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Blockchain and PUF-based secure key establishment protocol for cross-domain digital twins in industrial Internet of Things architecture

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Journal of Advanced Research 2024年 62卷 155-163页

作者： Mahmood, Khalid Shamshad, Salman Saleem, Muhammad Asad Kharel, Rupak Das, Ashok Kumar Shetty, Sachin Rodrigues, Joel J.P.C. School of Psychology and Computer Science University of Central Lancashire Preston United Kingdom Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Yunlin 64002 Taiwan Department of Software Engineering The University of Lahore Lahore 54590 Pakistan Department of Computer Science University of Sahiwal Punjab Sahiwal 57000 Pakistan Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad 500 032 India Department of Modeling Simulation and Visualization Engineering Virginia Modeling Analysis and Simulation Center and Center for Cybersecurity Education and Research Old Dominion University Suffolk 23435 VA United States COPELABS Lusófona University Campo Grande 376 Lisbon 1749-024 Portugal

Introduction: The Industrial Internet of Things (IIoT) is a technology that connects devices to collect data and conduct in-depth analysis to provide value-added services to industries. The integration of the physical and digital domains is crucial for unlocking the full potential of the IIoT, and digital twins can facilitate this integration by providing a virtual representation of real-world entities. Objectives: By combining digital twins with the IIoT, industries can simulate, predict, and control physical behaviors, enabling them to achieve broader value and support industry 4.0 and 5.0. Constituents of cooperative IIoT domains tend to interact and collaborate during their complicated operations. Methods: To secure such interaction and collaborations, we introduce a blockchain-based cross-domain authentication protocol for IIoT. The blockchain maintains only each domain's dynamic accumulator, which accumulates crucial materials derived from devices, decreasing the overhead. In addition, we use the on-chain accumulator to effectively validate the unlinkable identities of cross-domain IIoT devices. Results: The implementation of the concept reveals the fact that our protocol is efficient and reliable. This efficiency and reliability of our protocol is also substantiated through comparison with state-of-the-art literature. In contrast to related protocols, our protocol exhibits a minimum 22.67% increase in computation cost efficiency and a 16.35% rise in communication cost efficiency. Conclusion: The developed protocol guarantees data transfer security across the domain and thwarts IoT devices from potential physical attacks. Additionally, in order to protect privacy, anonymity and unlinkability are also guaranteed. © 2024

关键词： Digital twins Industrial Internet of Things (IIoT) Key agreement Mutual authentication Physically Unclonable Functions (PUFs)

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A quantified hypervulnerability approach for assessing resilience in supply chain networks

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International Journal of simulation and Process Modelling 2024年第3期21卷 166-178页

作者： Smith, Katherine Diaz, Rafael Shen, Yuzhong Virginia Modeling Analysis and Simulation Center Old Dominion University 1030 University Blvd. SuffolkVA23435 United States School of Cybersecurity Old Dominion University 1113A Monarch Hall NorfolkVA23529 United States Department of Electrical and Computer Engineering Old Dominion University 231 Kaufman Hall NorfolkVA23529 United States

The COVID-19 pandemic highlighted the vulnerability of supply chain networks to sources of concurrent disruption. This research investigates and broadens a quantified, generalised definition of vulnerability, which enables a group of entities to be identified as highly, or hyper, vulnerable. This concept of hypervulnerability thresholds is demonstrated on a conceptual example. The example explains and shows how the definition of hypervulnerability thresholds can be applied. A maritime supply chain case study with various risks and disruptions is presented and analysed to demonstrate the practical utility of the approach and provide valuable information to guide decision making in other applications. Finally, the article concludes with answers to research questions and directions for future work. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： disruption resilience risk supply chain systems theory vulnerability

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A Simultaneous Wireless Information and Power Transfer-based Multi-hop Clustering Routing Protocol for RF Energy Harvesting-Cognitive Radio Sensor Networks

Journal of Network Intelligence

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Journal of Network Intelligence 2023年第3期8卷 991-1007页

作者： Wang, Ji-Hong Su, Xi-Tong Ge, Yi-Yang Chen, Yeh-Cheng Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University China School of Electrical Engineering Northeast Electric Power University 169 Changchun Road Jilin132012 China Department of Computer Science University of California DavisCA001313 United States

