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A comprehensive survey on 6G-security: physical connection and service layers

Discover Internet of Things 2025年第1期5卷 1-30页

作者： Saeed, Mamoon M. Saeed, Rashid A. Hasan, Mohammad Kamrul Ali, Elmustafa Sayed Mazha, Tehseen Shahzad, Tariq Khan, Sunawar Hamam, Habib Sana00967 Yemen Department of Computer Engineering College of Computers and Information Technology Taif University P.O. Box 11099 Taif21944 Saudi Arabia Department of Electronics Engineering College of Electronics Engineering Sudan University of Science and Technology Omdurman Sudan Bangi43600 Malaysia Department of Electrical and Electronic Engineering Faculty of Engineering Red Sea University Port Sudan33312 Sudan School of Computer Science National College of Business Administration and Economics Lahore54000 Pakistan Faculty of Engineering Uni de Moncton MonctonNBE1A3E9 Canada Department of Computer Engineering COMSATS University Islamabad Sahiwal Campus Sahiwal57000 Pakistan Department of Computer Science and Software Engineering International Islamic University Islamabad44000 Pakistan School of Electrical Engineering University of Johannesburg Johannesburg2006 South Africa BP 1989 Av. Grandes Ecoles Libreville Gabon Bridges for Academic Excellence-Spectrum Tunis Tunisia Department of Computer Science School Education Department Government of Punjab Layyah31200 Pakistan Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India

After adopting 5G technology, businesses and academia have started working on sixth-generation wireless networking (6G) technologies. Mobile communications options are expected to expand in areas where previous generations could not do so. 6G networks are anticipated to be constructed using various diverse technologies. These encompass diverse cutting-edge advancements, such as distributed ledger systems like blockchain, visible light communications (VLC), post-quantum cryptography, edge computing, molecular communication, THz, and other advances. These advances necessitate a reassessment of previous security strategies from a security perspective. In the future, networks must adhere to stricter criteria for authentication, encryption, access control, connectivity, and detection of harmful activities. Ensuring privacy and dependability necessitates the implementation of supplementary security protocols. The essay explores the primary concerns and challenges related to the security of the 6G network. This paper describes the improvements in security in communications from 1G through 6G. This paper divides security in the sixth generation into three layers: physical, connection, and service. Each layer-by-layer discusses the standard technologies and security issues for each technology proposed in each sixth-generation security layer. All proposed solutions for each of the three layers are discussed in Sixth Generation Security. It also reviews all proposed solutions for each layer, indicating the proposed solution and its limitations. © The Author(s) 2025.

关键词： 5G mobile communication systems

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Augmenting ATM Security: Real-Time Facial Emotion Recognition as an Additional Safeguard

Augmenting ATM Security: Real-Time Facial Emotion Recognitio...

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2024 International Conference on science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Adebiyi, Marion O. Oluwadamilola, Omirin Olaniyan, Deborah Olaniyan, Julius Emmanuel, Asani O Oluwasegunfunmi, Ige-Bello Adebiyi, Abayomi A. Landmark University Department of Computer Science Kwara-State Omu-Aran Nigeria Durban University of Technology Faculty of Engineering and the Built Environment Department of Electrical Power Engineering South Africa

ISBN: (纸本)9798350358155

Motion detection and facial recognition fields have undergone thorough research to enhance surveillance services in locations that need accurate motion detection and human identification. With the continuous improvement of criminal strategies, it is essential for surveillance technologies likewise to progress accordingly. In the present literature, MD&FR stands out as a dependable surveillance technology. Although there is potential to integrate MD&FR technologies into existing surveillance systems (SS), the present systems have only implemented MD-based and FR-based SS *** research investigates integrating Facial Expression Recognition (FER) technology to bolster the security of Automated Teller Machines (ATMs). FER technology holds potential as an additional security layer, capable of detecting and responding to emotional cues in realtime. Through a thorough exploration, three different models - LSTM, CNN, and CapsNet - were evaluated for their effectiveness in classifying facial emotions. Results indicate that the CNN model outperformed LSTM and CapsNet, exhibiting higher accuracy, precision, recall, and F1 score. These findings underscore the CNN model's potential to enhance ATM security by accurately recognizing facial expressions. However, further research is needed to address challenges and refine FER models for optimal performance in real-world scenarios. This study contributes valuable insights into leveraging FER technology to bolster ATM security, ultimately enhancing user safety and mitigating fraudulent activities. © 2024 IEEE.

