Ensuring Secure Platooning of Constrained Intelligent and Connected Vehicles Against Byzantine Attacks:A Distributed MPC Framework

This study investigates resilient platoon control for constrained intelligent and connected vehicles(ICVs)against F-local Byzantine attacks.We introduce a resilient distributed model-predictive platooning control framework for such ICVs.This framework seamlessly integrates the predesigned optimal control with distributed model predictive control(DMPC)optimization and introduces a unique distributed attack detector to ensure the reliability of the transmitted information among vehicles.Notably,our strategy uses previously broadcasted information and a specialized convex set,termed the“resilience set”,to identify unreliable data.This approach significantly eases graph robustness prerequisites,requiring only an(F+1)-robust graph,in contrast to the established mean sequence reduced algorithms,which require a minimum(2F+1)-robust graph.Additionally,we introduce a verification algorithm to restore trust in vehicles under minor attacks,further reducing communication network robustness.Our analysis demonstrates the recursive feasibility of the DMPC optimization.Furthermore,the proposed method achieves exceptional control performance by minimizing the discrepancies between the DMPC control inputs and predesigned platoon control inputs,while ensuring constraint compliance and cybersecurity.Simulation results verify the effectiveness of our theoretical findings.

Anti-Byzantine Attacks Enabled Vehicle Selection for Asynchronous Federated Learning in Vehicular Edge Computing

In vehicle edge computing(VEC),asynchronous federated learning(AFL)is used,where the edge receives a local model and updates the global model,effectively reducing the global aggregation latency.Due to different amounts of local data,computing capabilities and locations of the vehicles,renewing the global model with same weight is inappropriate.The above factors will affect the local calculation time and upload time of the local model,and the vehicle may also be affected by Byzantine attacks,leading to the deterioration of the vehicle data.However,based on deep reinforcement learning(DRL),we can consider these factors comprehensively to eliminate vehicles with poor performance as much as possible and exclude vehicles that have suffered Byzantine attacks before AFL.At the same time,when aggregating AFL,we can focus on those vehicles with better performance to improve the accuracy and safety of the system.In this paper,we proposed a vehicle selection scheme based on DRL in VEC.In this scheme,vehicle’s mobility,channel conditions with temporal variations,computational resources with temporal variations,different data amount,transmission channel status of vehicles as well as Byzantine attacks were taken into account.Simulation results show that the proposed scheme effectively improves the safety and accuracy of the global model.

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.

Byzantine Robust Federated Learning Scheme Based on Backdoor Triggers

Federated learning is widely used to solve the problem of data decentralization and can provide privacy protectionfor data owners. However, since multiple participants are required in federated learning, this allows attackers tocompromise. Byzantine attacks pose great threats to federated learning. Byzantine attackers upload maliciouslycreated local models to the server to affect the prediction performance and training speed of the global model. Todefend against Byzantine attacks, we propose a Byzantine robust federated learning scheme based on backdoortriggers. In our scheme, backdoor triggers are embedded into benign data samples, and then malicious localmodels can be identified by the server according to its validation dataset. Furthermore, we calculate the adjustmentfactors of local models according to the parameters of their final layers, which are used to defend against datapoisoning-based Byzantine attacks. To further enhance the robustness of our scheme, each localmodel is weightedand aggregated according to the number of times it is identified as malicious. Relevant experimental data showthat our scheme is effective against Byzantine attacks in both independent identically distributed (IID) and nonindependentidentically distributed (non-IID) scenarios.

A Systematic Literature Review on Blockchain Consensus Mechanisms’ Security: Applications and Open Challenges

This study conducts a systematic literature review(SLR)of blockchain consensus mechanisms,an essential protocols that maintain the integrity,reliability,and decentralization of distributed ledger networks.The aim is to comprehensively investigate prominent mechanisms’security features and vulnerabilities,emphasizing their security considerations,applications,challenges,and future directions.The existing literature offers valuable insights into various consensus mechanisms’strengths,limitations,and security vulnerabilities and their real-world applications.However,there remains a gap in synthesizing and analyzing this knowledge systematically.Addressing this gap would facilitate a structured approach to understanding consensus mechanisms’security and vulnerabilities comprehensively.The study adheres to Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)guidelines and computer science standards and reviewed 3749 research papers from 2016 to 2024,excluding grey literature,resulting in 290 articles for descriptive analysis.The research highlights an increased focus on blockchain consensus security,energy efficiency,and hybrid mechanisms within 60%of research papers post-2019,identifying gaps in scalability,privacy,and interoperability for future exploration.By synthesizing the existing research and identifying the key trends,this SLR contributes to advancing the understanding of blockchain consensus mechanisms’security and guiding future research and structured innovation in blockchain systems and applications.

门限Byzantine quorum系统及其在分布式存储中的应用

针对纠删编码和门限方案在分布式存储中的应用,提出门限Byzantine quorum系统(TBQS)的概念.该系统与数据分离算法相结合,可以构造可靠性较强的存储系统,当故障服务器个数不超过服务器总数的1/4时,利用TBQS设计存储策略可以实现容错和无间断服务.讨论了TBQS的存在性,构造了两类TBQS并对其效率进行分析,在此基础上设计了基于TBQS的分布式读写协议.

