Byzantine Fault Research Articles

Adrestus: Secure, scalable blockchain technology in a decentralized ledger via zones

Nowadays, an increasing number of blockchain architectures provide well-promising protocols for pseudonymous online payments via proposed cryptocurrencies. Most of them suffer from a number of extensibility and scalability issues, as their capacity regarding the number of transactions they are capable of processing per second is limited. Security is also a challenge for this kind of architectures. This paper presents the design and implementation of the Adrestus system, a blockchain-based transaction system with a novel consensus mechanism that is able to tolerate Byzantine faults and is designed to scale without compromising system security. One of the main components of the Adrestus design is a consistent hashing mechanism for the efficient assignment of transactions on parallel regions, called zones, and for solving load balancing problems. We claim that the Adrestus blockchain system scales linearly without compromising system security and achieves its goals without introducing the unnecessary overhead and by eliminating energy and computational waste. Preliminary theoretical simulations and results reflect that Adrestus exceeds the average throughput of the most well-known cryptocurrencies like Bitcoin, and thus, it achieves a higher performance. In this paper, we present this proposed approach along with simulation results and examine the conditions for the proposed fault-tolerant system to meet safety and liveness.

Between Grassroots Pressure and Local Polycracy: Street Renaming in Nazi Berlin

Abstract The names of Berlin’s streets have attracted scrutiny throughout the twentieth century. When regimes collapsed and their pantheons of heroes fell into disrepute, some city streets named after individuals had to be changed: streets honouring republican luminaries no longer seemed appropriate during the Third Reich; militaristic street names seemed out of touch in Communist East Berlin; and reunited Berlin seemed the wrong place to honour the architects of the German Democratic Republic. Cultural geographers have spearheaded much of the research on renaming in twentieth-century Berlin, but their work has focused on the postwar era, when name changes were decreed by high-ranking politicians and bureaucrats. This article examines the byzantine process of street renaming in Nazi Berlin. Rather than realizing any grand plan of approved street names, Nazi-era renamings were shaped by bureaucratic polycracy, jockeying centres of power and ad hoc name changes. Case studies—including the renamings as Ludendorffstraße and Limastraße as well as thwarted renamings as Paula-Christopher-Ufer and Paul-Lincke-Straße—demonstrate the chaotic and unplanned nature of Nazi-era renamings. Ultimately, grassroots activism and individual requests from below determined the Nazi-era history of street renaming far more than any vetted and approved plan from above. This was not a well-orchestrated ‘street-sign revolution’, as happened during the postwar era.

Application of Blockchain Technology in Agricultural Water Rights Trade Management

Water is a basic and essential natural resource, and its rational allocation plays a key role in environmental and economic sustainable development. Agriculture consumes a large share of water resources, but the allocation of water rights often deviates from water use in reality. Therefore, an appropriate management method for agricultural water rights trading is needed. In this paper, blockchain technology is applied to address the agricultural water rights trading issue. Firstly, an alliance chain and the practical Byzantine fault tolerance (PBFT) consensus mechanism are adopted to support a smart contract and application. Then, a trading platform based on blockchain for agricultural water rights trading is proposed. Finally, the role and function of a decentralized autonomous organization (DAO) in a self-financing irrigation drainage district (SIDD) are clarified. This study provides a secure and stable platform which can reduce the trading confirmation time and support numerous users. The trading process of agricultural water rights is updated to minimize the cost of water rights’ transactions and improve the system’s efficiency.

A Trustworthy Safety Inspection Framework Using Performance-Security Balanced Blockchain

Regular safety inspection is critical to reduce safety risk in industry. Applying consortium blockchain technology to safety inspection can ensure the effectiveness of inspection process and tracing of problems. However, there are two major issues when using conventional consortium blockchain. It is challenging to guarantee the authenticity of the retrieved data source, and meanwhile, achieving a balance between performance and security is not easy. Hence, this paper proposes a blockchain based performance-security balanced safety inspection framework (PSB-SIF), in which a safety inspection box is designed to ensure the authenticity of the inspector’s identity while inspection logic is executed automatically via smart contracts. In addition, this paper also proposes a novel credit scoring based Byzantine fault tolerant (BFT) consensus algorithm, named Safety Inspection Byzantine Fault Tolerance consensus algorithm (SIBFT), which is used to balance the performance and security of consensus network in safety inspection. We evaluate the proposed approach by comparing with the solutions using RAFT, Practical Byzantine Fault Tolerance (PBFT), and SIBFT consensus algorithms in terms of throughput, transaction latency, scalability and security of PSB-SIF. The evaluation results show that PSB-SIF is efficient for all these quality metrics.

