Consensus Mechanism Research Articles

Optimization of Blockchain Financial Transaction Security and Transparency Based on Notary Pool Consensus Mechanism

Optimization of Blockchain Financial Transaction Security and Transparency Based on Notary Pool Consensus Mechanism

Research on the Application of Blockchain Technology in Financial Risk Management

This paper explores the application of blockchain technology in financial risk management. By analyzing foundational blockchain concepts such as public and private chains, smart contracts, and consensus mechanisms, the paper first illustrates how blockchain is transforming financial risk management practices. Additionally, it highlights challenges related to scalability, interoperability, and regulatory/legal barriers. Finally, the paper discusses innovative opportunities that blockchain presents for financial risk management, aiming to provide financial institutions with new strategies and insights to tackle modern financial challenges.

Exploring the Security Challenges of an E-Voting System (EVS): A Case Study in the Bolgatanga Senior High School

The integration of electronic voting systems (EVS) into electoral processes promises increased efficiency, speed, and transparency. However, this technology also introduces a variety of security challenges that must be addressed to ensure the integrity of the voting process. This study explores the security vulnerabilities of an EVS, focusing on its implementation at Bolgatanga Senior High School (BIGBOSS). Through a case study approach, this research examines the potential threats to the administration of EVS, including issues related to data privacy, system integrity, authentication protocols, and susceptibility to cyber-attacks. A mixed-methods strategy was employed, utilizing surveys, interviews, and system tests to assess both technical vulnerabilities and user experiences. Key findings revealed Potential Voter Manipulation where unauthorized access could allow individuals to cast votes fraudulently; Insider Threats where trusted users exploiting their access could manipulate election outcomes; Weak Authentication; Lack of Robust Verification; Potential Physical Attack where individuals could vandalize machines and Vulnerabilities in Encryption which may expose votes, compromising ballot secrecy. The study recommends the implementation a blockchain-based technology , such as cryptographic techniques, consensus mechanisms, use of biometric verification to ensure the identity of voters as well as the use of digital signatures to verify the authenticity of electronic ballots and ensure that they haven't been altered during transmission, implementation of real-time monitoring of the e-voting system to detect and respond to security threats promptly” and also provide ongoing cybersecurity education and training to election officials, staff, and voters to raise awareness and reduce the risk of human error. These findings contribute to the ongoing discourse on EVS security, providing insights into practical measures for improving the reliability and safety of electronic voting systems in educational institutions and beyond.

Leveraging quantum blockchain for secure multiparty space sharing and authentication on specialized metaverse platform

In the era of digital transformation, securing data on metaverse platforms poses significant challenges. This paper proposes Multiparty Space Sharing and Authentication (MSSA), a novel approach for secure user login and location access control within specialized metaverse platforms. MSSA leverages Quantum Multiparty Secret Computation (QMSC) integrated with a quantum blockchain network. This integration facilitates user verification within the presence of potentially untrusted metaverse authority. The underlying quantum blockchain employs a Delegated Proof-of-Stake (DPoS) consensus mechanism with a Borda voting scheme for authority node selection. By harnessing the principles of quantum cryptography, MSSA offers enhanced security against both classical and anticipated future quantum attacks. This research demonstrates the feasibility and potential of quantum blockchain for securing metaverse platforms, paving the way for secure and decentralized digital ecosystems.

NexoNet: Blockchain Online Social Media with User-Centric Multiple Incentive Mechanism and PoAP Consensus Mechanism

Online social media (OSM) has revolutionized the manner in which communication unfolds, enabling users to spontaneously generate, disseminate, share, and aggregate multimedia data across the internet. Nevertheless, in this exchange of information, OSM platforms assume a dominant, central role, wielding excessive power. Blockchain online social media (BOSM) seeks to mitigate the drawbacks of traditional centralized OSM by leveraging the decentralized nature of blockchain technology, migrating the functionalities of social media into a decentralized realm, and positioning the users at the core of the OSM ecosystem. However, current BOSM models often rely on tokens for incentives and are hampered by the centralized, inefficient blockchain consensus mechanisms, alongside vulnerabilities such as collusion attacks. This paper introduces a novel blockchain system, NexoNet, tailored for decentralized social media, exploring the application of blockchain technology in the realm of online social media from both technical and economic perspectives. The NexoNet quantifies and evaluates user participation within the system, employing a multiple incentive mechanism to equitably distribute value created by users without the need for tokens. Furthermore, we propose the Proof-of-Active-Participation (PoAP) blockchain consensus mechanism, enabling all users to partake in the maintenance of the blockchain system, thus ensuring its security and efficiency. Theoretical analysis and simulations across various scenarios demonstrate that the NexoNet, with extensive user engagement, achieves equitable value distribution through its multiple incentive mechanism. It successfully safeguards against a spectrum of malicious attacks and attains high transaction processing efficiency. The simulation results show that NexoNet achieves an average transaction throughput of 2000 transactions per second (TPS) and a consensus delay of 2.385 s with 100 maintainers in the network. Furthermore, our tests demonstrated that even collusion with users comprising 75% of the total would only allow an additional 30 chances to propose a block. By deeply integrating user behavior with the underlying mechanisms of the blockchain system, the NexoNet fosters a user-centric blockchain social media ecosystem.