Radio frequency energy harvesting (RF EH) and clustering are promising solutions to solve the energy constraint problem faced by cognitive radio sensor networks (CRSNs). However, study on clustering routing protocol design for RF EH-CRSNs is still in the initial stage, and there lacks of solutions for inter-cluster routing problem, which restricts the network scalability. In addition, unbalanced harvested energy and energy consumption may result in premature death of nodes in key position, which will significantly reduce the network performance. In this paper, a simultaneous wireless information and power transfer (SWIPT)-based multi-hop clustering routing protocol (SMCRP) is proposed for RF EH-CRSNs to well balance the residual energy distribution among nodes and postpone node death. Apart from the RF energy harvested from dedicated or ambi-ent energy sources, the energy obtained through intra-cluster and inter-cluster SWIPT is also considered to facilitate high-quality cluster heads selection, cluster formation and inter-cluster route establishment. Power splitting ratio is derived based on the residual energy of CRSNs nodes and their energy consumption to enable effective implementation of SWIPT in CRSNs. simulation results show that SMCRP is effective in balancing the residual energy distribution among nodes and improving node sustainability. To be specific, compared with current clustering protocols, the network lifetime is extended by 64.07% while intra-cluster energy balance degree and network energy balance degree are improved by 15.1% and 7.82%, respectively. © 2023 ISSN 2414-8105 (Online).

关键词： Cognitive radio

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Texture Analysis of Breast US Images Using Morphological Transforms, Hausdorff Dimension and Bagging Ensemble Method 32

Texture Analysis of Breast US Images Using Morphological Tra...

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32nd Mediterranean Conference on Control and Automation, MED 2024

作者： Tabacaru, Gigi Moldovanu, Simona Barbu, Marian 'Dunarea de Jos' University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Automatic Control and Electrical Engineering Romania 'Dunarea de Jos' University of Galati Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Romania Dunarea de Jos University of Galati The Modelling & Simulation Laboratory Galati800008 Romania

ISBN: (纸本)9798350395440

In this work, an attempt is made for the first time to use the measurement pattern generated by morphological transformation quantified by Hausdorff fractal dimension (HFD) and classified with ensemble learning based on bagging. The proposed work uses three morphological transformations for image preprocessing: hit-and-miss transform (HMT), white (WHT), and black top-hat (BHT). The pattern texture of US breast images is described by extracting the HFD from the regions of interest (ROI) after the ultrasound (US) images have been preprocessed. The main objective of this study was achieved by comparatively analyzing the classification performance of features using the Random Forest (RF), Extra Trees (ET) classifier, and bagging ensemble method based on XGBoot classifier. In presented study, the XGBoost classifier and BHT image processing method give an accuracy of 89.8% in a binary classification, benign versus malignant breast cancer. © 2024 IEEE.

关键词： Fractal dimension

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Neural Network Based Active Fault-tolerant Control of Spacecraft via Prescribed Performance

Neural Network Based Active Fault-tolerant Control of Spacec...

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Asian Control Conference

作者： Ze Yang Baoqing Yang Ruihang Ji Jie Ma Control and Simulation Center Harbin Institute of Technology Harbin China Department of Electrical and Computer Engineering National University of Singapore Singapore

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

This paper mainly studies the fault diagnosis and fault tolerance control of spacecraft attitude control system (ACS). Firstly, a novel model-free fault diagnosis network (FDN) is constructed based on Bi-LSTM neural networks. It uses only historical data to approximate the ACS mechanism, generate residuals, and combine adaptive thresholds to detect actuator and sensor faults. Secondly, to solve the problem of missing angular rate measurement caused by sensor faults, a fault-tolerant controller based on adaptive tracking differentiator (ATD) to generate virtual angular rate and have prescribed performance is designed to improve the robustness to faults and avoid performance degradation. Finally, simulation results are given to evaluate the effectiveness of the proposed scheme.

关键词： Fault diagnosis Space vehicles Fault tolerance Analytical models Actuators Attitude control simulation

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LESSONS LEARNED FROM THE COVID-19 PANDEMIC: AN ANALYSIS OF REGIONAL PHILIPPINE DATA AND COVID-19 OUTCOMES

LESSONS LEARNED FROM THE COVID-19 PANDEMIC: AN ANALYSIS OF R...