关键词： Automatic teller machines

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Construction of the Molecular Structure Model of the Zhaotong Lignite Using Simulation and Experiment Data

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Chinese Journal of Structural Chemistry 2022年第3期41卷 137-147,I0011页

作者： ZHANG Dian-Kai LI Yan-Hong CHANG Li-Ping ZI Chang-Yu ZHANG Yuan-Qin TIAN Guo-Cai ZHAO Wen-Bo Faculty of Chemical Engineering Kunming University of Science and TechnologyKunming 650500China Key Laboratory of Coal Science and Technology Taiyuan University of TechnologyMinistry of Education and Shanxi Province 030024China State Key Laboratory of Complex Nonferrous Metal Resources Clean Utilization Kunming University of Science and TechnologyKunming 650093China

Aiming to better understand the physiochemical properties of lignite, we select Zhaotong lignite as object and adopt simulation and experiment data to construct its molecular structure. Firstly, the important parameters including carbon skeleton, valence state and functional group of the sample are obtained by ultimate analysis, 13 C NMR, XPS and Py-GC/MS. Results indicate that the ratio of aromatic carbon and aromatic bridge carbon to surrounding carbon of the sample are 40.32% and 0.14, respectively. Such results imply that the aromatic structure of the sample is dominated by benzene and naphthalene. Moreover, the ratio of aliphatic carbon is 51.55%, and the aliphatic structure is mainly comprised by methyl, methylene, quaternary carbon and oxygen-aliphatic carbon. Oxygen atoms principally exist in ether, carbonyl and carboxyl groups, of which ether accounts for 70.2%. Additionally, the contents of pyridine, pyrrole and quaternary nitrogen are 25.2%, 46.3% and 13.0%, respectively. Based on the aforementioned results, the molecular structure model of Zhaotong lignite is constructed by the method of computer-aided molecular design. Subsequently, the molecular formula of Zhaotong lignite is calculated as C;H;O;N;. Finally, in order to verify the reasonability of the constructed model, the 13 C NMR of the molecular structure model is simulated by employing the basis set of GIAO/6-31G at the Gaussian 09 computing platform. These simulated results agree well with the experimental ones, which suggests that the molecular structure model of Zhaotong lignite is accurate and reasonable.

关键词： fluoroquinolone amide derivatives Hep-3B cell Capan-1cell HL60 cell anti-proliferative activity comparative molecular field analysis

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A review of intelligent ore sorting technology and equipment development

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International Journal of Minerals,Metallurgy and Materials 2022年第9期29卷 1647-1655页

作者： Xianping Luo Kunzhong He Yan Zhang Pengyu He Yongbing Zhang Jiangxi Key Laboratory of High-efficiency Development and Application of Tungsten Resources Jiangxi University of Science and TechnologyGanzhou 341000China Jiangxi Key Laboratory of Mining&Metallurgy Environmental Pollution Control Jiangxi University of Science and TechnologyGanzhou 341000China Faculty of Resource and Environmental Engineering Jiangxi University of Science and TechnologyGanzhou 341000China

