CRBFT:A Byzantine Fault-Tolerant Consensus Protocol Based on Collaborative Filtering Recommendation for Blockchains

Blockchain has been widely used in finance,the Internet of Things(IoT),supply chains,and other scenarios as a revolutionary technology.Consensus protocol plays a vital role in blockchain,which helps all participants to maintain the storage state consistently.However,with the improvement of network environment complexity and system scale,blockchain development is limited by the performance,security,and scalability of the consensus protocol.To address this problem,this paper introduces the collaborative filtering mechanism commonly used in the recommendation system into the Practical Byzantine Fault Tolerance(PBFT)and proposes a Byzantine fault-tolerant(BFT)consensus protocol based on collaborative filtering recommendation(CRBFT).Specifically,an improved collaborative filtering recommendation method is designed to use the similarity between a node’s recommendation opinions and those of the recommender as a basis for determining whether to adopt the recommendation opinions.This can amplify the recommendation voice of good nodes,weaken the impact of cunningmalicious nodes on the trust value calculation,andmake the calculated resultsmore accurate.In addition,the nodes are given voting power according to their trust value,and a weight randomelection algorithm is designed and implemented to reduce the risk of attack.The experimental results show that CRBFT can effectively eliminate various malicious nodes and improve the performance of blockchain systems in complex network environments,and the feasibility of CRBFT is also proven by theoretical analysis.

A Fault Detection Mechanism in Erasure-Code Byzantine Fault-Tolerance Quorum

Fault-tolerance is increasingly significant for large-scale storage systems in which Byzantine failure of storage nodes may happen. Traditional Byzantine Quorum systems that tolerate Byzantine failures by using replication have two main limitations： low space-efficiency and static quorum variables. We propose an Erasure-code Byzantine Fault-tolerance Quorum that can provide high reliability with far lower storage overhead than replication by adopting erasure code as redundancy scheme. Through read/write operations of clients and diagnose operation of supervisor, our Quorum system can detect Byzantine nodes, and dynamically adjust system size and fault threshold. Simulation results show that our method improves performance for the Quorum with relatively small quorums.

New Parallel N-Input Voting for Large Scale Fault-Tolerant Control Systems

Average （mean） voter is one of the commonest voting methods suitable for decision making in highly-available and long-missions applications where the availability and the speed of the system are critical.In this paper,a new generation of average voter based on parallel algorithms and parallel random access machine（PRAM） structure are proposed.The analysis shows that this algorithm is optimal due to its improved time complexity,speed-up,and efficiency and is especially appropriate for applications where the size of input space is large.

Intelligent System for Parallel Fault-Tolerant Diagnostic Tests Construction

This investigation deals with the intelligent system for parallel fault-tolerant diagnostic tests construction. A modified parallel algorithm for fault-tolerant diagnostic tests construction is proposed. The algorithm is allowed to optimize processing time on tests construction. A matrix model of data and knowledge representation, as well as various kinds of regularities in data and knowledge are presented. Applied intelligent system for diagnostic of mental health of population which is developed with the use of intelligent system for parallel fault-tolerant DTs construction is suggested.

Improved PBFT Consensus Algorithm Based on Node Role Division

The PBFT (Practical Byzantine Fault Tolerance, PBFT) consensus algorithm, which addressed the issue of malicious nodes sending error messages to disrupt the system operation in distributed systems, was challenging to support massive network nodes, the common participation over all nodes in the consensus mechanism would lead to increased communication complexity, and the arbitrary selection of master nodes would also lead to inefficient consensus. This paper offered a PBFT consensus method (Role Division-based Practical Byzantine Fault Tolerance, RD-PBFT) to address the above problems based on node role division. First, the nodes in the system voted with each other to divide the high reputation group and low reputation group, and determined the starting reputation value of the nodes. Then, the mobile node in the group was divided into roles according to the high reputation value, and a total of three roles were divided into consensus node, backup node, and supervisory node to reduce the number of nodes involved in the consensus process and reduced the complexity of communication. In addition, an adaptive method was used to select the master nodes in the consensus process, and an integer value was introduced to ensure the unpredictability and equality of the master node selection. Experimentally, it was verified that the algorithm has lower communication complexity and better decentralization characteristics compared with the PBFT consensus algorithm, which improved the efficiency of consensus.