Byzantine-Resilient Decentralized Stochastic Gradient Descent

Decentralized learning has gained great popularity to improve learning efficiency and preserve data privacy. Each computing node makes equal contribution to collaboratively learn a Deep Learning model. The elimination of centralized Parameter Servers (PS) can effectively address many issues such as privacy, performance bottleneck and single-point-failure. However, how to achieve Byzantine Fault Tolerance in decentralized learning systems is rarely explored, although this problem has been extensively studied in centralized systems. In this paper, we present an in-depth study towards the Byzantine resilience of decentralized learning systems with two contributions. First, from the adversarial perspective, we theoretically illustrate that Byzantine attacks are more dangerous and feasible in decentralized learning systems: even one malicious participant can arbitrarily alter the models of other participants by sending carefully crafted updates to its neighbors. Second, from the defense perspective, we propose Ubar, a novel algorithm to enhance decentralized learning with Byzantine Fault Tolerance. Specifically, Ubar provides a <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">U</b> niform <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</b> yzantine-resilient <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A</b> ggregation <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</b> ule for benign nodes to select the useful parameter updates and filter out the malicious ones in each training iteration. It guarantees that each benign node in a decentralized system can train a correct model under very strong Byzantine attacks with an arbitrary number of faulty nodes. We conduct extensive experiments on standard image classification tasks and the results indicate that Ubar can effectively defeat both simple and sophisticated Byzantine attacks with higher performance efficiency than existing solutions.

LBSV: Lightweight Blockchain Security Protocol for Secure Storage and Communication in SDN-Enabled IoV

The development of modern software-defined networking (SDN) solutions brings new opportunities in Internet-of-Vehicles (IoVs). However, the autonomous nature of the vehicular environment leads to unpredictable security vulnerabilities and reliability issues. The high computation overhead and storage requirements also pose a significant challenge in message dissemination. To overcome these issues, we introduce a lightweight blockchain-based security protocol for secure communication and storage in SDN-enabled IoV, known as LBSV. The LBSV is a permissioned blockchain network that uses the proposed modified practical byzantine fault tolerance (mPBFT) consensus algorithm. Additionally, the SDN-enabled network exploits the blockchain framework and schedules different procedures. The secure message dissemination is achieved through various cryptographic functions (i.e., elliptic curve cryptography (ECC) and the secure hash algorithm (SHA256)). The security analysis shows that the LBSV withstands various cyberattacks regarding message dissemination privacy. The experimental results show that LBSV provides high performance with 85% less computational cost, 55% less storage and communication overhead and 90% less consensus delay compared with state-of-the-art schemes.

Proximal policy optimization-based committee selection algorithm in blockchain-enabled mobile edge computing systems

To cope with the low latency requirements and security issues of the emerging applications such as Internet of Vehicles (IoV) and Industrial Internet of Things (IIoT), the blockchain-enabled Mobile Edge Computing (MEC) system has received extensive attention. However, blockchain is a computing and communication intensive technology due to the complex consensus mechanisms. To facilitate the implementation of blockchain in the MEC system, this paper adopts the committee-based Practical Byzantine Fault Tolerance (PBFT) consensus algorithm and focuses on the committee selection problem. Vehicles and IIoT devices generate the transactions which are records of the application tasks. Base Stations (BSs) with MEC servers, which serve the transactions according to the wireless channel quality and the available computing resources, are blockchain nodes and candidates for committee members. The income of transaction service fees, the penalty of service delay, the decentralization of the blockchain and the communication complexity of the consensus process constitute the performance index. The committee selection problem is modeled as a Markov decision process, and the Proximal Policy Optimization (PPO) algorithm is adopted in the solution. Simulation results show that the proposed PPO-based committee selection algorithm can adapt to the system design requirements with different emphases and outperforms other comparison methods.

