基于信用等级划分的医疗数据安全共识算法

在基于区块链的医疗数据共享系统中为防御恶意节点攻击并且提高共识效率,该文提出基于信用等级划分的医疗数据安全共识算法(SCA_MD).首先,在SCA_MD中,考虑由数据节点、共识节点和监管节点组成的医疗区块共识模型,提出相应的节点身份验证机制,实现快速验证.其次,提出基于海洋掠食者的自我优化信用等级划分算法(SCRD),...     

用于图片交易的混合共识机制

随着信息技术的发展,越来越多的用户通过线上网站传输图像、浏览照片、交易版权。近年来,由于元宇宙概念逐渐引发热议,通过区块链进行的图片交易越来越多。区块链是一种分布式的数据库账本,拥有去中心化、防篡改、不依赖可信第三方等优良特性,但现有的区块链共识方案在处理图片交易时,存在奖励单一,过程复杂等不足。本文研究改进了工作量证明算法与实用拜占庭算法,并设计了基于工作积分的节点分级机制用于沟通公有链和联盟链;提出了基于双链的混合共识机制,以弥补现有共识机制在处理图片交易时节点选举随意,缺少奖惩机制的不足。实验表明,新的混合共识机制在处理图片交易时减少了通信开销,提高了交易速度。     

基于节点可信度的改进PBFT算法

本文主要是对区块链的核心技术—共识算法进行深入了解,在联盟链中难以避免会有恶意节点的存在,在节点达成共识的过程中,恶意节点将会散布不实信息,影响数据的一致性。本文对区块链防作弊技术进行研究,提出了一种基于节点可信度的NRPBFT(node-reliability-based PBFT consensus algorithm)共识算法,利用节点的可信度将所有的节点分成普通节点和共识节点,提高了共识的效率,降低了主节点作恶的可能性。     

网络共识区块链模型构建与实现

针对B/S架构以服务器作为中心存在安全隐患的问题,提出一种真实网络环境下共识区块链方案。方案基于网络中存在的多个节点,利用区块链去中心化机制存储交易数据,利用共识机制完成记账权校验。为了保护交易数据的隐私,方案对交易数据进行了哈希加密运算,同时,为了解决网络中不同节点数据同步的问题,根据最长区块链来更新网络中的节点。为了验证模型,使用Python语言编写仿真程序,通过flask框架搭建3个节点的Web框架。实验表明,提出方案能实现交易数据上链及多个节点数据同步,并实现网络中任何节点发送并存储数据,能有效对交易数据进行加密,可以解决B/S架构对中心节点过于依赖等问题。     

适用于物联网数据共享的区块链节点存储优化方案

在基于区块链的物联网数据共享中,区块链要求节点具备大量的存储资源,这极大阻碍了更多物联网设备加入共享。针对这个问题,提出一种适用于物联网数据共享的区块链节点存储优化方案。该方案提出适用于物联网数据共享场景的存储模型,引入部分重复码对实用拜占庭容错算法进行改进,在共识过程中完成区块链账本的优化存储。实验分析表明,该方案能够在保证共识效率和容错性的同时,大幅降低区块链节点的存储开销。     

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。     

基于信誉值的实用拜占庭容错改进算法研究

共识问题是区块链中的核心问题,针对联盟链常用的实用拜占庭容错算法(PBFT)中主节点选取随意、网络通信量大、公平性较低等问题,提出一种基于信誉值的PBFT改进算法。首先改变信誉值主节点选取方式,然后优化共识流程,节点的累计信誉作为判断达成共识的条件。达成共识时没有参与共识过程的节点或恶意节点的信誉值降低,降低的信誉值均分给成功参与共识的节点。经过多次共识后,故障或恶意节点对共识的影响变小,提高了算法的公平性。     

关于车联网联邦学习中可信信誉管理方法的研究

联邦学习由于其分布式、隐私保护等特点有望应用到车联网中，然而由于缺少相应的本地模型质量验证机制，全局模型容易受到恶意用户的攻击从而导致模型训练的准确率降低。提出一种车联网中分层区块链使能的联邦学习信誉管理架构。首先介绍整个架构的组成以及具体的工作流程，然后设计智能合约为系统提供更加灵活可信的信誉意见共享环境，并开发一种轻量级的区块链共识算法，以提升区块链的运行效率。仿真结果表明所提方法能够筛选出恶意用户，同时保证数据隐私和安全，从而提高FL的准确性。     