Under the background of increasingly scarce ore worldwide and increasingly fierce market competition,developing the mining industry could be strongly *** ore sorting equipment not only improves ore use and enhances the economic benefits of enterprises but also increases the ore grade and lessens the grinding cost and tailings ***,long-term research on intelligent ore sorting equipment found that the factors affecting sorting efficiency mainly include ore information identification technology,equipment sorting actuator,and information processing *** high precision,strong anti-interference capability,and high speed of these factors guarantee the separation efficiency of intelligent ore sorting *** ore sorter,X-ray ore transmission sorter,dual-energy X-ray transmission ore sorter,X-ray fluorescence ore sorter,and near-infrared ore sorter have been successfully developed in accordance with the different characteristics of minerals while ensuring the accuracy of equipment sorting and improving the equipment sorting *** the continuous improvement of mine automation level,the application of online element rapid analysis technology with high speed,high precision,and strong anti-interference capability in intelligent ore sorting equipment will become an inevitable trend of equipment development in the ***-induced breakdown spectroscopy,transientγneutron activation analysis,online Fourier transform infrared spectroscopy,and nuclear magnetic resonance techniques will promote the development of ore sorting *** addition,the improvement and joint application of additional high-speed and high-precision operation algorithms(such as peak area,principal component analysis,artificial neural network,partial least squares,and Monte Carlo library least squares methods)are an essential part of the development of intelligent ore sorting equipment in the future.

关键词： intelligent ore sorting technology sorting equipment separation efficiency online element rapid analysis technology

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Constellation-Preserving Symbol Encryption with Minimal Impact on Fiber Non-linear Channels 8

Constellation-Preserving Symbol Encryption with Minimal Impa...

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8th Optoelectronics Global Conference, OGC 2023

作者： Shimada, Keiji Matsumoto, Ryosuke Kodama, Takahiro Kagawa University Faculty of Engineering and Design Takamatsu Japan National Institute of Advanced Industrial Science and Technology Tsukuba Japan

We showed that uniform-QAM constellation-preserving symbol encryption is below the FEC limit Q2 in any fiber transmission distance without decryption. 32Gbaud 7ch-WDM-DP-16QAM transmission experiments under the condit... 详细信息

ISBN: (纸本)9798350325324

关键词： Quadrature amplitude modulation

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Ethanol production from cassava peels using Saccharomyces cerevisiae via ethanologenic fermentation process

Arab Gulf Journal of Scientific Research

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Arab Gulf Journal of Scientific Research 2024年第4期42卷 1664-1684页

作者： Sokan-Adeaga, Adewale Allen R.E.E. Ana, Godson Olorunnisola, Abel Olajide Sokan-Adeaga, Micheal Ayodeji Roy, Hridoy Reza, Md Sumon Islam, Md. Shahinoor Department of Environmental Health Sciences Faculty of Public Health College of Medicine University of Ibadan Ibadan Nigeria Department of Environmental Health Science Faculty of Public Health Lead City University Ibadan Nigeria Department of Environmental Health Science Faculty of Basic Medical Sciences Ajayi Crowther University Oyo Nigeria Department of Wood Products Engineering Faculty of Technology University of Ibadan Ibadan Nigeria Department of Microbiology Environmental Microbiology Unit Faculty of Science Obafemi Awolowo University Ile-Ife Nigeria Department of Microbiology General Microbiology Unit Faculty of Science University of Ibadan Ibadan Nigeria Department of Chemical Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh Faculty of Natural Sciences Research Institute of New Chemical Technologies L.N. Gumilyov Eurasian National University Astana Kazakhstan Department of Civil Engineering East West University Dhaka Bangladesh