Breaking Blockchain’s Communication Barrier With Coded Computation

Although blockchain, the supporting technology of various cryptocurrencies, has offered a potentially effective framework for numerous decentralized trust management systems, its performance is still sub-optimal in real-world networks. With limited bandwidth, the communication complexity for nodes to process a block scales with the growing network size and hence becomes the limiting factor of blockchain’s performance. In this paper, we suggest a re-design of existing blockchain systems, which addresses the issue of the communication burden. First, by employing techniques from Coded Computation, our scheme guarantees correct verification of transactions while reducing the bit complexity dramatically such that it grows logarithmically with the number of nodes. Second, with the adoption of techniques from Information Dispersal and State Machine Replication, the system is resilient to Byzantine faults and achieves linear message complexity. Third, we propose a novel 2-dimensional sharding strategy, which inherently supports cross-shard transactions, alleviating the need for complicated communication protocols between shards, while keeping the computation and storage benefits of sharding.

Cob: a leaderless protocol for parallel Byzantine agreement in incomplete networks

In this paper we extend the Multidimensional Byzantine Agreement (MBA) Protocol, a leaderless Byzantine agreement for lists of arbitrary values, into a protocol suitable for wide gossiping networks: Cob. This generalization allows the consensus process to be run by an incomplete network of nodes provided with (non-synchronized) same-speed clocks. Not all nodes are active in every step, so the network size does not hamper the efficiency, as long as the gossiping broadcast delivers the messages to every node in reasonable time. These network assumptions model more closely real-life communication channels, so Cob may be applicable to a variety of practical problems, such as blockchain platforms implementing sharding. Cob has the same Bernoulli-like distribution that upper-bounds the number of steps as the MBA protocol. We prove its correctness and security assuming a supermajority of honest nodes in the network, and compare its performance with Algorand.

A Blockchain-Based Digital Asset Platform with Multi-Party Certification

Assets such as warehouse receipts are important for enterprises, which can be used to pledge in supply chain finance (SCF). However, traditional pledges are performed manually, which inevitably encounters inefficiency and security problems such as multiple pledges. To improve asset security, we propose a blockchain-based digital asset platform (BDAP) with multi-party certification. BDAP not only has a security protocol based on the threshold ECDSA algorithm to make related participants confirm the authenticity of assets but also embeds a Verifiable Byzantine Fault Tolerant (VBFT) mechanism, randomly selecting the consensus nodes and improving the safety of the nodes. Moreover, data stored on the blockchain makes traceability possible. Through a set of experiments, we have verified the functionality and performance of BDAP. When the pressure test reaches 100 concurrent user volume, BDAP’s average response time is 1.441 s, showing a high ability to process transactions. However, now just a few open-minded banks are willing to access BDAP, it might take a long time to change the traditional perception of the participants in supply chain finance.

Fault Tolerance Byzantine Algorithm for Lower Overhead Blockchain

A new algorithm for practical Byzantine fault tolerance (PBFT), called score-PBFT or S-PBFT, is proposed to solve the problems of high communication overhead and low algorithm efficiency. This algorithm is based on the characteristics of the consortium chain. The scoring mechanism for nodes is added. All the nodes are broken up into consensus nodes, candidate nodes, and early nodes. To make sure the consensus nodes are as reliable as possible, the nodes are changed dynamically based on how each node is behaving. Improved: the election method for the controller node has been changed. The node’s score and behaviour are used as the election basis to make the algorithm more stable. In this paper, we want to improve the consensus protocol’s execution process, cut down on how many nodes are involved in the consensus process, simplify it, and make it more efficient. Results show that, when compared with the PBFT algorithm, the S-PBFT algorithm has a shorter consensus delay, less communication overhead and throughput, and better consensus node reliability.

Energy Efficient Consensus Approach of Blockchain for IoT Networks with Edge Computing.

