IET Blockchain最新文献

Cryptocurrency blockchain networks safeguard digital assets using cryptographic keys, with wallets playing a critical role in generating, storing, and managing these keys. Wallets, typically categorized as hot and cold, offer varying degrees of security and convenience. However, they are generally software-based applications running on microcontrollers. Consequently, they are vulnerable to malware and side-channel attacks, allowing perpetrators to extract private keys by targeting critical algorithms, such as ECC, which processes private keys to generate public keys and authorize transactions. To address these issues, this work presents EthVault, the first hardware architecture for an Ethereum hierarchically deterministic cold wallet, featuring hardware implementations of key algorithms for secure key generation. Also, an ECC architecture resilient to side-channel and timing attacks is proposed. Moreover, an architecture of the child key derivation function, a fundamental component of cryptocurrency wallets, is proposed. The design minimizes resource usage, meeting market demand for small, portable cryptocurrency wallets. FPGA implementation results validate the feasibility of the proposed approach. The ECC architecture exhibits uniform execution behavior across varying inputs, while the complete design utilizes only 27%, 7%, and 6% of LUTs, registers, and RAM blocks, respectively, on a Xilinx Zynq UltraScale+ FPGA.

In this paper, CoINS-Parking, a compressed IoT blockchain network for smart parking systems, is presented. Smart parking collects data and processes it to provide real-time information about parking availability. This data includes the environmental information through the sensors and the users' information, which mainly has a confidentiality requirement. In CoINS-Parking, this data is transmitted to the blockchain network using a hybrid mesh-star topology. Data integrity, confidentiality, and memory management are the main requirements of this data-driven system that are provided through hashing, encryption, and data compression. Moreover, the response time of CoINS-Parking is improved by optimizing the mentioned schemes and modifying the conventional hash structure. This scheme finds the previous chain of the network in a short time, employing the largest prime factor in tree construction. To evaluate the efficiency of the proposed method, various experiments are considered, and it is compared to related studies. Based on these experiments, CoINS-Parking outperforms related methods in terms of memory and gas usage by about 4.4% and improves their security dramatically in cost of about 11% increase in execution time.

Cryptocurrency taxation poses a fundamental dilemma: how to ensure compliance while protecting privacy and enabling real-time cross-border coordination. This paper introduces a blockchain-driven framework to address these challenges. First, a permissioned consortium chain with a multi-channel architecture links OECD tax authorities, compliant exchanges and international organizations, safeguarding data sovereignty. Second, a dynamic account-transaction graph with rule-guided subgraph templates detects hidden ‘tax-base dark matter’ behaviours, including mixing services, cross-chain transfers and NFT profit masking. Third, a zero-knowledge proof protocol (zero-knowledge-TaxProof) encodes tax rules into verifiable arithmetic circuits, allowing taxpayers to prove taxable conditions without exposing details. Fourth, a dynamic-weight PBFT mechanism ties node voting power to data integrity, accuracy and responsiveness, enabling multinational collaboration. Fifth, off-chain identity anchoring with on-chain KYC decoupling preserves privacy while permitting traceability strictly under judicial authorization. Finally, a real-time dashboard and adaptive early-warning system monitors global tax-base changes with sub-minute responsiveness. Experiments on a Hyperledger Fabric testbed show the model achieves 87.8% identification accuracy, an average dark-matter capture rate of 88.9%, leakage entropy of 2.3 bits and event confirmation within 53 s. These results demonstrate a feasible, sustainable paradigm for reconstructing global digital tax governance that balances privacy, compliance and efficiency.