Purpose: This study aims to assess the effect of water variation on bioethanol production from cassava peels (CP) using Saccharomyces cerevisiae yeast as the ethanologenic agent. Design/methodology/approach: The milled CP was divided into three treatment groups in a small-scale flask experiment where each 20 g CP was subjected to two-stage hydrolysis. Different amount of water was added to the fermentation process of CP. The fermented samples were collected every 24 h for various analyses. Findings: The results of the fermentation revealed that the highest ethanol productivity and fermentation efficiency was obtained at 17.38 ± 0.30% and 0.139 ± 0.003 gL⁻¹ h⁻¹. The study affirmed that ethanol production was increased for the addition of water up to 35% for the CP hydrolysate process. Practical implications: The finding of this study demonstrates that S. cerevisiae is the key player in industrial ethanol production among a variety of yeasts that produce ethanol through sugar fermentation. In order to design truly sustainable processes, it should be expanded to include a thorough analysis and the gradual scaling-up of this process to an industrial level. Originality/value: This paper is an original research work dealing with bioethanol production from CP using S. cerevisiae microbe. Highlights: Hydrolysis of cassava peels using 13.1 M H₂SO₄ at 100 ^oC for 110 min gave high Glucose productivity Highest ethanol production was obtained at 72 h of fermentation using Saccharomyces cerevisiae Optimal bioethanol concentration and yield were obtained at a hydration level of 35% agitation Highest ethanol productivity and fermentation efficiency were 17.3%, 0.139 g.L⁻¹.h⁻¹ © 2023, Adewale Allen Sokan-Adeaga, Godson R.E.E. Ana, Abel Olajide Olorunnisola, Micheal Ayodeji Sokan-Adeaga, Hridoy Roy, Md Sumon Reza and Md. Shahinoor Islam.

关键词： Bioenergy Bioethanol Fermentation Glucose productivity Lignocellulosic biomass

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Enhancing Predictive Accuracy with Machine Learning and IoT Integration in Energy Management 2

Enhancing Predictive Accuracy with Machine Learning and IoT ...

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2nd International Conference Computational and Characterization Techniques in engineering and sciences, IC3TES 2024

作者： Balaji, S. Bharathi, S. Prasanna Balaji, T.S. Hariharan, R. Subin, P. Glaret Faculty of Engineering and Technology Srm Institute of Science and Technology Department of Electronics and Communication Engineering Tamilnadu Vadapalani Campus Chennai India Vellore Institute of Technology School of Electronics Engineering Tamil Nadu Chennai India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Electrical and Electronics Engineering Tamilnadu Chennai India Srm Institute of Science and Technology Department of Ece Vadapalani Campus Tamilnadu Chennai India

ISBN: (纸本)9798350364699

The combination of IoT and ML has the capacity to radically change the energy management as it would increase predictability measurements many folds. This study seeks to analyse the relationship between the use of IoT and ML in enhancing the prediction of energy consumption and the enhancement of the management strategies. Therefore, using the data obtained from the IoT sensors in real-time and applying different ML algorithms, the goal of the study is to design sound machine learning models for EMS. The method used entails data acquisition from smart meters and environmental sensors and the initial data cleaning process and applies regression, classification, and clustering algorithms. Findings show that energy consumption can be predicted more accurately through the machine learning models, especially the Polynomial Regression. Thus, the role of data quality and feature selection in the improvement of a model is shown in the study. The results show that the application of IoT together with the application of ML technologies make great sense and have significant advantages mainly in improving the productivity and efficiency, cutting costs and achieving better control of energy consumption. Thus, this work will be instrumental in the continual enhancement of energy management and contribute to the broader literature through the findings on suitable modeling approaches and the influence of IoT data on superior prognosis. In the subsequent studies, more efforts will be made on enhancing the aforementioned models and expanding the application fields on energy management practices. © 2024 IEEE.

关键词： Data accuracy

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Compressed VGGNet for Automatic COVID-19 Disease Detection from CT Scan Images 8th

Compressed VGGNet for Automatic COVID-19 Disease Detection f...

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8th IFIP TC 12 International Conference on Computer, Communication and Signal Processing, ICCCSP 2024

作者： Vinothini, R. Niranjana, G. Dhamanti, Inge Lailiyah, Syifa’ul Yakub, Fitri Department of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur 603203 India Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur 603203 India Department of Health Policy and Administration Faculty of Public Health Universitas Airlangga Surabaya Indonesia Faculty of Health Medicine and Life Sciences Universitas Airlangga East Java Indonesia Electronic System Engineering Department Malaysia-Japan International Institute of Technology Kuala Lumpur Malaysia