Blockchain technology is gaining a lot of attention in various fields, such as intellectual property, finance, smart agriculture, etc. The security features of blockchain have been widely used, integrated with artificial intelligence, Internet of Things (IoT), software defined networks (SDN), etc. The consensus mechanism of blockchain is its core and ultimately affects the performance of the blockchain. In the past few years, many consensus algorithms, such as proof of work (PoW), ripple, proof of stake (PoS), practical byzantine fault tolerance (PBFT), etc., have been designed to improve the performance of the blockchain. However, the high energy requirement, memory utilization, and processing time do not match with our actual desires. This paper proposes the consensus approach on the basis of PoW, where a single miner is selected for mining the task. The mining task is offloaded to the edge networking. The miner is selected on the basis of the digitization of the specifications of the respective machines. The proposed model makes the consensus approach more energy efficient, utilizes less memory, and less processing time. The improvement in energy consumption is approximately 21% and memory utilization is 24%. Efficiency in the block generation rate at the fixed time intervals of 20 min, 40 min, and 60 min was observed.

Joint spectrum sensing and resource allocation against byzantine attack in overlay cognitive radio networks

AbstractCognitive radio (CR) technology has emerged as a viable solution to solve the dilemma of spectrum scarcity and underutilization. It allows secondary users (SUs) to opportunistically access the primary user (PU) channel. Cooperative spectrum sensing (CSS) further improves the accuracy of detecting spectrum availability by exploiting spatial diversity gain. However, the open nature of CR networks (CRNs) makes CSS process be prone to Byzantine attack, resulting in the excessive interference to the PU and the waste of spectrum resources. To this end, we propose a joint spectrum sensing and resource allocation scheme to defend against Byzantine attack. Specifically, we develop a probabilistic Byzantine attack model to characterize attack behaviors from malicious users (MUs) and evaluate its negative impact on the CSS performance. Then, the delivery evaluation mechanism is designed to evaluate the sensing performance of SUs and distinguish between normal users and MUs. Based on this, we propose a selection‐majority algorithm to improve CSS performance by exploiting sensing reports from MUs. To further solve the Byzantine attack, we propose a spectrum resource allocation algorithm, which allocates corresponding spectrum resources according to the historical behavior of SUs. By reducing the resources allocated to poorly performing SUs, this scheme incentivizes them to report correct sensing results and drive MUs to stop attacking or leave CRN. Extensive simulation results corroborate the correctness and effectiveness of our theoretical analysis and show that our proposed scheme can effectively resist Byzantine attack.

An Innovative Methodology for Network Latency Detection Based on IoT Centered Blockchain Transactions

The new IoT apps will not be able to inspire people to utilize them and may ultimately lose all their potential if an interoperable and trustworthy ecosystem is not provided. IoT has its extra security difficulties such as information storage, administration, privacy concerns, and authentication. The presently deployed IoT apps have encountered various security and privacy assaults globally. Due to being less secure and low powered, the IoT devices present a simple entryway to the adversaries to obtain access to the corporate networks, leading to giving easy control over all of the data of the users. The objective of this doctorate proposed work will be to solve the security associated difficulties in multiple IoT domains like the e-commerce, vehicular ad hoc networks (VANET), mobile ad hoc networks (MANET), and Internet of Drones (IoD). The proposed study focuses on the development of a distributed framework for IoT based on blockchain. The framework includes the usage of Ethereum-based smart contracts and auction models to increase the income and QoS for both the seller and the buyer and the development of a DAG chain-based distributed framework for parking lot allocation in a network of automobiles. The suggested model includes the requirement of obtaining agreement among the nodes with probability one in such a circumstance. The suggested model demonstrates to be predictable as typical voting-based consensus protocols like Practical Byzantine Fault Tolerance (PBFT) and at the same time can accommodate a high number of nodes even in an asynchronous setting. Research on Byzantine fault-tolerant systems has been ongoing for more than four decades, and although the solutions were shown to be feasible early on, they remained unworkable for a long time. With PBFT, the first feasible solution was provided in 1999, and this sparked fresh research that has resulted in unique applications that are still being developed today employing this technology. Despite the fact that the safety and liveness properties of PBFT-type protocols have been thoroughly investigated, when it comes to practical performance, only empirical results—often obtained in artificial environments—are known, and imperfections in the communication channels are not explicitly considered. It is our goal in this paper to propose the first performance model for PBFT that takes into account the effect of unreliable channels as well as the usage of alternative transport protocols across those channels. We also performed a large number of simulations to test the model and acquire a better understanding of the influence of different deployment factors on the total transaction timeframe.