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2023 Philippine Geomatics Symposium, PhilGEOS 2023

作者： Gaano, J.B. Rule, C. Celeste, J. Bongolan, V.P. Rivera, R.L. Caoili, S.E. System Modeling and Simulation Lab Department of Computer Science College of Engineering University of the Philippines – Diliman Quezon City Philippines Center for Informatics University of San Agustin Iloilo Philippines College of Social Work and Community Development UP Diliman Philippines UP College of Medicine Philippines

Variations in indicators which may affect COVID-19 outcomes exist among regions in the Philippines. These variations suggest that the impacts of the pandemic differ not only between countries but also within regions and local areas in a country. This study aims to investigate COVID-19 outcomes (case fatality rate or CFR, incidence rate and hospitalization rate) over time and their correlation with regional healthcare and population factors during different phases of the pandemic across the 17 regions of the Philippines. These outcomes were chosen because they are readily available from government data sources, and are simple to work with. We mark five 100-day time periods of the COVID-19 pandemic in the country. The COVID-19 dataset was based on data maintained by the department of Health (DOH). Spearman’s rank correlation coefficient analysis was used to examine the link between COVID-19 outcomes region-specific indicators referring to population and access to health care resources. Despite their higher vaccination coverage, regions with greater access to health care resources may still be susceptible to future COVID-19 outbreaks due to their urban and densely populated nature. However, vaccines remain effective in reducing COVID-19 hospitalizations in these regions. Therefore, it is crucial to focus on increasing vaccination coverage in rural, underserved regions and implement targeted outbreak control measures in densely populated areas. © Author(s) 2024.

关键词： COVID-19

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Federated Learning With Client Clustering Selection and Quality-Aware Model Aggregation(2024)

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IEEE Internet of Things Journal 2025年

作者： Peng, Y. Wang, C. Shi, H. Ma, R. Guan, H. Yang, Hanbo Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai China Beijing Simulation Center National Key Laboratory of Modeling and Simulation for Complex Systems Beijing China

The Industrial Internet of Things (IIoT) is revolutionizing industries through device interconnectivity, enabling real-time data collection and transmission for enhanced monitoring, control, and automation. This has led to improvements in predictive maintenance, production optimization, and supply chain management. The integration of machine learning (ML) and deep learning (DL) within IIoT has been accelerated by increased data availability, computational advancements, and algorithmic innovations, with applications ranging from image processing to autonomous vehicles. Foundation models, such as ChatGPT, are becoming prevalent in IIoT for their capabilities in natural language processing and computer vision. However, the growth of IIoT and foundation models presents challenges, including data volume, real-time processing requirements, computational costs, and security vulnerabilities. Federated learning (FL) addresses these issues by allowing distributed model training without raw data transfer, enhancing privacy and security. FL is particularly beneficial for IIoT’s decentralized architecture and real-time decision-making needs. Despite the advantages, FL faces challenges such as data heterogeneity and communication overhead. To overcome these, we propose a federated learning framework, Fed-CCSQMA, which includes client selection and model aggregation modules to mitigate data heterogeneity’s impact. The client selection module uses Principal Component Analysis (PCA) and clustering to select clients with diverse yet representative data, while the model aggregation module assigns weights based on model accuracy to ensure faster global model convergence. We test our proposed framework on FMNIST and CIFAR-10 datasets, with accuracy surpassing baseline methods and faster convergence, demonstrating an improvement in overall generalizability and learning efficiency. © 2014 IEEE.

关键词： Decision making

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Multi-Timescale Trading Strategy for Renewable Power to Ammonia Virtual Power Plant in the Electricity, Hydrogen, and Ammonia Markets

IEEE Transactions on Energy Markets, Policy and Regulation

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IEEE Transactions on Energy Markets, Policy and Regulation 2023年第4期1卷 322-335页

作者： Wu, Sirui Lin, Jin Li, Jiarong Liu, Feng Song, Yonghua Xu, Yanhui Cheng, Xiang Yu, Zhipeng Tsinghua University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Beijing100087 China Tsinghua University Sichuan Energy Internet Research Institute Chengdu610213 China University of Macau Department of Electrical and Computer Engineering Macau999078 China Tsinghua University Department of Electrical Engineering Beijing100087 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China

Renewablepower to ammonia (RePtA) is a prominent zero-carbon pathway for decarbonization. Due to the imbalance between renewables and production energy demand, the RePtA system relies on electricity exchange with the power grid. Participating in the electricity market as a virtual power plant (VPP) may help to reduce energy costs. However, the power profile of local photovoltaics and wind turbines is similar to those in the market, resulting in rising energy costs under the conventional strategy. Hence, we develop a multi-timescale trading strategy for the RePtA VPP in the electricity, hydrogen, and ammonia markets. By utilizing the hydrogen and ammonia buffer systems, the RePtA VPP can optimally coordinate production planning. Moreover, we find it possible to describe the trading of electricity, ammonia, and hydrogen in a unified timeframe. The two-stage robust optimization model of the electricity market is extended to multiple markets and solved by the column and constraint generation (CC&G) algorithm. The case is derived from an actual project in the Inner Mongolia Autonomous Region. Sensitivity analysis demonstrates the economic advantages of the RePtA VPP joining multiple markets over the conventional strategy and reveals the necessity of the hydrogen and ammonia buffer and reactor flexibility. © 2023 IEEE.