Skill Verification Using Blockchain Technology : Ensuring Transparency and Trust

Blockchain technology, with its decentralized, immutable, and transparent nature, offers a promising solution for verifying skills and credentials. This paper explores the potential of blockchain in skill verification, highlighting its advantages, challenges, and potential applications. We delve into the technical aspects of implementing blockchain-based skill verification systems, discussing key considerations such as consensus mechanisms, smart contracts, and data privacy. Additionally, we examine the challenges that may arise in the adoption and implementation of blockchain technology for skill verification, including scalability, interoperability, and regulatory compliance. Finally, we conclude by discussing the future prospects and potential impact of blockchain-based skill verification on various industries

Blockchain Consensus Mechanisms: A Bibliometric Analysis (2014–2024) Using VOSviewer and R Bibliometrix

Blockchain consensus mechanisms play a critical role in ensuring the security, decentralization, and integrity of distributed networks. As blockchain technology expands beyond cryptocurrencies into broader applications such as supply chain management and healthcare, the importance of efficient and scalable consensus algorithms has grown significantly. This study provides a comprehensive bibliometric analysis of blockchain and consensus mechanism research from 2014 to 2024, using tools such as VOSviewer and R’s Bibliometrix package. The analysis traces the evolution from foundational mechanisms like Proof of ork (PoW) to more advanced models such as Proof of Stake (PoS) and Byzantine Fault Tolerance (BFT), with particular emphasis on Ethereum’s “The Merge” in 2022, which marked the historic shift from PoW to PoS. Key findings highlight emerging themes, including scalability, security, and the integration of blockchain with state-of-the-art technologies like artificial intelligence (AI), the Internet of Things (IoT), and energy trading. The study also identifies influential authors, institutions, and countries, emphasizing the collaborative and interdisciplinary nature of blockchain research. Through thematic analysis, this review uncovers the challenges and opportunities in decentralized systems, underscoring the need for continued innovation in consensus mechanisms to address efficiency, sustainability, scalability, and privacy concerns. These insights offer a valuable foundation for future research aimed at advancing blockchain technology across various industries.

MetaBlock: A Revolutionary System for Healthcare Industry Fusing Metaverse and Blockchain

The Metaverse is like another world functioning parallel to the actual physical world. It merges physical reality with digital virtuality by the convergence of different technologies that enable interactions with virtual objects and environment. The complete immersive experience with metaverse generates huge data which comes with its own set of challenges, a major one being the security and storage of user centric data. Considerably, blockchain offers a significant solution due to its exceptional features of decentralization, immutability, and transparency. For a detailed insight into the role of blockchain in the metaverse, the paper explores its usage in the healthcare industry. The paper then proposes a healthcare system named MetaBlock that is a fusion of both the metaverse and blockchain techniques. The paper discusses the components of the system from a detailed technical interpretation, such as data acquisition, data storage, virtual object and space simulation, data sharing and data privacy protection. Finally, an important research direction in terms of distributed consensus mechanism is discussed.

