchain-Enabled Internet of Vehicles in Smart Cities

Internet of Vehicles(IoV) enables vehicles to generate and share messages to improve transportation safety and efficiency, especially in a smart city scenario where modern communication technology is utilized. The current IoV, however, faces three main issues: (1) existing frameworks fail to build a complete data management system, (2) received messages in an untrusted environment are challenging to assess for credibility, and (3) the centralized ways to store data are causing severe security and efficiency problems. Blockchain-enabled IoV (BIoV) provides an opportunity for addressing these issues. This paper proposes a trusted paradigm of data management based on a vehicle–road–cloud architecture. A few-shot learning model, Wasserstein Generative Adversarial Network (WGAN) with Synthetic Minority Oversampling Technique (SMOTE) sampling is designed to evaluate whether the uploading message is malicious. This paper also proposes the novel group-weighted-decay Practical Byzantine Fault Tolerance (PBFT) consensus algorithm, an improved version of PBFT to store data, and provides a comprehensive review of its viability and data management procedures. By employing the joint gwd-PBFT and Proof of Trust (PoT) consensus, the method mitigates the issue of excessive incentives. According to simulation results, the system's overall efficiency can be increased while retaining security and availability.

A node selection algorithm with a genetic method based on PBFT in consortium blockchains

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.

Develop a New Lightweight Consensus Algorithm for IoT

Blockchain has gained a lot of attention in non-financial applications like the Internet of Things (IoT). It is characterized by security, decentralization, anonymity, and auditability. Today's technology makes extensive use of the internet of things to gather data from sensors and carry out specific tasks by processing it according to the requirements. To produce secure and impermeable records of transactions, the collected data can be transferred through the blockchain network. The integration of blockchain with IoT has enormous promise due to its ability to offer decentralized computing, storage, and exchange for IoT data. Conventional blockchains generally have low throughput, long transaction delays, and rely on computationally expensive consensus algorithms. However, because of its limitations, IoT applications need a blockchain network that has a lightweight consensus algorithm to integrate with it successfully. In this paper, we implement and design a Lightweight Practical Byzantine Fault Tolerance (LPBFT) consensus algorithm that improves the conventional (PBFT) algorithm. Through the implementation of the proposed LPBFT, it has shown: a simpler message structure; doesn't need a primary server; low computation time; and consists of just two stages (request and reply). That makes it workable efficiently in IoT networks.

EB-BFT: An elastic batched BFT consensus protocol in blockchain

With the rapid increasing number of applications using blockchain, how to improve the throughput of business and reduce the latency of committing transaction on the blockchain have become important topics. This article proposes an elastic batched byzantine fault tolerance consensus protocol whose name is EB-BFT, which elastically changing consensus nodes participating in the consensus and scaling the number of transactions batching in the consensus based on volume of the transaction as well as the physical resources. The protocol EB-BFT first identifies low-performance nodes and suspends them from participating in consensus, so the number of consensus nodes is dynamically changed. After validate the legality of transactions sent by clients, the algorithm of dynamically scaling the number of batched transactions in consensus is proposed. Finally, a series of experiments are conducted to verify the effectiveness and efficiency of EB-BFT in terms of throughput and latency, and it proves when the upper limit of the latency of committing transactions is set at 15 s, the dealing speed of business can reach 20000 transactions per seconds, this results proves that this protocol will make the blockchain having better performance in larger throughput and shorter latency of processing transactions, which also proves that our method can handle transactions as well as traditional centralized system.