Byzantine Fault Tolerant Distributed Stochastic Gradient Descent Based on Over-the-Air Computation

Wireless distributed machine learning is envisaged to facilitate advanced learning services and applications in wireless networks consisting of devices with limited computing capability. Distributed machine learning algorithms are more vulnerable in wireless systems since information exchange in learning is limited by wireless resources and channel conditions. Moreover, their performance can be significantly degraded by attacks of the Byzantine devices, and information distorted by channel fading can be treated as Byzantine attacks. Consequently, protection of wireless distributed machine learning from Byzantine devices is paramount. Leveraging over-the-air computation, we put forth a novel wireless distributed stochastic gradient descent system which is resilient to Byzantine attacks. The proposed learning system is underpinned by two novel and distinct features which enable more accurate and faster distributed machine learning resilient to Byzantine attacks: <xref ref-type="disp-formula" rid="deqn1-deqn2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(1)</xref> collecting training data in the PS to obtain its own training results and <xref ref-type="disp-formula" rid="deqn1-deqn2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(2)</xref> grouping the distributed devices. We derive upper bounds of the mean square error of the global parameter when the proposed algorithms are used in the cases with and without Byzantine devices, and prove the convergence of the proposed algorithms with the derived bounds. The effectiveness of the algorithms is validated by showing the accuracy and convergence speed.

Blockchain‐Empowered Dynamic Spectrum Management for Space‐Air‐Ground Integrated Network

Space-air-ground integrated network is capable of providing seamless and ubiquitous services to cater for the increasing wireless communication demands of emerging applications. However, how to efficiently manage the heterogeneous resources and protect the privacy of connected devices is a very challenging issue, especially under the highly dynamic network topology and multiple trustless network operators. In this paper, we investigate blockchain-empowered dynamic spectrum management by reaping the advantages of blockchain and software defined network (SDN), where operators are incentive to share their resources in a common resourced pool. We first propose a blockchain enabled spectrum management framework for space-air-ground integrated network, with inter-slice spectrum sharing and intra-slice spectrum allocation. Specifically, the inter-slice spectrum sharing is realized through a consortium blockchain formed by the upper-tier SDN controllers, and then a graph coloring based channel assignment algorithm is proposed to manage the intra-slice spectrum assignment. A bilateral confirmation protocol and a consensus mechanism are also proposed for the consortium blockchain. The simulation results prove that our proposed consensus algorithm takes less time than practical Byzantine fault tolerance algorithm to reach a consensus, and the proposed channel assignment algorithm significantly improves the spectrum utilization and outperforms the baseline algorithm in both simulation and real-world scenarios.

CyberChain: Cybertwin Empowered Blockchain for Lightweight and Privacy-Preserving Authentication in Internet of Vehicles

Internet of Vehicles (IoVs) presents promising opportunities for vehicle to everything (V2X) applications, wherein authentication acts as the cornerstone to realize trustworthy vehicular context and to support advanced applications. However, existing authentication schemes mainly depend on centralized servers with both security and privacy issues. In this paper, we propose a CyberTwin (CT) empowered blockchain framework for authentication, namely CyberChain, to reduce both the communication and storage cost while maintaining vehicular privacy. By designing a blockchain system in the cyberspace, we decouple the consensus process from the physical world, so that the operation cost of blockchain can be reduced. A Privacy-Preserving Parallel Pedersen Commitment (P4C) algorithm is designed to protect the privacy of vehicles and accelerate the authentication process. To further enhance the operation efficiency of CyberChain, we propose a Diffused Practical Byzantine Fault Tolerance (DPBFT) mechanism to reach consensus in the cyberspace that can reduce consensus latency. The proposed cyberchain framework and the associated mechanisms are evaluated by qualitative analysis and simulations. The evaluation results demonstrated that the proposed cyberchain based framework significantly improves the authentication performance in terms of authentication latency, privacy, communication overhead and storage cost.