Blockchain Scalability with Proof of Descriptor

Blockchain networks use consensus mechanisms so that participants can exchange transactions without the need to rely on a trusted third party. Consensus mechanisms using Proof of Work burn significant energy to select a block miner, and this delay limits performance. Other consensus mechanisms such as Proof of Stake or Practical Byzantine Fault Tolerance still designate a single validator to append a block to the chain, preventing blocks from being built and published in parallel. In this paper we introduce a new consensus mechanism, Proof of Descriptor, enabling clients to work together to publish blockchain transactions using a descriptor object which stores information on the cooperative parallel execution of transactions. Proof of Descriptor consensus allows commutative transactions to be mined concurrently. It does not require a single leader to append transactions to the ledger, enabling clients to cooperate on publishing transactions. We also propose a novel graph-based ledger with multiple entry points to facilitate the scalability of Proof of Descriptor, as well as a secure hashing scheme to resist long-range-attacks. We demonstrate that our approach is as secure as related works with respect to a malicious leader, 51% attack, and other known blockchain vulnerabilities. Furthermore, our experimental evaluation shows that our approach scales with the size of the network, experiencing up to a 4x improvement in throughput over the fastest sequential blockchain, Solana .

Strategic behavior in multi-criteria sorting with trust relationships-based consensus mechanism: Application in supply chain risk management

Strategic behavior is common in multi-criteria sorting, where manipulated alternatives are allocated to the target category to achieve the intended goal. Engaging in such strategic behavior in sorting consensus often comes at a cost, which is closely tied to the degree of preference adjustments and the level of trust relationships among decision makers. This study investigates strategic behavior using piecewise cost-based consensus mechanism in social trust network. Firstly, the trust relationship dependent piecewise cost is formally defined and formulated by considering the impact of trust relationship on the preference adjustments willingness to achieve sorting consensus. Then, based on the trust relationship dependent piecewise cost, a preference strategic manipulation model is proposed to achieve strategic behavior in sorting consensus, which is implemented by minimizing the cost of strategically guiding decision makers in adjusting their preferences. Considering that social trust network affects strategic manipulation, a preference-network collaborative strategic manipulation model is further proposed, which is designed to strategically guide decision makers in adjusting both their preferences and social trust networks. Moreover, the practicality of proposed strategic manipulation models is exemplified through a case study on supply chain risk management and their performance is validated via simulation analysis.

Trustworthy V2G scheduling and energy trading: A blockchain-based framework

The rapid growth of electric vehicles (EVs) and the deployment of vehicle-to-grid (V2G) technology pose significant challenges for distributed power grids, particularly in fostering trust and ensuring effective coordination among stakeholders. Establishing a trustworthy V2G operation environment is crucial for enabling large-scale EV user participation and realizing V2G’s potential in real-world applications. In this paper, an integrated scheduling and trading framework is developed to conduct transparent and efficacious coordination in V2G operations. In blockchain implementation, a cyber-physical blockchain architecture is proposed to enhance transaction efficiency and scalability by leveraging smart charging points (SCPs) for rapid transaction validation through a fast-path practical byzantine fault tolerance (fast-path PBFT) consensus mechanism. From the energy dispatching perspective, a game-theoretical pricing strategy is employed and smart contracts are utilized for autonomous decision-making between EVs and operators, aiming to optimize the trading process and maximize economic benefits. Numerical evaluation of blockchain consensus shows the effect of the fast-path PBFT consensus in improving systems scalability with a balanced trade-off in robustness. A case study, utilizing real-world data from the Southern University of Science and Technology (SUSTech), demonstrates significant reductions in EV charging costs and the framework’s potential to support auxiliary grid services.

Dynamic Compromise Behavior Driven Bidirectional Feedback Mechanism for Group Consensus With Overlapping Communities in Social Network

Dynamic Compromise Behavior Driven Bidirectional Feedback Mechanism for Group Consensus With Overlapping Communities in Social Network

Performance analysis and evaluation of postquantum secure blockchained federated learning

As the field of quantum computing progresses, traditional cryptographic algorithms such as RSA and ECDSA are becoming increasingly vulnerable to quantum-based attacks, underscoring the need for robust post-quantum security in critical systems like Federated Learning (FL) and Blockchain. In light of this, we propose a novel hybrid approach for blockchain-based FL (BFL) that integrates a stateless signature scheme, such as Dilithium or Falcon, with a stateful hash-based scheme like XMSS. This combination leverages the complementary strengths of both schemes to provide enhanced security. To further optimize performance, we introduce a linear formula-based device role selection method that takes into account key factors such as computational power and stake accumulation. This selection process is reinforced by a verifiable random function (VRF), which strengthens the blockchain consensus mechanism. Our extensive experimental results demonstrate that this hybrid approach significantly enhances both the security and efficiency of BFL systems, establishing a robust framework for the integration of post-quantum cryptography as we transition into the quantum computing era.

