IET Blockchain最新文献

The National Scholarship Portal in India serves as a one-stop solution for students seeking financial aid for their studies across the country. However, in this digital era, the national-level portal faces challenges such as limited provision for only government scholarships, non-automated systems, complex application processes, reliance on physical verifications, and delays in scholarship disbursement. This research proposes a blockchain-based scholarship module to address these challenges and automate the entire scholarship process. The paper emphasizes upon the transformative impact by the usage of Hyperledger fabric network, which provides a fool-proof system that streamlines the entire application process and fund disbursement. The proposed integration also ensures robust application verification, accountability of stakeholders, transparent scholarship selection criteria, automated and thorough tracking of fund disbursement, immutable transaction history, secure authorization; and stringent compliance measures. Thus, the implementation of the proposed system aims to alleviate the financial insecurities faced by students during their studies, simplify their search for scholarship opportunities, and enable them to focus more on their academic pursuits.

On-chain sealed auctions represent a novel approach to electronic bidding auctions, wherein the introduction of zero-knowledge proof technology has significantly enhanced the security of auctions. However, most mainstream on-chain sealed auction schemes currently employ Bulletproofs to prove auction correctness, which leaves room for optimization in terms of verification time and inherent security. Addressing these issues, an on-chain sealed auction scheme based on zero-knowledge succinct non-interactive argument of knowledge (zk-STARK) is proposed. This scheme leverages the decentralization and immutability of blockchain and smart contracts to eliminate third-party involvement while ensuring the security of the auction process. The Inter Planetary File System is utilized to provide a qualification review mechanism for the auctioneer, enabling the screening of unqualified bidders before the auction. Additionally, the scheme employs RSA encryption to conceal bidders' bids, Pedersen commitments to ensure the consistency of bidding information, and zk-STARKs to verify the correctness of the winning bid. Security analysis and experimental results demonstrate that the proposed scheme meets the required security standards, with time consumption at various stages of the auction being within acceptable limits, and effectively reduces the time required for proof verification.

The development of Web 3.0 technology may signify the dawn of a new digital era. Its concepts of co-management, co-construction, and sharing address the need for private data sharing among medical institutions. However, the sharing of private data has been challenging due to the lack of effective monitoring methods and authorization mechanisms. Additionally, controlling the scope of data sharing, providing incentives, and ensuring legal compliance have presented difficulties. To this end, a medical privacy data security sharing model based on key technologies of Web 3.0 has been proposed and implemented. It stores the source data in Inter Planetary File System by constructing an index of private data keywords, generates trapdoors using query keywords, and achieves retrieval of ciphertext data. Finally, data users apply to multiple parties for joint secure computing to obtain the use of private data. The experimental results indicate that when the size of the private data is less than 5 MB, with 3000 ciphertext indexes and three search keywords, both encryption and decryption times are around 50 ms, and the retrieval time is approximately 1.6 s. This performance is adequate for typical medical privacy sharing and computing scenarios.

Airport checked luggage entails specific requirements for speed, stability, and reliability. The issue of abnormal retention of checked luggage presents a significant challenge to aviation safety and transportation efficiency. Traditional luggage monitoring systems exhibit limitations in terms of accuracy and timeliness. To address this challenge, this paper proposes a real-time detection and alerting of luggage anomaly retention based on the YOLOv5 object detection model, leveraging visual algorithms. By eliminating cloud servers and deploying multiple edge servers to establish a private chain, images of anomalously retained luggage are encrypted and stored on the chain. Data users can verify the authenticity of accessed images through anti-tampering algorithms, ensuring the security of data transmission and storage. The deployment of edge computing servers can significantly reduce algorithm latency and enhance real-time performance. This solution employs computer vision technology and an edge computing framework to address the speed and stability of checked luggage transportation. Furthermore, blockchain technology greatly enhances system security during operation. A model trained on a sample set of 4600 images achieved a luggage recognition rate of 96.9% and an anomaly detection rate of 95.8% in simulated test videos.

In order to encourage participants to actively join the data sharing and to meet the distributed structure and privacy requirement in the medical consortium, the data-sharing strategy based on the master-slave multichain is presented in this paper. According to the different computing resources and the responsibility of participants, the adaptive Proof of Liveness and Quality consensus and hierarchical federated learning algorithm for master-slave multichain are proposed. Meanwhile, by quantifying the utility function and the optimization constraint of participants, this paper designs the cooperative incentive mechanism of medical consortium in multi-leader Stackelberg game to solve the optimal decision and pricing selection of the master-slave multichain. The simulation experiments show that the proposed methods can decrease the training loss and improve the parameter accuracy by MedMINST datasets, as well as reach the optimal equilibrium in selection and pricing strategy in the system, guaranteeing the fairness of profit distribution for participants in master-slave multichain.

Blockchain trilemma is a considerable obstacle for today's decentralized systems. It is hard to achieve a perfect balance among decentralization, security, and scalability. Many popular blockchain platforms sacrifice scalability to preserve decentralization and security, resulting in low speed, reduced throughput, and poor real-time performance (the time from transaction initiation to confirmation). Currently, there are several technologies, such as sharding, directed acyclic graph technology, sidechains, off-chain state channels etc., that aim to improve throughput and real-time performance. However, most of these solutions compromise the core feature of blockchain, which is decentralization, and introduce new security risks. In this paper, the authors propose a novel method, called MEchain, based on the Proof of Time Series Algorithm. MEchain consists of two models: the multi-chain model and the elastic-chain model. The authors’ experimental results show that these two models can enhance real-time performance and throughput to a higher level in the industry.

Metaverse is a new ecology that integrates the digital world with the physical world, generates a mirror image of the real world based on digital twin technology, and guarantees the fairness of the virtual world through the trusted mechanism of blockchain. Cross-chain communication technology is the key to realizing data circulation and collaborative processing between blockchains, which provides the communication foundation for the massive connection of blockchains in the metaverse. The current cross-chain communication mode is dominated by direct-connect routing, leading to network congestion and high propagation delay once the direct-connect link fails and cannot be recovered quickly. To optimize direct-connect routing, this paper proposed a cross-chain routing optimization strategy based on RON (Resilient Overlay Network), that is, Cross-Chain_RON, which firstly applies RON to reconstruct the direct-connect routing model, and then selects the optimal link through the shortest-path algorithm and policy routing, and combines with the RON performance database to improve the data transmission efficiency. Finally, the two communication modes were simulated by simulation tools. The experiments show that Cross-Chain_RON outperforms the direct-connect routing in terms of latency, rate of successful data transmission, and throughput in poor network environments, but at the expense of a certain amount of system overhead.

In recent years, the Metaverse has gained attention as a hub for technological revolution. However, its main platform suffers from issues like low-quality content and lackluster virtual environments, leading to subpar user experiences. Concerns arise from declining interest in NFTs and failed virtual real estate ventures, casting doubt on the Metaverse's future. Artificial intelligence generated content (AIGC) emerges as a key driver of Metaverse advancement, using AI to create digital content efficiently and affordably. AIGC also enables personalized content, enhancing the Metaverse. This paper examines the link between the Metaverse and AIGC, exploring AIGC's applications, underlying technologies, and future challenges. It reveals that while AIGC shows promise for improving the Metaverse, its technologies must better align with development needs to deliver immersive experiences.