Blockchain and IoT-Driven Optimized Consensus Mechanism for Electric Vehicle Scheduling at Charging Stations

The emerging demand for electric vehicles in urban cities leads to the need to install a huge number of charging stations. With this requirement, electric vehicle coordination and scheduling at charging stations in real-time becomes highly tedious. Thus, there is a need for an efficient scheduling mechanism for electric vehicle charging at charging stations. This paper proposes a novel blockchain and Internet of Things-based consensus mechanism called COME for secure and trustable electric vehicle scheduling at charging stations. The proposed mechanism is intending to resolve conflicts at charging stations. The integrated InterPlanetary File System protocol facilitates a cost-efficient mechanism with minimized bandwidth for electric vehicle scheduling. The proposed mechanism ensures that there is no loss for either the electric vehicle or the charging station. We formulate different scenarios for electric vehicle charging and apply different scheduling algorithms, including first-come first-served, longest remaining time first, and coalition game theory. The performance of the proposed COME consensus mechanism is estimated by comparing it with the practical Byzantine Fault Tolerance consensus protocol and traditional systems based on the charging demand, wait time, conflict resolution, scalability, and InterPlanetary File System bandwidth parameters. The performance results show that the proposed COME consensus mechanism ensures that electric vehicles can have their vehicle charged without any conflict and that the charging station can be satisfied in terms of profit. Moreover, the proposed COME consensus mechanism outperforms the both practical Byzantine Fault Tolerance consensus protocol and the traditional system in terms of scalability and conflict resolution along with additional parameters such as wait time, charging demand, and bandwidth analysis.

Primary node election based on probabilistic linguistic term set with confidence interval in the PBFT consensus mechanism for blockchain

This study proposes a primary node election method based on probabilistic linguistic term set (PLTS) for the practical Byzantine fault tolerance (PBFT) consensus mechanism to effectively enhance the efficiency of reaching consensus. Specifically, a novel concept of the probabilistic linguistic term set with a confidence interval (PLTS-CI) is presented to express the uncertain complex voting information of nodes during primary node election. Then, a novel score function based on the exponential semantic value and confidence approximation value for the PLTS-CI, called Score-ESCA, is used to solve the problems of comparing different nodes with various voting attitudes. This method helps select the node with the highest score by utilizing complex decision attitudes, making it an accurate primary node election solution. Furthermore, the feasibility of our proposed method is proved by both theoretical analysis and experimental evaluations.

Stochastic performance modeling for practical byzantine fault tolerance consensus in the blockchain

The practical Byzantine fault tolerant (PBFT) consensus mechanism is one of the most basic consensus algorithms (or protocols) in blockchain technologies. Thus its performance evaluation is an interesting and challenging topic due to the higher complexity of its consensus work in a peer-to-peer network. This study describes a simple stochastic performance model of the PBFT consensus mechanism. This model is refined not only as a queuing system with complicated service times but also as a level-independent quasi-birth-and-death (QBD) process. With regard to the level-independent QBD process, we apply the matrix-geometric solution to obtain the necessary and sufficient condition under which the PBFT consensus system is stable and then numerically compute the stationary probability vector of the QBD process. Thus, we provide four useful performance measures for the PBFT consensus mechanism, and we can numerically calculate these performance measures. Finally, we use numerical examples to verify the validity of our theoretical results and demonstrate how the four performance measures are influenced by certain key parameters of the PBFT consensus. Considering theory of multi-dimensional Markov processes, we are optimistic that the methodology and results presented in this study are applicable to a wide range of PBFT consensus mechanism and even other types of consensus mechanisms.

A Blockchain-Enabled Incentive Trust Management with Threshold Ring Signature Scheme for Traffic Event Validation in VANETs.

As a part of the intelligent transportation system, vehicular ad hoc networks (VANETs) provide timely information about road events and traffic to improve road safety and traffic efficiency. However, VANETs face many challenges, such as attacks from malicious vehicles, identity privacy leakage, and the absence of trust between vehicular nodes. In addition, vehicles nearby an event usually lack the motivation to participate in the traffic event validation whenever it occurs, which requires the cooperation of vehicles on the network. To solve these problems, a blockchain-enabled incentive trust model with a privacy-preserving threshold ring signature scheme for VANETs is proposed. Firstly, a threshold ring signature scheme is designed in order to allow participants in the non-trusted environment to anonymously witness the message’s authenticity and reliability while guaranteeing the vehicle’s privacy. Second, a blockchain-enabled incentive trust management model is presented to enable the roadside units (RSUs) to thwart various attacks and guarantee the trustworthiness of event messages transmitted in VANETs and also motivate the senders of the traffic information and their witnesses with incentives. Finally, to improve efficiency, a practical Byzantine fault-tolerant consensus mechanism is used. Our proposed system is demonstrated to be effective and secure for VANETs, according to both security analysis and performance evaluation.

