Traceability model based on improved witness mechanism

Abstract

Traceability system is one of the popular applications of graphic blockchains. However, there are centralisation problems and a long time for final consistency confirmation in the graphic blockchain. In addition, the blockchain system in the traceability application scenario has the problem of insufficient supervision. Therefore, a witness‐based graphic blockchain consensus mechanism is proposed. In the consensus mechanism, a verifiable random function is used to screen the publishers of the unit; an SM2 threshold signature is used to sign the unit information to improve the non‐repudiation of the traceability information uploaders to the unit information under the supervision of the witness. The improved consistency algorithm cancels the process of finding a stable main chain and makes relatively many nodes to participate in the consensus process. The experimental results show that the graphic blockchain using the improved witness mechanism can reduce the degree of centralisation, shorten the time for new units to reach consensus, and greatly ensure the security and scalability of the blockchain system.

Machine learning and human‐machine trust in healthcare: A systematic survey

“…Medical machines not only need to be trained with large amounts of data, but also need to be personalised for different medical individuals to assist in treatment [83]. That is, during the training process, researchers need to train the characteristics for different patients, based on their individual medical data.…”

“…Personalised models can leverage a combination of big data and individual‐specific data to provide more reliable predictions and monitoring. Transfer learning is a technique where a pre‐trained DL model is used as a starting point and fine‐tuned on a smaller dataset specific to an individual or a subgroup [83]. By leveraging the knowledge learned from big data, this approach can be used to adapt the model to an individual's unique physiology and improve its reliability for individual predictions.…”

Product Traceability and Supply Chain Sustainability of Black Soybeans as Raw Materials for Soy Sauce in Maintaining Quality and Safety

“…The traceability system is applied as a tool to ensure food safety and quality and gain consumer confidence [28,29]. Traceability information can effectively help consumers master purchase details and contribute to the efficient development of various industries, which can store product names, raw materials, production and processing processes, transportation, and other information in digital form [30]. This digital technology information is necessary for tracking all kinds of work and data security in various organizations and institutions [31].…”

“…There has been proactive development of various innovation institutions and regulations for supply chain sustainability, such as codes of conduct, product information, and eco-branding [14]. Sustainability in the infrastructure dimension has increased, such as for roads, product storage, product conditions, irrigation development, and port improvements [30].…”

Intelligent media computing technology and application for media convergence

“…The first article introduces different types of traceability models, considers the efficiency and storage security between different models, and then discusses the supervision of traceability information [1]. This article proposes a DAG blockchain consensus mechanism based on random verifiable function and witness mechanism.…”