一种基于ε-greedy的领导选举方法

随着区块链的广泛部署,无人协同等延迟敏感型的应用对区块链系统的低时延需求日益提高。在协同场景下,区块链节点通常跨地域部署,节点异构性较强。在基于领导节点的拜占庭容错(Byzantine Foult Tolerant, BFT)共识协议中,不稳定的或能力较差的领导节点将导致不必要的高延迟,并降低区块链的可用性,特别是在资源有限的移动或传感器网络下。针对上述问题,提出了ε-LE,一种带有网络感知的领导选举方法,基于节点到领导节点的通信延迟测量结果,采用ε-greedy策略对领导节点进行选择,使得当前性能较优或网络中关键位置的节点具有更高概率成为领导节点,从而优化共识延迟。相较于AWARE等方法,ε-LE实现O(N)的通信复杂度,更加适用于具备线性通信复杂度的共识协议。实验结果表明,ε-LE能够选择可优化集群共识延迟的节点作为领导节点,在线性拓扑网络中实现了约21%的吞吐量提升。     

基于区块链的社会物联网可信服务管理框架

针对当前社会物联网可信服务管理中存在的中心化程度高、交易不透明和易受攻击等问题,提出了一种基于区块链的社会物联网可信服务管理框架。该框架通过区块链的去中心化特性在服务请求者和服务提供者之间直接建立信任关系,利用智能合约产生并管理新的交易,实现交易过程透明化并减少管理维护成本。同时,区块链的共识机制可用于交易验证并防范恶意攻击和篡改,减少网络攻击和恶意节点的欺骗。最后,分析了该框架在实际构建中面临的主要挑战。     

An Optimal Stability Matching Algorithm for DAG Blockchain Based on Matching Theory

IOTA is a typical blockchain designed for IoT applications. The Markov chain monte carlo algorithm (MCMC) used in IOTA may lead to a large number of unverified blocks, which increases transaction delay to a certain extent. We propose a Stable matching algorithm (SMA) based on matching theory to stimulate nodes to verify blocks, thereby reducing the number of unverified blocks and the consensus delay. The structure of our IoT blockchain uses the Directed acyc1ic graph (DAG) to improve the transaction processing capability. The nodes in the network are abstracted as transaction issuers and transaction verifiers. A verification service scheduling system is used to assign transactions to the verifiers and achieve the optimal matching. We designed a trust evaluation mechanism which offers verifiers references and awards to check transactions. The simulation results show that SMA can significantly reduce the number of orphan blocks and improve the transaction throughput, which helps to improve the reliability of the IoT blockchain.     

6G oriented blockchain based Internet of things data sharing and storage mechanism

Considering the heterogeneity of various IoT system and the single point failure of centralized data-processing platform,a decentralized IoT data sharing and storage method based on blockchain technology was proposed.The block consensus and decentralized storage of shared data were realized through the PoS consensus mechanism.A block layered propagation mechanism between consensus node and verified node was proposed based on the Gossip protocol.The block propagation delay model and decentralization evaluation model of blockchain networks were derived.The trade-off between the block propagation delay and the decentralization degree of networks was analyzed.The simulation results demonstrate that the block propagation delay and degree of network decentralization decrease with the increase of minimal capabilities of consensus nodes.As an application example,in the trajectory data sharing scenario of confirmed patients,the data sharing smart contract is implemented and tested based on the Ethereum development platform.     

Imp Raft: a consensus algorithm based on Raft and storage compression consensus for IoT scenario

In order to meet various challenges in the Internet of things (IoT), such as identity authentication, privacy preservation of distributed data and network security, the integration of blockchain and IoT became a new trend in recent years. As the key supporting technology of blockchain, the consensus algorithm is a hotspot of distributed system research. At present, the research direction of the consensus algorithm is mainly focused on improving throughput and reducing delay. However, when blockchain is applied to IoT scenario, the storage capacity of lightweight IoT devices is limited, and the normal operations of blockchain system cannot be guaranteed. To solve this problem, an improved version of Raft (Imp Raft) based on Raft and the storage compression consensus (SCC) algorithm is proposed, where initialization process and compression process are added into the flow of Raft. Moreover, the data validation process aims to ensure that blockchain data cannot be tampered with. It is obtained from experiments and analysis that the new proposed algorithm can effectively reduce the size of the blockchain and the storage burden of lightweight IoT devices.     

Extensive game analysis and improvement strategy of DPOS consensus mechanism

Delegated proof-of-stake ( DPOS) consensus mechanism is widely adopted in blockchain platforms, but problems exist in its current applications. In order to explore the security risks in the voting attack of the DPOS consensus mechanism, an extensive game model between nodes was constructed, and it was concluded that the DPOS consensus mechanism relies too much on tokens, and the possibility of node attacks is very high. In order to solve the problems of frequent changes of DPOS consensus mechanism nodes, inactive node voting, excessive reliance on tokens, and malicious nodes, a dynamic, credible, and attack-evading DPOS consensus mechanism was proposed. In addition, the Python simulation results show that the improved Bayesian voting algorithm is effective in calculating node scores.     