移动自组网中一种基于集群的Byzantine节点检测机制

该文主要介绍了移动自组网中一种基于集群方法的Byzantine错误检测机制。并结合CBRP,提出了一种适合移动自组网的内部出错节点清除算法。通过算法分析证明了所提出的算法可以显著减少清除具有Byzantine错误节点时所需的消息数目,降低了网络负载,有效提高了移动自组网的安全性和可信度。

分布式Byzantine容错系统研究进展

由于网络攻击的经济利益驱动和信息系统复杂性的不断增加,网络安全事件和代码缺陷也日益增多,导致信息系统出现各种错误、甚至被攻击者完全控制。Byzantine错误,又称为任意错误,是所有错误中最为严重的一种。分布式Byzantine容错系统由多台独立运行的服务器组成,能够容忍一定数量部件的Byzantine错误,在错误情况下仍然能提供正确服务。本文对现有代表性的Byzantine容错系统进行介绍和总结,讨论了Byzantine容错系统的技术发展。

基于代理的Byzantine一致性协议的研究

本文在研究了国内外Byzantine协议的基础上提出了一种新的 Byzantine一致性协议,即基于代理的 Byzan tine一致性协议。该协议按照Byzantine容错机制将所有参与运算的进程分成很多小块,每个块设有一个代理。通过代理,块内的进程向其他块的进程发送运算结果。这样,在进程发生Byzantine错误时可以先在块的内部处理,从而可以有效地减少容错的开销和时延,提高系统的安全性。

Byzantine故障环境下安全群组通信方案

提出一种Byzantine故障环境下的安全群组通信方案.在安全群组通信的通信安全层中引入Byzantine协议,采用Byzantine机制在组成员间达成一致的意见,从而检测出叛变者.在忠诚的组成员之间进行密钥协商,从而能够保证在组密钥协商之前参与协商的群组成员不是叛变者.与以前方案相比,该方案在通信开销与计算开销都有所增加,但是它能够防御内部攻击,提高了安全性及具有容忍入侵性.

T-PBFT: An EigenTrust-Based Practical Byzantine Fault Tolerance Consensus Algorithm

Blockchain with these characteristics of decentralized structure, transparent and credible, time-series and immutability, has been considering as a promising technology. Consensus algorithm as one of the core techniques of blockchain directly affects the scalability of blockchain systems. Existing probabilistic finality blockchain consensus algorithms such as PoW, PoS, suffer from power consumptions and low efficiency;while absolute finality blockchain consensus algorithms such as PBFT, HoneyBadgerBFT, could not meet the scalability requirement in a largescale network. In this paper, we propose a novel optimized practical Byzantine fault tolerance consensus algorithm based on EigenTrust model, namely T-PBFT, which is a multi-stage consensus algorithm. It evaluates node trust by the transactions between nodes so that the high quality of nodes in the network will be selected to construct a consensus group. To reduce the probability of view change, we propose to replace a single primary node with a primary group. By group signature and mutual supervision, we can enhance the robustness of the primary group further. Finally, we analyze T-PBFT and compare it with the other Byzantine fault tolerant consensus algorithms. Theoretical analysis shows that our T-PBFT can optimize the Byzantine fault-tolerant rate,reduce the probability of view change and communication complexity.

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.

Excellent Practical Byzantine Fault Tolerance

With the rapid development of blockchain technology,more and more people are paying attention to the consensus mechanism of blockchain.Practical Byzantine Fault Tolerance(PBFT),as the first efficient consensus algorithm solving the Byzantine Generals Problem,plays an important role.But PBFT also has its problems.First,it runs in a completely closed environment,and any node can't join or exit without rebooting the system.Second,the communication complexity in the network is as high as O(n2),which makes the algorithm only applicable to small-scale networks.For these problems,this paper proposes an Optimized consensus algorithm,Excellent Practical Byzantine Fault Tolerance(EPBFT),in which nodes can dynamically participate in the network by combining a view change protocol with a node's add or quit request.Besides,in each round of consensus,the algorithm will randomly select a coordination node.Through the cooperation of the primary and the coordination node,we reduce the network communication complexity to O(n).Besides,we have added a reputation credit mechanism and a wrong node removal protocol to the algorithm for clearing the faulty nodes in time and improving the robustness of the system.Finally,we design experiments to compare the performance of the PBFT and EPBFT algorithms.Through experimental,we found that compared with the PBFT algorithm,the EPBFT algorithm has a lower delay,communication complexity,better scalability,and more practical.

