IET Blockchain最新文献

Traditional voting procedures are non-remote, time-consuming, and less secure. While the voter believes their vote was submitted successfully, the authority does not provide evidence that the vote was counted and tallied. In most cases, the anonymity of a voter is also not sure, as the voter's details are included in the ballot papers. Many voters consider this voting system untrustworthy and manipulative, discouraging them from voting, and consequently, an election loses a significant number of participants. Although the inclusion of electronic voting systems (EVS) has increased efficiency; however, it has raised concerns over security, legitimacy, and transparency. To mitigate these problems, blockchain technology has been leveraged and smart contract facilities with a combination of artificial intelligence (AI) to propose a remote voting system that makes the overall voting procedure transparent, semi-decentralized, and secure. In addition, a system that aids in boosting the number of turnouts in an election through an incentivization policy for the voters have also developed. Through the proposed virtual campaigning feature, the authority can generate a decent amount of revenue, which downsizes the overall cost of an election. To reduce the associated cost of transactions using smart contracts, this system implements a hybrid storage system where only a few cardinal data are stored in the blockchain network.

Blockchain is a powerful technology to facilitate decarbonization, decentralization, digitalization, and democratization (4D's) of the energy systems of the future. The 4D's are the driving forces of transition into new energy systems that are more sustainable, resilient, efficient, and equitable. Although this technology can be applied to a wide spectrum of applications in the power sector, a set of challenges and limitations still need to be addressed to facilitate a full-scope implementation in energy systems. This paper presents an overview of blockchain technology from its inception through its most recent evolution and presents a thematic review of state of the art in the application of this technology in power systems. Further, it addresses the barriers preventing the power sector from large-scale, full-scope adoption of this technology. Finally, the emerging blockchain trends in the near future will be discussed and its potential to facilitate a secure, decentralized energy trading platform will be investigated.

The ultra-dense deployment of unmanned aerial vehicles (UAVs) as mobile small cell base stations (SBS) is expected to support ultra-high-speed, ultra-reliable, and ultra-low-latency wireless connections in sixth generation (6G) wireless cellular networks. Inevitably, the explosively increasing number of SBSs each with ever-shrinking cell size will result in the spectrum scarcity and pose critical challenges to the spectrum management. Towards the centralized spectrum management system, a third-party authority is employed to coordinate the spectrum sensing, sharing, and allocation among participants. However, a centralized authority is vulnerable to numerous security threats, such as single point of failure, denial of service attacks, and privacy disclosure, and cannot guarantee fair and efficient spectrum management without mutual trusts among participants. To address these problems, a novel framework of blockchain-aided spectrum management is designed to securely record the spectrum auction data and spectrum allocation data in the decentralized spectrum sharing. Moreover, a trust management scheme is proposed to evaluate the trusts of all UAVs participating in the decentralized spectrum sharing, where the trust increase depends on legal use of spectrum allocation and honest report of spectrum sensing. In particular, it is shown that the proposed trust management can not only incentivize the UAVs to comply with the legal rule of spectrum sharing in blockchain, but also punish the malicious behaviour that either violates the spectrum sharing rule or provides misleading spectrum sensing results.

The industry 4.0 revolution leads by technologies such as distributed digital ledgers, big data processing techniques, automation, and the internet of things (IoT). The interest in the industrial internet of things (IIoT) has progressed rapidly with huge internet areas such as research, academics, and industries. Through a decentralised and distributed approach blockchain and IIoT ensure maximum security. In the distributed approach, every block is chained together with each other. This paper presented a survey on industry 4.0 and blockchain-based systems. The integration of blockchain, IoT devices, and industry 4.0 provides security, transparency, and scalability to the system. The paper also addresses many types of cyber attacks and possible solutions for blockchain based industrial internet of things (BIIoT) systems.

Nowadays, blockchain is an upcoming area for researchers from different research fields. Bitcoin, as the first successful cryptocurrency, has accumulated numerous data after its existence. Here, the Bitcoin transaction graph from a graph theory perspective is investigated with more available data given now. This paper mainly focuses on the transaction graph and provides researchers with both practical and theoretical sides of the data. Several existent measurements and some newer ones are first computed and analysed. These measurements help to interpret the transaction graph more extensively. A new modified Buckley–Osthus random graph model is proposed, and a simulation of the Chung–Lu model is attempted to represent the Bitcoin transaction network. Some suggestions are given to improve the modified Buckley–Osthus model and point out the pros and cons of these random graph models. Moreover, the experiments show that scale-free networks are fundamentally not a good model for Bitcoin transaction networks considering all the data, but the mechanics of preferential attachment is crucial. How to proceed with Bitcoin transaction graph theory from both theoretical and experimental perspectives for future studies is also discussed and analysed.

The cover image is based on the Original Research Bitcoin address clustering method based on multiple heuristic conditions by Xi He et al., https://doi.org/10.1049/blc2.12014.

Single heuristic method and incomplete heuristic conditions were difficult to cluster a large number of addresses comprehensively and accurately. Therefore, this paper analysed the associations between Bitcoin transactions and addresses and used six heuristic conditions to cluster addresses and entities. We proposed an improved change address detection algorithm and compared it with the original change address algorithm to prove the effectiveness of the improved algorithm. By adding conditional constraints, the identified change address was more accurate, and the convergence speed of the algorithm was accelerated. Our work presented the pseudo-anonymity mechanism of the Bitcoin system, which could be used by the law enforcement agencies to track and crack down illegal transactions.

Cross-chain is the key technology to achieve interconnectivity and interoperability across various blockchain networks. It surpasses traditional single-chain architecture in terms of the performance, capacity, privacy, economic and technical scalability. Cross-chain can break barriers between institutions, industries, and regions. This paper integrates existing blockchain interoperability technologies and proposes a distributed fusion cross-chain model in financial industry. In order to support large scale computing and high availability requirements in financial industry, the model is built on a decentralized architecture and highly scalable. It supports large-scale isomorphic or heterogeneous blockchain cross-chain data and state interaction. And it achieves reliable financial value circulation in various underlying blockchain networks.

Blockchain is a distributed ledger based on peer-to-peer networks, originally used for crypto-currency systems. Blockchains are being used as an enabling technology for decentralised applications in the areas of Internet-of-Things, finance, supply-chain and others. Consistency, data privacy, performance, and energy efficiency are of paramount importance in such applications. The full nodes of public, permissionless blockchains undertake the task of verifying the transactions generated by the network. Full nodes perform operations such as confirming balances, transactions, and history, i.e. mostly database search queries. Consequently, their throughput is crucial for the performance of blockchain systems. In this work, the benefits of accelerating the blockchain search and insert queries by leveraging GPU platforms are studied. An extensive comparison between the most dominant utilized database is provided, i.e. LevelDB, and MegaKV, a high-performance GPU-accelerated database. Realistic operations that take place in blockchain systems are emulated and evaluated over representative scenarios, showing three orders of magnitude gains in throughput and energy efficiency without compromising the security aspect. The extensive comparison between LevelDB and MegaKV indicates that GPU acceleration is an effective solution for runtime and energy efficiency enhancement of blockchain systems, and the integration of the two technologies is a promising field of research.