Throughput-oriented associated transaction assignment in sharding blockchains for IoT social data storage

Blockchain is a viable solution to provide data integrity for the enormous volume of 5G IoT social data, while we need to break through the throughput bottleneck of blockchain. Sharding is a promising technology to solve the problem of low throughput in blockchains. However, cross-shard communication hinders the effective improvement of blockchain throughput. Therefore, it is critical to reasonably allocate transactions to different shards to improve blockchain throughput. Existing research on blockchain sharding mainly focuses on shards formation, configuration, and consensus, while ignoring the negative impact of cross-shard communication on blockchain throughput. Aiming to maximize the throughput of transaction processing, we study how to allocate blockchain transactions to shards in this paper. We propose an Associated Transaction assignment algorithm based on Closest Fit (ATCF). ATCF classifies associated transactions into transaction groups which are then assigned to different shards in the non-ascending order of transaction group sizes periodically. Within each epoch, ATCF tries to select a shard that can handle all the transactions for each transaction group. If there are multiple such shards, ATCF selects the shard with the remaining processing capacity closest to the number of transactions in the transaction group. When no such shard exists, ATCF chooses the shard with the largest remaining processing capacity for the transaction group. The transaction groups that cannot be completely processed within the current epoch will be allocated in the subsequent epochs. We prove that ATCF is a 2-approximation algorithm for the associated transaction assignment problem. Simulation results show that ATCF can effectively improve the blockchain throughput and reduce the number of cross-shard transactions.     

Research on sybil attack in defense blockchain based on improved PBFT algorithm

Aiming at the problem that sybil attack has great harm to block chain technology,a method to improve the PBFT algorithm in the alliance chain to defend against sybil attacks was proposed.Firstly,using the idea of consensus algorithm based on proof of rights and interests,a reputation model was established,the reputation value of each node accorded to the behavior of each node in the consensus process was calculated,and different discourse rights accorded to the size of the reputation value was given.Then pre-commit phase was added to the PBFT algorithm to reduce the number of communication between nodes.The solution through formal analysis and reasoning and security testing shows that the improved PBFT algorithm can not only effectively defend against sybil attacks in the blockchain,but also make the performance of the blockchain system in terms of TPS and block generation delay.     

基于区块链的雾网络中的任务卸载优化方案研究

当前物联网(IoT)应用的快速增长对用户设备的计算能力是一个巨大的挑战。雾计算(FC)网络可为用户设备提供近距离、快速的计算服务,为资源紧张,计算能力有限的用户设备提供了解决方案。该文提出一个基于区块链的雾网络模型,该模型中用户设备可以将计算密集型任务卸载到计算能力强的节点处理。为最小化任务处理时延和能耗,引入两种任务卸载模型,即设备到设备(D2D)协作群组任务卸载和雾节点(FNs)任务卸载。此外,针对雾计算网络任务卸载过程的数据安全问题,引入区块链技术构建去中心化分布式账本,防止恶意节点修改交易信息,实现数据安全可靠传输。为降低共识机制时延和能耗,提出了改进的基于投票的委托权益证明(DPoS)共识机制,得票数超过阈值的FNs组成验证集,验证集中的FN轮流作为管理者生成新区块。最后,以最小化网络成本为目标,联合优化任务卸载决策、传输速率分配和计算资源分配,提出任务卸载决策和资源分配(TODRA)算法进行求解,并通过仿真实验验证了该算法的有效性。     

RBFT:基于Raft集群的拜占庭容错共识机制

针对现有联盟链共识机制因可拓展性不足,无法在支持大规模网络的同时满足低时延、高吞吐量和安全性的问题,采用网络分片的思想,提出一种适用于联盟链的带有监督节点的两级共识机制——RBFT.首先对网络节点进行分组,组内采用改进的Raft机制进行共识,然后由每个组内选出的领导者组成网络委员会,网络委员会内部采用PBFT机制进行共...     

Performance optimization for smart grid blockchainintegrated with fog computing using DDQN

In order to solve the energy crisis and pollution problems, smart grid is widely used. However, there are many challenges such as the management of distributed energy during the construction. Blockchain, as an emerging technology, can provide a secure and transparent solution to the decentralized network. Meanwhile, fog computing network is considered to avoid the high deployment cost. The edge servers have abundant computing and storage resources to perform as nodes in grid blockchain. In this paper, an innovative structure of smart grid blockchain integrated with fog computing are proposed. And a new consensus mechanism called scalable proof of cryptographic selection (SPoCS) is designed to adapt the hybrid networks. The mechanism not only includes a special index, contribution degree, to measure the loyalty of fog nodes and the probability of being a function node, but also has flexible block interval adjustment method. Meanwhile, the number of function nodes (validating nodes and ordering nodes) can also be adjusted. And a deep reinforcement learning (DRL) method is used to select the appropriate quantity to improve the performance under the strict constraints of security and decentralization. The simulation shows the scheme performs well in the throughput, cost and latency.