The popularity of mobile smart terminals has driven edge computing to become a research hotspot, and blockchain technology provides a new way to address data security 15 in edge computing; however, traditional consensus algorithms are difficult to adapt to IoT environments with limited storage and computational resources. For this reason, this paper proposes a Practical Byzantine Fault Tolerance (PBFT) consensus optimisation algorithm based on dynamic reputation and adaptive clustering (DRAC-PBFT). First, a hierarchical regulation model based on dynamic reputation is proposed, where nodes are divided into upper-layer and lower-layer node sets according to their reputation values, which are responsible for consensus decision-making and data validation and forwarding, respectively. A reputation assessment mechanism based on node roles and behaviours is proposed to dynamically adjust the node tiers and maintain incentives. The master node selection is randomly generated in the upper-layer nodes using SHA-256 hash to ensure security. Second, the weight factor and the number of clusters K are dynamically adjusted by comprehensively considering the node reputation and load condition, and the geographic coordinates and Euclidean distance of the edge gateway nodes are used for efficient clustering to optimise the data transmission path and reduce the latency. Finally, a two-layer consensus mechanism with separation of duties is designed, where the lower-layer nodes pre-verify the transactions within the cluster and submit only qualified data to the cluster head to reduce redundant communication. Inter-cluster interactions are coordinated by the upper consensus layer to ensure consistency and optimize data synchronisation. Experimental results show that DRAC-PBFT improves the average throughput by 67% and reduces the average delay by 50% compared to PBFT. Compared with other PBFT improvement algorithms, DRAC-PBFT shows better performance in large-scale consortium chain environments, and is suitable for IoT or edge computing environments with limited computing resources and stringent requirements on latency and throughput.

In the current Internet era, whether the domain name system (DNS) can achieve efficient resolution is of great significance for optimizing user experience and promoting global development. However, the existing DNS architectures have flaws in dealing with network service latency and ensuring their own robustness. Based on this, this study constructs a blockchain-based distributed domain master architecture, aiming to optimize the resolution effect of top-level domains (TLDs). As internet service latency continues to pose severe challenges to user experience and global development, the demand for accelerated DNS resolution always exists. Although local caching has always been helpful in improving DNS efficiency, how to ensure the integrity of cached records is a tricky problem. The new architecture proposed in this study adopts a consortium blockchain framework, allowing nodes to freely enter and exit. Consensus is reached through the 3R-PBFT algorithm, strengthening system security. Focusing on the top-level domains of.com and.net, an in-depth exploration is conducted on the effect of locally deployed caches on resolution time, highlighting the key value of TLD caches in enhancing the DNS resolution speed. Experimental results show that the local cache implemented through the consortium blockchain architecture can not only improve the security of the cache but also reduce the latency of DNS resolution.

The distributed denial of service (DDoS) attacks represent a real danger on cloud computing systems, the existing security approaches have notable limitations such as centralization, lack of adaptability and scalability, and focusing on detection over mitigation. In this paper, we present a novel blockchain-based system to enhance attack tolerance of cloud systems against DDoS attacks by integrating a hierarchical risk-based cloud attack tolerance mechanism with smart contracts, The proposed approach ensures comprehensive threat detection and mitigation by estimating risks at all three layers: local, cluster, and global dynamically using Dempster–Shafer theory. Simulations validated the superiority of our approach compared to similar systems in terms of availability, attack detection rate, and packet loss metrics in large-scale cloud simulation of 10,000 nodes. The results demonstrate that our system not only improves security but also maintains service quality under high-intensity attack scenarios. Additionally, the implementation of our blockchain architecture shows significant scalability and cost-efficiency, thus, confirming its suitability for large cloud deployments. Furthermore, the reliability of the smart contracts against potential threats were confirmed by a formal security analysis using the Echidna tool.

As a disruptive technology, blockchain has attracted widespread attention from academia and industry. However, current blockchain technologies still suffer from many severe problems, for example, insufficient trust and security, vulnerability to attacks, low efficiency, poor scalability, low throughput, high energy consumption, privacy leakage, and the inability to remove dishonest or harmful information once it has been recorded. Hence, blockchain evolution is urgently demanded, including its fundamental architecture, consensus mechanism, and new applications. The recent advances in artificial intelligence have offered opportunities to detect anomalies and optimise resources. The evolution of blockchain in architecture, intelligence, and consensus protocol will further extend its applications to broader fields. The current special issue is focused on research ideas, articles and experimental studies related to ‘Blockchain Evolution: Architecture and Applications’ for learning, analysing, and forecasting the various aspects of blockchain.

In this special issue, we have received 12 papers, all of which underwent peer review. Of the 12 originally submitted papers, three have been accepted and nine have been ‘rejected with referral,’ that is, they did not meet the IET Blockchain criteria for publication. Thus, the overall submissions were of high quality, which marks the success of this special issue.