Cooperative spectrum sensing algorithm based on bilateral threshold selection against Byzantine attack

To deal with Byzantine attacks in 5 G cognitive radio networks,a bilateral threshold selection-based algorithm is proposed in the spectrum sensing process. In each round,secondary uses( SUs) first submit the energy values and instantaneous detection signal-to-noise ratios( SNRs) to the fusion center( FC). According to detection SNRs,the FC conducts normalization calculations on the energy values. Then,the FC makes a sort operation for these normalized energy values and traverses all the possible mid-points between these sorted normalized energy values to maximize the classification accuracy of each SU. Finally,by introducing the recognition probability and misclassification probability,the distributions of the normalized energy values are analyzed and the bilateral threshold of classification accuracy is obtained via a target misclassification probability. Hence,the blacklist of malicious secondary users( MSUs) is obtained. Simulation results show that the proposed scheme outperforms the current mainstream schemes in correct sensing probability,false alarm probability and detection probability.

A game-theory approach against Byzantine attack in cooperative spectrum sensing

In order to solve the Byzantine attack problem in cooperative spectrum sensing,a non-cooperative game-theory approach is proposed to realize an effective Byzantine defense.First,under the framework of the proposed non-cooperative game theory,the pure Byzantine attack strategy and defense strategy in cooperative spectrum sensing are analyzed from the perspective of the Byzantine attacker and network administrator.The cost and benefit of the pure strategy on both sides are defined. Secondly,the mixed attack and defense strategy are also derived. The closed form Nash equilibrium is obtained by the Lemke-Howson algorithm. Furthermore,the impact of the benefit ratio and penalty rate on the dynamic process of the noncooperative game is analyzed. Numerical simulation results show that the proposed game-theory approach can effectively defend against the Byzantine attack and save the defensive cost.

CF-BFT:A Dual-Mode Byzantine Fault-Tolerant Protocol Based on Node Authentication

The consensus protocol is one of the core technologies in blockchain,which plays a crucial role in ensuring the block generation rate,consistency,and safety of the blockchain system.Blockchain systems mainly adopt the Byzantine Fault Tolerance(BFT)protocol,which often suffers fromslow consensus speed and high communication consumption to prevent Byzantine nodes from disrupting the consensus.In this paper,this paper proposes a new dual-mode consensus protocol based on node identity authentication.It divides the consensus process into two subprotocols:Check_BFT and Fast_BFT.In Check_BFT,the replicas authenticate the primary’s identity by monitoring its behaviors.First,assume that the systemis in a pessimistic environment,Check_BFT protocol detects whether the current environment is safe and whether the primary is an honest node;Enter the fast consensus stage after confirming the environmental safety,and implement Fast_BFT protocol.It is assumed that there are 3f+1 nodes in total.If more than 2f+1 nodes identify that the primary is honest,it will enter the Fast_BFT process.In Fast_BFT,the primary is allowed to handle transactions alone,and the replicas can only receive the messages sent by the primary.The experimental results show that the CF-BFT protocol significantly reduces the communication overhead and improves the throughput and scalability of the consensus protocol.Compared with the SAZyzz protocol,the throughput is increased by 3 times in the best case and 60%in the worst case.

A New Solution to Detectable Byzantine Agreement Problem

We present a new quantum protocol for solving detectable Byzantine agreement problem between threeparties by employing one quantum key distribution protocol.The protocol is suggested by a special four-qubit entangledstate instead of singlet states,which shows that singlet states are not necessary to achieve detectable Byzantine agreement.

ASYNCHRONOUS BYZANTINE AGREEMENT PROTOCOL BASED ON VERIFIABLE SIGNATURE SHARING

An ([n/3]-1)-resilient Asynchronous Byzantine Agreement Protocol (ABAP) that combines verifiable signature sharing and random secret sharing is proposed. The protocol works in the asynchronous network environment and produces Byzantine agreement within a fixed expected number of computational rounds. The correctness of the protocol is proved in theory.

Theriac and Tao： More Aspects on Byzantine Diplomatic Gifts to Tang China

This article deals with the presenting of diplomatic gifts around the 7th Century from the Roman Empire in the East （i.e. the Byzantine Empire）, and among these a kind of medication supposedly capable of curing all sorts of illnesses, theriac. The links between these uses and Taoist expectations regarding ever-lasting life are discussed herein in the context of that diplomatic mission. It explores the different understandings of what theriac meant in the Byzantine and in the Tang courts. This sheds light on the kind of different misunderstandings, sometimes of an ironical nature, which may happen in intercultural contacts of political-diplomatic nature.

基于区块链的互联网医院云药房平台设计和实践

目的应用区块链技术,构建互联网医院云药房处方流转可信安全互通机制,实现信息可信、过程可追溯,保障用药安全。方法通过对云药房的处方流转风险与问题分析,利用区块链去中心化、智能合约、防篡改和可追溯等技术特性,针对问题给出解决问题的技术方案。结果提出基于区块链的互联网医院云药房平台管理架构,建设信息互联互通、处方信息认证、处方流转全程追溯机制,形成互联网医院电子处方流转多主体间透明、对等、可信的合作范式。结论实现互联网医院处方流转过程的规范化管理,确保互联网电子处方信息安全流通,保障患者用药安全。