面向联盟链的共识算法研究

实用拜占庭容错算法(Practical Byzantine Fault Tolerance)广泛用于理论研究和实际生产中,但存在着选取主节点随机、缺乏惩罚机制等缺点.针对以上问题,(1)提出一种基于复杂网络角度的区块链共识算法,通过引入时间感知PageRank算法,建立区块链网络节点的影响力评分机制,并建立共识群组;(2)为了减少共识攻击的发生,建立节点惩罚机制,增加节点作恶的成本,有效提高攻击代价,降低攻击概率;(3)实验表明,基于时间感知PageRank的共识算法在扩展性和可靠性上高于实用拜占庭容错算法和基于信用分级的拜占庭容错算法(Credit-Layered Byzantine Fault Tolerance);在公平性和在延迟性方面,均取得良好效果.

基于信誉分类的拜占庭容错共识算法

针对许可区块链场景下实用拜占庭容错(Practical Byzantine Fault Tolerance,PBFT)共识算法通信开销大、主节点选取随意以及吞吐量低等问题,通过引入并优化信誉评分模型(Reputation Scoring Model,RSM)。提出了一种基于信誉分类的拜占庭容错(Byzantine Fault Tolerance Based on Reputation Classification,RCBFT)共识算法。定义RSM,依据节点的历史共识行为所获得的信誉评分排序对参与节点进行动态分类以及分级管理,提出基于信誉分类的多层次节点架构;在可信节点层中随机选取节点来担任主节点,优化主节点选取机制;设计了缓冲节点层类型转换策略(Type Conversion Strategy for Nodes,TCSN),兼顾了环境等非主观因素导致低信誉评分的诚实节点不能参与共识的问题,使得诚实节点尽可能多地参与共识,而拜占庭节点快速下降到最差类型中限制共识权限;RCBFT共识算法还对传统三阶段共识协议进行优化,减少通信开销,在确保容错性的同时能够提高算法性能。实验分析表明,相较于PBFT共识算法,RCBFT共识算法能够提升交易吞吐量,降低通信开销与共识时延。

基于Raft的多主节点拜占庭容错共识机制

为了解决联盟链中实用拜占庭容错(PBFT)共识机制在区块链网络中节点数量增多的情况下,通信复杂度高、共识效率低下等问题,本文提出一种基于Raft的多主节点拜占庭容错共识机制IMRBFT。IMRBFT通过Maglev一致性哈希算法对区块链网络节点均匀分组,将这个共识流程分成组外共识和组内共识2部分。组内先选出领导者节点,通过信用机制将节点分为3个等级:可信节点、普通节点和不可信节点。与投票机制共同降低恶意节点成为领导者节点的概率,并与其他组的领导者节点组成委员会,委员会再经过组外信用值机制选出信用值最高的多个主节点进行组外PBFT共识。组内共识在Raft共识的基础上引入监管节点与中继节点,进一步提升安全性与共识效率,减少恶意节点的作恶行为。实验结果表明:IMRBFT的通信开销为线性增长,通信量为PBFT的41.6%,吞吐量为PBFT的4.2倍,共识延时降低76.4%。随着节点增多,优化更加明显,完全满足大型区块链网络的通信复杂度小、吞吐量高、共识延时短、安全性与共识效率高的要求。