The three eventually accepted papers can be clustered into three main categories, namely theoretical, applications and case studies. The papers in the first category introduce innovations in Ethereum cost optimisation in Layer 2 rollups via EIP-4844, including gas efficiency and economic analysis, to provide solutions for gas costs and system design. The paper in this category is by Dyade et al. The second category of paper designs a system for the blockchain-based intelligent disbursement in national scholarship portal. The paper in this category is by Samu et al. The last category proposes a case study for the adoption of blockchain-based cryptocurrency as a payment method in Saudi Arabia. The paper in this category is by Alrehaili et al. A brief presentation of each of the papers in this special issue follows.

Dyade et al. introduce a comprehensive gas efficiency and economic analysis of EIP-4844's impact on Layer 2 rollups, providing mathematical models, simulation results and architectural diagrams to illustrate the improvements in gas costs and system design. EIP-4844 is poised to drive significant improvements in the efficiency, performance and cost-effectiveness of Ethereum Layer 2 rollups, paving the way for a more scalable and economically viable blockchain ecosystem. Access the full paper using the following link: https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/blc2.70014

Samu et al. propose a blockchain-based scholarship module to address these challenges and automate the entire scholarship pro

This paper introduces an architecture for a next-generation airline system, utilising cloud-based microservices, distributed Artificial intelligence (AI), and blockchain to overcome critical system limitations of scale, integrity of data, and avenues of customer inefficiency. In the modular architecture, reservations, payments, and customer profiles can be managed independently, thereby improving scalability by 40% and availability by 30%. AI modules analyse historical data of bookings and user behaviours for demand forecasting and for making personalised recommendations, which, in turn, increases customer engagement by 25%. Blockchain provides proper secure tamper-proof record-keeping of transactions, thereby minimising fraud and increasing data transparency by 20%. The proposed system was evaluated under real-world traffic occurrences, simulating concurrent users in the range of 100–1000, employing a simulation platform that was built for this purpose. The proposed approach reduces transaction latency by 15% and offers a 35% enhancement in throughput for secure data as compared to the usual Systems - Ablation confirms that each module (AI, blockchain, microservices) contributes uniquely to the performance of the system. This architecture holds cross-domain potential, especially for logistics and hospitality. The findings emphasise the transformation possible when we use AI, blockchain, and cloud services in mission-critical, high-demand environments.

This manuscript presents an exhaustive review of blockchain-based mixing services, aiming to fill the existing gap between academic innovations and real-world implementations. Starting with an identification of the core functionalities and techniques employed by mixing services, the paper delves into detailed explanations of these operational mechanisms. It further outlines an evaluation framework tailored for a rigorous assessment, highlighting the key vulnerabilities and strengths of various solutions. In addition, the study identifies potential attack vectors that compromise these services. The paper explores the dual nature of mixing services: while they contribute to the preservation of privacy—a cornerstone of blockchain technologies—they can also facilitate illicit activities. By addressing key research questions, this study not only offers a comprehensive overview of the current state of mixing services but also sets the stage for future academic discourse in this evolving field.

The rapid development of educational informatisation has made smart classrooms a key platform for advancing innovative teaching methods. However, traditional evaluation systems face challenges related to data security, fairness, and result traceability. This paper introduces a blockchain-based teaching evaluation system for smart classrooms to address these issues and improve teaching quality and management efficiency. The system employs a cloud-network-edge-device architecture, integrating cloud computing, network communication, and edge devices for real-time data collection, secure transmission, and intuitive visualisation. Blockchain technology ensures data integrity and transparency, while the practical Byzantine fault tolerance consensus algorithm maintains system reliability and prevents data manipulation. Experiments conducted at Dalian Jiaotong University demonstrate that the smart classroom improves teaching quality by 20% compared to traditional classrooms. The system is particularly effective in enhancing teaching resources and real-time communication, though improvements in student engagement are still needed. System performance tests indicate that the platform maintains low response times and stability under varying levels of concurrent requests, demonstrating its capability to support high-demand teaching scenarios and ensure data consistency and transparency.