BDEdge: Blockchain and Deep-Learning for Secure Edge-Envisioned Green CAVs

Green Connected and Autonomous Vehicles (CAVs) are the future of next-generation Intelligent Transportation Systems (ITS) that will help humans to improve road safety and reduce pollution, energy consumption, and travel delays. To increase the performance of green CAV, the data generated by Autonomous Vehicles (AVs) and associated infrastructure needs to be processed in real-time. Mobile Edge Computing (MEC) is a promising paradigm that can be integrated with green CAV to save energy and to improve the network performance in terms of low latency for data processing. However, MEC servers and other communication entities in green CAV environment cannot be fully trusted and may bring vulnerabilities related to data privacy and security. Motivated by the above challenges, we design a blockchain and Deep-Learning (DL)-enabled secure data processing framework for an edge-envisioned green CAV environment (hereafter referred to as BDEdge). In blockchain-based scheme, all communication entities are registered, verified and thereafter validated using smart contract-based Practical Byzantine Fault Tolerance (PBFT) consensus algorithm. The authenticated data is forwarded to DL scheme. In DL-based scheme, an Intrusion Detection System (IDS) based on a hybrid model of Sparse Auto-Encoder-enabled Attention Bidirectional Gated Recurrent Unit (SAE-ABIGRU) is designed by analyzing the link load behaviors of the MEC-enabled Road Side Unit (RSU) server. The security analysis and comparative simulation findings shows that the proposed BDEdge framework can significantly reduce false alarm rate and increase accuracy close to 99%.

μDFL: A Secure Microchained Decentralized Federated Learning Fabric Atop IoT Networks

Federated Learning (FL) has been recognized as a privacy-preserving machine learning (ML) technology that enables collaborative training and learning of a global ML model based on the aggregation of distributed local model updates. However, security and privacy guarantees could be compromised due to malicious participants and the centralized aggregation manner. Possessing attractive features like decentralization, immutability and auditability, Blockchain is promising to enable a tamper-proof and trust-free framework to enhance performance and security in IoT based FL systems. However, directly integrating blockchains into the large scale IoT-based FL scenarios still faces many limitations, such as high computation and storage demands, low transactions throughput, poor scalability and challenges in privacy preservation. This paper proposes <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> DFL, a novel hierarchical IoT network fabric for decentralized federated learning (DFL) atop of a lightweight blockchain called microchain. Following the hierarchical infrastructure of FL, participants in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> DFL are fragmented into multiple small scale microchains. Each microchain network relies on a hybrid Proof of Credit (PoC) block generation and Voting-based Chain Finality (VCF) consensus protocol to ensure efficiency and privacy-preservation at the network of edge. Meanwhile, microchains are federated vie a high-level inter-chain network, which adopts an efficient Byzantine Fault Tolerance (BFT) consensus protocol to achieve scalability and security. A proof-of-concept prototype is implemented, and the experimental results verify the feasibility of the proposed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> DFL solution in cross-devices FL settings with efficiency, security and privacy guarantees.

Weighted Byzantine Fault Tolerance consensus algorithm for enhancing consortium blockchain efficiency and security

In blockchain, the consensus algorithm is a core component that governs the trust among the participants in the blockchain activities. However, the exiting consensus algorithms suffer from performance bottleneck such as low throughput, high delay, unstable performance, sustainability issues and vulnerability to targeted attacks. In this paper, we propose a new consortium blockchain consensus algorithm, referred to as Weighted Byzantine Fault Tolerance (WBFT) consensus algorithm that improves system throughput and consensus delay. We introduce a dynamic weighting mechanism for consensus nodes, which enhances the security of blockchain system by weakening the influence of malicious nodes and reduces the probability of malicious behavior. We validate the performance of WBFT experimentally and compare it against Practical Byzantine Fault Tolerance (PBFT) and Reputation-Based Byzantine Fault-Tolerance (RBFT) based approaches. The results show that WBFT substantially outperforms PBFT and RBFT in terms of system throughput, consensus delay and security.