GBFT:一种实用拜占庭容错算法改进方案

区块链技术近年来成为研究热点,在金融、物流等行业已经有联盟链的落地案例。共识算法作为区块链的核心技术,将对区块链的整体性能产生直接影响。应用于联盟链的实用拜占庭容错算法(Practical Byzantine Fault Tolerance,PBFT)仍然存在着交易确认时间长、吞吐量低等问题。面向联盟链应用场景,基于PBFT算法,引入了非拜占庭容错协议,结合基于节点行为的选举机制,提出了三级共识机制的PBFT:GBFT。最后从吞吐量、交易确认时延、容错性等方面对GBFT方案和原始PBFT算法进行了对比实验与分析。实验结果表明,GBFT保持了PBFT算法1/3的容错性,有效提高了吞吐量,降低了交易确认时延。

基于信誉机制的改进PBFT共识算法

针对实用拜占庭容错共识算法(practical Byzantine fault tolerant,PBFT)通信开销大和缺乏奖惩机制的问题,提出一种基于信誉机制的改进PBFT共识算法RPBFT(reputed practical Byzantine fault tolerance)。首先,引入信誉机制对节点评分,将参与共识的节点分为收集器节点和普通共识节点,并对恶意节点进行惩罚。其次,收集器节点负责收集普通共识节点的投票消息,避免普通共识节点之间的通信,从而降低通信开销。最后,当普通共识节点中的拜占庭节点均无恶意行为时,通过增加收集所需的投票数量,减少一次投票收集过程,实现快速共识。实验结果表明,RPBFT能够有效地发现恶意节点并对其作出惩罚,同时具有更低的通信开销、平均共识时延以及更高的共识吞吐量。当节点总数为37时,与SBFT相比,RPBFT将平均共识时延降低25.2%以上,并将共识吞吐量提高39%以上。

基于奖励积分机制的高效拜占庭容错算法DIG-PBFT

实用拜占庭容错共识算法(PBFT)作为联盟链中最常见的共识算法,可以在恶意节点少于三分之一的情况下,保证系统的正确性.然而,PBFT算法在建立信任与共识过程中存在高时延、低吞吐量、主节点选取安全性、恶意节点未处理等问题.为了解决这些问题,引入奖励积分机制来对共识节点进行分组并设定候选节点集,提出了一种高效快速的拜占庭容错算法(DIG-PBFT).在共识过程中,DIG-PBFT通过动态地调整实际参与共识的节点,增加了安全性更高节点的参与度.仿真实验结果表明:与PBFT算法及其同类工作相比,DIG-PBFT算法的吞吐量更大、时延更低,且安全性更高.

基于节点动态评分机制的分组共识算法

针对实用拜占庭容错(practical Byzantine fault tolerance,PBFT)共识算法三阶段流程通信开销大,主节点随机选取且缺乏奖惩机制等问题,提出基于节点动态评分机制的分组共识算法(dynamic scoring practical Byzantine fault tolerance,DS-PBFT)。首先,优化一致性协议,简化三阶段通信流程从而提高共识效率;其次,提出节点评分分组机制,通过节点在共识过程中的历史行为进行评分,并分为共识组和候选组,降低恶意节点参与共识过程的可能性;最后,提出动态过程选择参与共识的节点,优化视图切换协议和垃圾回收机制,减少参与共识的节点数量,从根本上提高共识效率。用Docker容器模拟多个节点的仿真实验表明,在网络稳定、可信节点较多的联盟链中,提出的DS-PBFT共识算法在共识时延、吞吐量、容错性和通信复杂度等方面比PBFT共识算法及其他改进算法相比具有更好的性能,能够快速达成共识,提高共识效率。