关键词： Ammonia

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Preventing Pressure Oscillations Does Not Fix Local Linear Stability Issues of Entropy-Based Split-Form High-Order Schemes

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Communications on Applied Mathematics and Computation 2022年第3期4卷 880-903页

作者： Hendrik Ranocha Gregor J.Gassner Applied Mathematics Münster University of Münster48149 MünsterGermany Computer Electrical and Mathematical Science and Engineering(CEMSE)Division King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia Department of Mathematics and Computer Science Center for Data and Simulation ScienceUniversity of CologneCologneGermany

Recently,it was discovered that the entropy-conserving/dissipative high-order split-form discontinuous Galerkin discretizations have robustness issues when trying to solve the sim-ple density wave propagation example for the compressible Euler *** issue is related to missing local linear stability,i.e.,the stability of the discretization towards per-turbations added to a stable base *** is strongly related to an anti-diffusion mech-anism,that is inherent in entropy-conserving two-point fluxes,which are a key ingredi-ent for the high-order discontinuous Galerkin *** this paper,we investigate if pressure equilibrium preservation is a remedy to these recently found local linear stability issues of entropy-conservative/dissipative high-order split-form discontinuous Galerkin methods for the compressible Euler *** equilibrium preservation describes the property of a discretization to keep pressure and velocity constant for pure density wave *** present the full theoretical derivation,analysis,and show corresponding numerical results to underline our *** addition,we characterize numerical fluxes for the Euler equations that are entropy-conservative,kinetic-energy-preserving,pressure-equilibrium-preserving,and have a density flux that does not depend on the *** source code to reproduce all numerical experiments presented in this article is available online(https://***/10.5281/zenodo.4054366).

关键词： Entropy conservation Kinetic energy preservation Pressure equilibrium preservation Compressible Euler equations Local linear stability Summation-by-parts

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Performance Creativity Enhancement Method Based on Emotional Analysis and Concentration

Journal of Network Intelligence

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Journal of Network Intelligence 2023年第3期8卷 1019-1048页

作者： Liu, Chang Zhang, Longfei Huang, Tianyu Wu, Yufeng Zhang, Fuquan Lin, Qi Department of Computer Science and Technology Beijing Institute of Technology 100081 China Beijing Key Laboratory of Digital Performance and Simulation Technology 100081 China College of Computer and Control Engineering Minjiang University Fuzhou350108 China Digital Media Art Key Laboratory of Sichuan Province Sichuan Conservatory of Music Chengdu610021 China Informatics King’s College London LondonWC2R 2LS United Kingdom

Intelligent performance creativity is a new research direction of the intersection of technology and art. At present, the cutting-edge technologies such as computer simulation, emotional computing and machine learning have been applied to the evaluation and enhancement of intelligent performance creativity. The application of these technologies has greatly increased the diversity of performance forms and the complexity of performance content. For the traditional stage performance, due to the lack of timely feedback from the audience, it is difficult for the director to enhance the creativity effec-tively. In order to solve this problem, this paper proposes concentration level enhancement method (CLEM). The CLEM extracts and analyzes the physiological and emotional characteristics of the audience by collecting the multimodal physiological signal data of the audience. Through the analysis of the features, the concentration information of the audience is obtained and the concentration level (CL) is defined. Based on the physiological and emotional induction mechanism, a performance creativity enhancement strategy is proposed, which enhances the performance creativity in two aspects: " Visual-based" and " Content-based". Through the concentration level enhancement method, compare the audience’s performance attention changes before and after the performance creativity enhancement, select the effective strategies to enhance the performance creativity, and provide the director with quantifiable performance creativity enhancement feedback results. The experimental results show that the CLEM proposed in this paper can effectively induce significant changes in the audience’s emotion, and the selected creative enhancement strategy can significantly improve the audience’s concentration and achieve the purpose of enhancing the creativity of the performance. © 2023, Journal of Network Intelligence.

关键词： Physiology

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