ISBN: (纸本)9783031736162

Millions of people across the globe were affected by this rapidly spreading disease by the year 2020. Contamination of the respiratory system results from contracting COVID-19. Nonetheless, establishing a conclusive diagnosis of COVID-19 may prove difficult due to the subtle differences it shares with conventional pneumonia and the complexities involved in identifying areas of infection. A growing number of approaches based on deep learning (DL) are being proposed for the automated detection of COVID-19 from CT scan images. By employing the data pretreatment methodology, unprocessed image data becomes prepared for further analysis. The proposed framework utilised transfer learning to construct VGGNet, which is capable of discerning the Covid-19 disease. The model was subsequently assessed in comparison to the most sophisticated models, VGG16 and VGG19, using the SARS-COV2 CT scan dataset. This dataset contains 1230 CT scans of non-infected images and 1252 CT scans of Covid-19-infected images. The model has achieved 99% accuracy, 98% precision, 97% recall, and 98% F1-score, among other performance metrics. © IFIP International Federation for Information Processing 2025.

关键词： COVID-19

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Deep E-Cue:Systematic Deep Network for Multimodal Emotional Cues Recognition in Email Communication 4

Deep E-Cue:Systematic Deep Network for Multimodal Emotional ...

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4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Revathi, K. Pabitha, C. Theresa, W. Gracy Chawengsaksopark, Pornpimol Sathiyanarayanan, Mithileysh Srm Valliammai Engineering College Department of Information Technology Chennai India Panimalar Engineering College Department of Artificial Intelligence and Data Science Chennai India Shinawatra University Faculty of Engineering Pathum Thani Thailand

ISBN: (纸本)9798331529635

Organizations require virtual communication because efficient communication is essential to successful company operations. Among the features of virtual communication typically email communication, which is textual and asynchronous, meaning that the sender and the recipient do not encounter it simultaneously. Email can be troublesome because it eliminates in-person interactions, which can distort our capacity to develop interpersonal cues that are essential for communicating, exchanging information, and establishing trust. The proposed research is aimed to investigate the adaptability of emotional cues in email communication. A deep learning model is built to extract the emotional cues in email considering multiple parameters like text, audio, video and context of communication. The proposed models achieve accuracy of 96.86%, precision of 97.44%, and sensitivity of 97.69% which is highest score when compared to other existing models. © 2024 IEEE.

关键词： Contrastive Learning

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CdS decorated resorcinol-formaldehyde spheres as an inorganic/organic S-scheme photocatalyst for enhanced H_(2)O_(2)production

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Journal of Materials science & technology 2023年第31期162卷 90-98页

作者： Bicheng Zhu Jingjing Liu Jian Sun Fei Xie Haiyan Tan Bei Cheng Jianjun Zhang Laboratory of Solar Fuel Faculty of Materials Science and ChemistryChina University of GeosciencesWuhan 430078China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070China School of Chemistry and Environmental Engineering Hubei University for NationalitiesEnshi 445000China

Photocatalytic H_(2)O_(2)production provides a clean and sustainable strategy for artificial ***,an inorganic/organic composite photocatalyst was fabricated by in-situ growth of CdS nanoparticles on the surface of resorcinol-formaldehyde(RF)resin *** spheres played multiple roles:(i)acting as a substrate for the growth of CdS and constructing a core-shell structure with seamless con-tact;(ⅱ)improving visible light absorption of CdS;(ⅲ)forming an S-scheme heterojunction with CdS and promoting the charge separation and ***,under visible light illumination,CdS/RF composite presented remarkably enhanced H_(2)O_(2)production *** H_(2)O_(2)yield in 60 min was 801μmol L^(-1),which was 5.2 and 1.5 times higher than that of RF spheres and CdS hollow spheres,*** charge migration between CdS and RF followed the S-scheme photocatalytic mechanism,which was verified by work function measurement,ex-situ and in-situ irradiated X-ray photoelectron *** work brings a novel insight into designing RF-based inorganic/organic S-scheme heterojunction pho-tocatalysts for efficient H_(2)O_(2)production.

关键词： Photocatalysis Step-scheme heterojunction Resorcinol-formaldehyde Hydrogen peroxide in-situ irradiated XPS

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