A Relative Projection-Based Multiattribute Group Decision-Making Model With Noncooperative Behavior Management and Application to NEV Supplier Selection.

This article reports a novel consensus model where a group of internal and external experts evaluate alternatives under multiple attributes and provide mutual evaluations. First, different from previous studies, the cognitive and interest conflicts of internal and external experts are considered simultaneously. But interest conflict is emphasized for internal experts, and cognitive conflict is mainly considered for external experts. Second, we explore the categorization and management methods of noncooperative behaviors (NCBs) of experts. The relative projection-based indexes are proposed for the first time to measure the degrees of cognitive and interest conflicts by using multiattribute preference matrices (MAPMs) and the weight vectors of attributes. A group of experts are divided into three categories and the corresponding management strategies are developed. Third, we investigate the consensus mechanism among experts with cognitive and interest conflicts. For reaching an acceptable consensus level, an adjustment process is proposed to revise some local entries in MAPMs and mutual evaluation matrix (MEM). A penalty mechanism is further established to dynamically update the weights of experts. An algorithm is designed to capture the consensus reaching process in multiattribute group decision making, where internal and external experts are distinguished by proposing a parameter. Finally, the high-performance battery supplier selection of new energy vehicle is studied to illustrate the proposed model. The results reveal that the efficiency of reaching consensus can be enhanced by using the developed model with effective management of NCBs.

Blockchain-based Reputation System for Smart Farm Anomaly Detection and Prevention

While smart farming is becoming increasingly popular as a way to improve the efficiency and sustainability of agroecosystems and global food security, its vulnerability to cyber-attacks is rapidly increasing. A distributed reputation system can help detect and prevent malicious activities by tracking the reputation of IP addresses of devices, products, and entities in a smart farming system, thereby enhancing its security and trust. In this paper, we propose a blockchain-based reputation system for IP addresses in smart farms for real-time intrusion detection and prevention. The study uses the Ethereum blockchain smart contracts, Oracles, Intrusion Detection System (IDS), and a Proof-of-Reputation (PoR) consensus mechanism. The system was evaluated on two datasets, the Spamhaus Blocklist, and the Malware Domain List datasets. It achieved high accuracy, recall, and precision rates, F1 score, as well as low false positive and false negative rates. This shows that the proposed system has high potential to be an effective tool for improving malware detection and prevention in real-time, creating a trusted supply chain for a smart farming ecosystem against a wide range of attack types, including denial-of-service attacks, probe attacks, and user-to-root attacks.

Hybrid-Blockchain-Based Electronic Voting Machine System Embedded with Deepface, Sharding, and Post-Quantum Techniques

The integrity of democratic processes relies on secure and reliable election systems, yet achieving this reliability is challenging. This paper introduces the Post-Quantum Secured Multiparty Computed Hierarchical Authoritative Consensus Blockchain (PQMPCHAC-Bchain), a novel e-voting system designed to overcome the limitations of current Biometric Electronic Voting Machine (EVM) systems, which suffer from trust issues due to closed-source designs, cyber vulnerabilities, and regulatory concerns. Our primary objective is to develop a robust, scalable, and secure e-voting framework that enhances transparency and trust in electoral outcomes. Key contributions include integrating hierarchical authorization and access control with a novel consensus mechanism for proper electoral governance. We implement blockchain sharding techniques to improve scalability and propose a multiparty computed token generation system to prevent fraudulent voting and secure voter privacy. Post-quantum cryptography is incorporated to safeguard against potential quantum computing threats, future-proofing the system. Additionally, we enhance authentication through a deep learning-based face verification model for biometric validation. Our performance analysis indicates that the PQMPCHAC-Bchain e-voting system offers a promising solution for secure elections. By addressing critical aspects of security, scalability, and trust, our proposed system aims to advance the field of electronic voting. This research contributes to ongoing efforts to strengthen the integrity of democratic processes through technological innovation.