A model for blockchain-based privacy-preserving for big data users on the internet of thing

Recently, with the emergence and growth of the IoT as a promising vehicle for sustainable development, the concept of ‘smart cities’ has advanced significantly. However, many challenges inhibit the development of using IoT applications in smart cities, such as issues of privacy, scalability, trust, security, and centralisation. On a daily basis in smart cities, the IoT generates a large amount of data (big data) which could potentially be used for questionable or suspect purposes by attackers. The weight of the security issues surrounding big data must be acknowledged as the associated technology is continuously developing. To solve this issue, a strategy that secures important and potentially sensitive user information on a distributed blockchain and transmits non-sensitive information to the primary system by controlling the size of the blockchain is proposed. This solution cannot be achieved in traditional blockchain because it requires too many resources. The model is composed of three proposed algorithms: the first aims to allocate data to each user; the second performs the process of searching for data, and the third confirms the communication process. Experiments have proved that this proposed protocol for blockchain has excellent byzantine fault tolerance. The final experimental results of the proposed model established that the algorithms effectively meet the performance requirements.

When Attackers Meet AI: Learning-Empowered Attacks in Cooperative Spectrum Sensing

Defense strategies have been well studied to combat Byzantine attacks that aim to disrupt cooperative spectrum sensing by sending falsified versions of spectrum sensing data to a fusion center. However, existing studies usually assume network or attackers as passive entities, e.g., assuming the prior knowledge of attacks is known or fixed. In practice, attackers can actively adopt arbitrary behaviors and avoid pre-assumed patterns or assumptions used by defense strategies. In this paper, we revisit this security vulnerability as an adversarial machine learning problem and propose a novel learning-empowered attack framework named Learning-Evaluation-Beating (LEB) to mislead the fusion center. Based on the black-box nature of the fusion center in cooperative spectrum sensing, our new perspective is to make the adversarial use of machine learning to construct a surrogate model of the fusion center&#x0027;s decision model. We propose a generic algorithm to create malicious sensing data using this surrogate model. Our real-world experiments show that the LEB attack is effective to beat a wide range of existing defense strategies with an up to 82 percent of success ratio. Given the gap between the proposed LEB attack and existing defenses, we introduce a non-invasive method named as influence-limiting defense, which can coexist with existing defenses to defend against LEB attack or other similar attacks. We show that this defense is highly effective and reduces the overall disruption ratio of LEB attack by up to 80 percent.

Exploiting smart contracts in PBFT-based blockchains: A case study in medical prescription system

Smart contracts allow application developers to automate business processes through a decentralized computation architecture. Contemporary blockchain platforms such as Ethereum and Hyperledger Fabric offer support for smart contracts through consensus mechanisms such as Proof-of-Work (PoW) or other types of transaction validation and ordering services. This article exploits smart contracts in the Byzantine Fault Tolerant (BFT) blockchain platforms. In particular, we explore Tendermint and Hyperledger Besu, BFT blockchain platforms, and apply them to a decentralized e-prescription case study to evaluate their effectiveness. We adopt Hyperledger Besu and Tendermint in this research, given that both are BFT-based blockchains. Also, it is noteworthy that smart contracts in BFT blockchain platforms such as Tendermint are not well established and not widely adopted yet. Our article empirically evaluates the performance of smart contracts in Tendermint and Hyperledger Besu using a decentralized medical prescription case study and compares their results with Ethereum, a PoW blockchain. Our results demonstrate that BFT blockchain platforms are efficient for multi-stakeholder applications such as e-prescription and supply chains. To the best of our knowledge, this is the first study investigating the implementation of smart contracts in BFT blockchain platforms, such as Tendermint and Hyperledger Besu.