CS-Raft:适用于联盟链的拜占庭容错共识算法

针对目前联盟链共识算法的性能不足,提出了一种基于信用评分的可拜占庭容错联盟链共识算法CS-Raft。首先,为所有节点赋予信用评分属性,节点的信用评分根据节点的共识行为、活跃度、加入集群时间等指标进行更新,信用评分越高代表节点可信度越高;其次,根据节点信用评分选取监督节点,监督节点具有检验权,可以参与领导人选举,监督节点的设置可以有效抵抗拜占庭恶意节点的攻击;最后,改善了领导人选举中选票分裂问题,对领导人选举的速度进行提升。经实验分析,CS-Raft算法相较于PBFT算法在实现拜占庭容错的同时,有效地减少了共识时间延迟、提高了系统吞吐量,并加快了其领导人选举速度。

基于k-means的动态多组织PBFT算法

联盟区块链系统被广泛用于金融和物流等场景。现有应用于区块链系统的实用拜占庭算法(practical Byzantine fault tolerance,PBFT)存在可扩展性较低及通信成本较高等问题,阻碍了区块链系统在大规模场景中的应用。针对上述问题,提出了一种动态多组织实用拜占庭容错算法(k-means-practical Byzantine fault tolerance,k-PBFT)。通过改进k-means算法,根据节点的时延以及节点间通信距离将节点分为多个自治组织,各组织之间通过组织代表节点进行通信。当新节点加入时,根据其特点将其分配到最合理的组织。同时,引入信誉机制以辨别系统中的诚实节点与恶意节点,从而提高系统的安全性。此外,该算法还引入节点任期机制,使区块链中每个诚实节点都有机会充当组织代表节点或主节点。实验结果表明,与PBFT算法相比,k-PBFT算法通信复杂度降低了75%;当节点数为100时,相比于PBFT算法,时延降低了210 ms,吞吐量提高了100%。在高延迟环境下,相较于基于信誉分组的PBFT改进算法,当节点数为100时,时延降低了20%,吞吐量提高了17%。

基于一致性哈希和随机选取的PBFT算法改进

针对实用拜占庭容错算法PBFT存在的系统动态性不足以及主节点选取随意导致的共识效率较低、系统稳健性较差等问题,提出一种基于一致性哈希和随机选取的CRPBFT共识算法。采用一致性哈希对节点进行分组,在分组的基础上增加节点动态变化机制,为系统提供动态的网络结构。根据节点在共识中的表现动态计算各节点的信誉值,同时定义主节点候选列表、普通节点和恶意节点这三种节点信誉层次,从高信誉值的主节点候选列表中使用可验证随机函数选取可靠且身份难以被恶意预测的主节点,并将符合信誉值要求的节点组成较稳定的共识集群。实验结果表明CRPBFT算法较PBFT算法中共识节点集群的可靠程度更高,在共识时延、吞吐量以及系统稳健性方面的性能优于PBFT算法。

RG-BFT:基于随机分组的拜占庭容错算法

随着网络环境的复杂性和网络用户数量的不断增长,区块链的发展逐渐受到共识算法的效率、安全性和可靠性的制约。针对此类问题,提出一种基于随机分组的拜占庭容错算法(random grouping-based Byzantine fault tolerant algorithm, RG-BFT),提高共识算法的效率和可靠性。使用随机选择算法与投票机制相配合,减少共识过程中的节点数量和消息数。此方案具有随机性和公正性,在保证系统活性的前提下,提高了达成共识的效率。实验结果表明,RG-BFT算法能实现较低的共识时延和通信开销及高交易吞吐量。

基于路径存储表的Hashgraph共识算法优化与实现

Hashgraph是一种数据采用有向无环图(DAG)结构的区块链共识算法,Hashgraph引入了虚拟投票的概念,允许节点在无额外通信开销的情况下并发出块,实现异步场景下的拜占庭容错。然而,Hashgraph提出的虚拟投票算法存在算法时间复杂度较高、共识运行逻辑过于复杂等问题。为此,提出一种基于路径存储表的Hashgraph优化方案。首先,提出一种基于顶点可达表的见证人判定方法,通过存储路径的方式实时记录生成事件与历史事件的可达关系,在轮次划分阶段,通过查询顶点事件的可达信息取代回溯算法,降低见证人判断算法的时间复杂度;其次,针对顶点可达表无法跨轮次判断事件关系的问题,提出一种基于历史可达表的知名见证人判定方法,历史可达表将存储见证人与历史事件之间的可达关系,通过查询历史可达表解决知名见证人判定阶段需要反复回溯视图的问题;最后,根据顶点可达表和历史可达表改进Hashgraph中复杂的共识计算,提升算法效率,加快事件确认速度。实验结果表明,所提优化方案与Hashgraph原共识算法相比,算法运行效率提升65.76%,在吞吐量方面平均提升41.27%。