A Hierarchy Byzantine Fault Tolerance Consensus Protocol Based on Node Reputation.

A blockchain has been applied in many areas, such as cryptocurrency, smart cities and digital finance. The consensus protocol is the core part of the blockchain network, which addresses the problem of transaction consistency among the involved participants. However, the scalability, efficiency and security of the consensus protocol are greatly restricted with the increasing number of nodes. A Hierarchy Byzantine Fault Tolerance consensus protocol (HBFT) based on node reputation has been proposed. The two-layer hierarchy structure is designed to improve the scalability by assigning nodes to different layers. Each node only needs to exchange messages within its group, which deducts the communication complexity between nodes. Specifically, a reputation model is proposed to distinguish normal nodes from malicious ones by a punish and reward mechanism. It is applied to ensure that the malicious node merely existing in the bottom layer and the communication complexity in the high layer can be further lowered. Finally, a random selection mechanism is applied in the selection of the leader node. The mechanism can ensure the security of the blockchain network with the characteristics of unpredictability and randomicity. Some experimental results demonstrated that the proposed consensus protocol has excellent performance in comparison to some state-of-the-art models.

GPBFT: A Practical Byzantine Fault-Tolerant Consensus Algorithm Based on Dual Administrator Short Group Signatures

The practical Byzantine fault-tolerant consensus algorithm reduces the operational complexity of Byzantine protocols from an exponential level to a polynomial level, which makes it possible to apply Byzantine protocols in distributed systems. However, it still has some problems, such as high communication overhead, low security, poor scalability, and difficulty in tracking. In this article, we propose a Byzantine fault-tolerant consensus algorithm based on dual administrator short group signatures (GPBFT). Firstly, the certification authority chooses the master node and group administrators based on the credit value. The group administrators organize the nodes into a group, and the members generate the signatures by applying the short group signatures scheme, in which any group member can represent the group during the GroupSign phase. Additionally, the GPBFT algorithm adds the Trace phase. According to member and client authentication information, the group administrator can track the true identity of the malicious node, identify the malicious node, and revoke it. The experimental results show that compared with the PBFT algorithm, the GPBFT algorithm can reduce the network communication overhead, reduce the consensus delay, and greatly improve the security and stability of the system. The algorithm can effectively manage member nodes and enable the tracking of identified malicious nodes while maintaining anonymity in terms of node tracking.

LAP-BFT: Lightweight Asynchronous Provable Byzantine Fault-Tolerant Consensus Mechanism for UAV Network

Mission-oriented UAV networks operate in nonsecure, complex environments with time-varying network partitioning and node trustworthiness. UAV networks are thus essentially asynchronous distributed systems with the Byzantine General problem, whose availability depends on the tolerance of progressively more erroneous nodes in the course of a mission. To address the resource-limited nature of UAV networks, this paper proposes a lightweight asynchronous provable Byzantine fault-tolerant consensus method. The consensus method reduces the communication overhead by splitting the set of local trusted state transactions and then dispersing the reliable broadcast control transmission (DRBC), introduces vector commitments to achieve multivalue Byzantine consensus (PMVBA) for identity and data in a provable manner and reduces the computational complexity, and the data stored on the chain is only the consensus result (global trustworthiness information of the drone nodes), avoiding the blockchain’s “storage inflation” problem. This makes the consensus process lighter in terms of bandwidth, computation and storage, ensuring the longevity and overall performance of the UAV network during the mission. Through QualNet simulation platform, existing practical asynchronous consensus algorithms are compared, and the proposed method performs better in terms of throughput, consensus latency and energy consumption rate.