Application of Blockchain in Procurement and Management of Building Services: A Critical and Systematic Review

Building services systems are essential for creating a comfortable and safe living environment in buildings. These are complex systems with high stakeholder involvement, a lengthy lifecycle, and high financial costs. This leads to building services systems having complex procurement and management (P&M) requirements which create a multitude of challenges. Blockchain technology has emerged as a revolutionary digital technology under “Procurement 4.0”. The purpose of this paper is to investigate the applicability of blockchain technology for systematic procurement and management of building services. The science mapping method was used to systematically and quantitatively analyse 102 publications related to bibliographic records retrieved from Scopus and the Web of Science databases. This includes content analysis of the existing issues, current trends of technologies, and applicability of blockchain in the P&M of building services. The results of the bibliometric analysis indicate that publications had grown significantly faster in 2021 related to the P&M of building services with new technologies while there is a minimal collaboration of countries, organisations and authors in publishing research in this area. Further, it is observed that Building Information Modelling (BIM) is the main technology utilised in general P&M. As a result of content analysis, a total of 28 issues that affect the performance of procurement and management of building services are identified. The paper critically evaluates blockchain technology in terms of peer-to-peer networks, hashing algorithms, public key cryptography, consensus mechanisms, smart contracts, and distributed ledger. It indicates that blockchain provides a perfect match for resolving these issues. The findings of the research will open a path to apply blockchain technology in building services. The study offers a readily available point of reference for practitioners, policymakers and research and development bodies.

Large Group Failure Mode and Effects Analysis Method Considering Individual Concerns and Integrated Consensus Mechanism in Social Network Context: An Application to Mobile Medical Privacy Risk Evaluation

Large Group Failure Mode and Effects Analysis Method Considering Individual Concerns and Integrated Consensus Mechanism in Social Network Context: An Application to Mobile Medical Privacy Risk Evaluation

Reputation-Driven Asynchronous Federated Learning for Optimizing Communication Efficiency in Big Data Labeling Systems

With the continuous improvement of the performance of artificial intelligence and neural networks, a new type of computing architecture-edge computing, came into being. However, when the scale of hybrid intelligent edge systems expands, there are redundant communications between the node and the parameter server; the cost of these redundant communications cannot be ignored. This paper proposes a reputation-based asynchronous model update scheme and formulates the federated learning scheme as an optimization problem. First, the explainable reputation consensus mechanism for hybrid intelligent labeling systems communication is proposed. Then, during the process of local intelligent data annotation, significant challenges in consistency, personalization, and privacy protection posed by the federated recommendation system prompted the development of a novel federated recommendation framework utilizing a graph neural network. Additionally, the method of information interaction model fusion was adopted to address data heterogeneity and enhance the uniformity of distributed intelligent annotation. Furthermore, to mitigate communication delays and overhead, an asynchronous federated learning mechanism was devised based on the proposed reputation consensus mechanism. This mechanism leverages deep reinforcement learning to optimize the selection of participating nodes, aiming to maximize system utility and streamline data sharing efficiency. Lastly, integrating the learned models into blockchain technology and conducting validation ensures the reliability and security of shared data. Numerical findings underscore that the proposed federated learning scheme achieves higher learning accuracy and enhances communication efficiency.

Blockchain Based Analytical Bug Tracking in Software Engineering

This article examines a blockchain-based bug tracking system in detail, focusing on its four main components: the Blockchain Platform, the Consensus Mechanism (also known as Proof of Work, PoW), the Data Structure, and Smart Contracts. To improve the efficiency, security, and transparency of bug tracking in software development, we use mathematical models to dissect the operational framework and functionalities that underpin this cutting-edge system. The Blockchain Platform is the foundational layer. It stores data in multiple locations, cannot be changed, and provides a secure environment for fixing software bugs. We use mathematical abstractions to demonstrate how the blockchain is put together, emphasizing the importance of cryptographic hashes in maintaining data integrity and connecting blocks. People pay close attention to the Consensus Mechanism, particularly Proof of Work (PoW), because it is so important for verifying transactions and maintaining the blockchain's integrity. Using a mathematical model, we demonstrate how Proof of Work (PoW) prevents bad behavior while keeping the network safe and democratic by requiring work to be done on a computer to add blocks. The Data Structure module is examined using a model that depicts how bug reports are stored and found on the blockchain. This model demonstrates the efficiency of storing bug reports as transactions, which allows for quick access and unchangeable record-keeping. People associate smart contracts with self-running programs that manage permissions, automate workflows, and provide incentives for reporting bugs. Mathematical models are used to demonstrate how these contracts' conditions and actions are documented, emphasizing their importance in automating tasks and improving system reliability. This article uses mathematical modeling to provide a clear and structured understanding of a blockchain-based bug tracking system and demonstrate how it could change the way bugs are tracked by leveraging blockchain technology's strengths.