区块链共识算法研究综述

区块链已广泛应用于货币金融、通信网络、信息安全、物联网、电力运行管理和社会职能管理等多个领域,但依然存在许多急需解决的问题。共识算法是区块链的核心技术之一,是区块链各节点达成一致性最为重要的底层技术,是解决区块链吞吐量太小、通信存在延迟等一系列问题的关键技术,是区块链安全运行的重要保证。文中基于区块链共识算法的设计原理,主要介绍了区块链的构成、分类、架构、上链、节点处理流程及存在的问题,重点阐述了现有PoW、PoS、DPoS、PBFT、Raft、Paxos、Ripple等共识算法设计思路、共识理论及流程,对共识算法中的共性问题,即算法优化、算法效果进行了综合概述和分析,并对区块链共识算法研究进行了展望,希望开发出更加高效、安全的共识算法。

基于区块链技术的日志系统的设计与实现

随着互联网技术的快速发展,传统的日志系统面临着一些挑战。例如,数据的篡改和丢失风险、中心化的架构容易成为攻击目标、数据分散在不同的服务器上难以管理等,为了解决这些问题,区块链技术被引入到日志系统中。本文设计的基于区块链的日志系统中,每个网络事件都被记录在一个称为区块的数据结构中,每个区块包含网络事件的详细信息,这些区块被链接在一起形成一个链表,每个区块都包含了前一个区块的哈希值,以确保数据的完整性和不可篡改性。系统实现过程中,对实用拜占庭容错算法进行优化,提高了区块共识的速度和更加安全和可信的日志记录机制,推动了日志系统的创新和发展以及区块链技术的应用和研究。

BVDFed:Byzantine-resilient and verifiable aggregation for differentially private federated learning

Federated Learning(FL)has emerged as a powerful technology designed for collaborative training between multiple clients and a server while maintaining data privacy of clients.To enhance the privacy in FL,Differentially Private Federated Learning(DPFL)has gradually become one of the most effective approaches.As DPFL operates in the distributed settings,there exist potential malicious adversaries who manipulate some clients and the aggregation server to produce malicious parameters and disturb the learning model.However,existing aggregation protocols for DPFL concern either the existence of some corrupted clients(Byzantines)or the corrupted server.Such protocols are limited to eliminate the effects of corrupted clients and server when both are in existence simultaneously due to the complicated threat model.In this paper,we elaborate such adversarial threat model and propose BVDFed.To our best knowledge,it is the first Byzantine-resilient and Verifiable aggregation for Differentially privateFEDerated learning.In specific,wepropose Differentially Private Federated Averaging algorithm(DPFA)asour primary workflow of BVDFed,which ismore lightweight and easily portable than traditional DPFL algorithm.We then introduce Loss Score to indicate the trustworthiness of disguised gradients in DPFL.Based on Loss Score,we propose an aggregation rule DPLoss to eliminate faulty gradients from Byzantine clients during server aggregation while preserving the privacy of clients'data.Additionally,we design a secure verification scheme DPVeri that are compatible with DPFA and DPLoss to support the honest clients in verifying the integrity of received aggregated results.And DPVeri also provides resistance to collusion attacks with no more than t participants for our aggregation.Theoretical analysis and experimental results demonstrate our aggregation to be feasible and effective in practice.