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A Hybrid and Lightweight Device-to-server Authentication Technique for the Internet of Things

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Computers, Materials & Continua 2024年第3期78卷 3805-3823页

作者： shaha al-Otaibi Rahim Khan Hashim ali Aftab Ahmed Khan Amir saeed Jehad ali Department of Information systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer science Abdul Wali Khan University MardanMardan23200Pakistan Department of Computer science and IT UET PeshawarJalozai Campus PeshawarPeshawar24240Pakistan Department of AI Convergence Network Ajou UniversitySuwon16499South Korea

The Internet of Things(IoT)is a smart networking infrastructure of physical devices,i.e.,things,that are embedded with sensors,actuators,software,and other technologies,to connect and share data with the respective server *** IoTs are cornerstones in different application domains,the device’s authenticity,i.e.,of server(s)and ordinary devices,is the most crucial issue and must be resolved on a priority ***,various field-proven methodologies were presented to streamline the verification process of the communicating devices;however,location-aware authentication has not been reported as per our knowledge,which is a crucial metric,especially in scenarios where devices are *** paper presents a lightweight and location-aware device-to-server authentication technique where the device’s membership with the nearest server is subjected to its location information along with other ***,Media Access Control(MAC)address and Advance Encryption scheme(AEs)along with a secret shared key,i.e.,λ_(i) of 128 bits,have been utilized by Trusted Authority(TA)to generate MaskIDs,which are used instead of the original ID,for every device,i.e.,server and member,and are shared in the offline ***,TA shares a list of authentic devices,i.e.,server s_(j) and members C_(i),with every device in the IoT for the onward verification process,which is required to be executed before the initialization of the actual communication ***,every device should be located such that it lies within the coverage area of a server,and this location information is used in the authentication process.A thorough analytical analysis was carried out to check the susceptibility of the proposed and existing authentication approaches against well-known intruder attacks,i.e.,man-in-the-middle,masquerading,device,and server impersonations,etc.,especially in the IoT ***,proposed authentication and existing state-of-the-art approaches have been s

关键词： Internet of things authenticity security location communication

WebFLex:A Framework for Web Browsers-Based Peer-to-Peer Federated Learning systems Using WebRTC

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Computers, Materials & Continua 2024年第3期78卷 4177-4204页

作者： Mai alzamel Hamza ali Rizvi Najwa altwaijry Isra al-Turaiki Department of Computer science College of Computer and Information SciencesKing Saud UniversityRiyadhKingdom of Saudi Arabia Department of Computer science and Engineering Punjab Engineering CollegeChandigarhIndia

scalability and information personal privacy are vital for training and deploying large-scale deep learning *** learning trains models on exclusive information by aggregating weights from various devices and taking advantage of the device-agnostic environment of web ***,relying on a main central server for internet browser-based federated systems can prohibit scalability and interfere with the training process as a result of growing client ***,information relating to the training dataset can possibly be extracted from the distributed weights,potentially reducing the privacy of the local data used for *** this research paper,we aim to investigate the challenges of scalability and data privacy to increase the efficiency of distributed training *** a result,we propose a web-federated learning exchange(WebFLex)framework,which intends to improve the decentralization of the federated learning *** is additionally developed to secure distributed and scalable federated learning systems that operate in web browsers across heterogeneous ***,WebFLex utilizes peer-to-peer interactions and secure weight exchanges utilizing browser-to-browser web real-time communication(WebRTC),efficiently preventing the need for a main central *** has actually been measured in various setups using the MNIsT *** results show WebFLex’s ability to improve the scalability of federated learning systems,allowing a smooth increase in the number of participating devices without central data *** addition,WebFLex can maintain a durable federated learning procedure even when faced with device disconnections and network ***,it improves data privacy by utilizing artificial noise,which accomplishes an appropriate balance between accuracy and privacy preservation.

关键词： Federated learning web browser privacy deep learning

Tubular Heat Enhancement Using Twisted Tape Inserts with Large Holes

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Energy Engineering 2024年第2期121卷 273-290页

作者： ali Jaber Abdulhamed Aws al-Akam Wisam J.Khudhayer ali sabri allw Faculty of Engineering-al-Mussayib University of BabylonHillaBabylon15001Iraq

Heat augmentation techniques play a vital role in the heating and cooling processes in industries,including solar collectors and many applications that utilize heat *** studies are based on inserting fillers inside the tubes to enhance heat *** investigation considered the effects of twisted tapes with large holes on a tubular heat exchanger’s(HX)heat transmission,pressure drop,and thermal boosting *** the experimental section,counter-swirl flow generators used twisted tapes with pairs of 1.0 cm-diameter holes and changes in porosity(Rp)at 1.30%and 2.70%.In the experiments,air was utilized as a working fluid in a tube with a circular *** turbulent flow was considered,with Reynolds numbers(Re)domain from 4800 to 9500,and a boundary condition with a uniform wall heat flux was *** findings expound that when the number of holes rose,the Nusselt number(Nu),the factor of friction(f),and the thermal enhancement factor(η)all increased as ***,as the friction factor increased,the Nusselt number of the tape-equipped tube was noticeably ***,it was discovered that the friction factor was between 70%and 94%lower than the values of the tube without tape,while the(Nu)was between 87%and 97%higher than the conventional tube *** maximum value ofηis 89%.According to the experimental results,empirical correlations for Nu,f,andηwere also generated.

关键词： Tubular heat exchanger tape inserts twisted tape

securing Cloud-Encrypted Data:Detecting Ransomware-as-a-service(Raas)Attacks through Deep Learning Ensemble

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Computers, Materials & Continua 2024年第4期79卷 857-873页

作者： Amardeep singh Hamad ali Abosaq saad Arif Zohaib Mushtaq Muhammad Irfan Ghulam Abbas Arshad ali alanoud al Mazroa school of Computer Information sciences University of CumberlandsWilliamsburgKentucky40769USA Computer science Department College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Electrical Engineering The University of LahoreLahore54000Pakistan Faculty of Computer and Information systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Information systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-service(Raas)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware *** study provides a new approach for Raas attack detection which uses an ensemble of deep learning *** this purpose,the network intrusion detection dataset“UNsWNB15”from the Intelligent security Group of the University of New south Wales,Australia is *** the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are ***,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested *** proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%*** empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual *** expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.

关键词： Cloud encryption Raas ensemble threat detection deep learning cybersecurity

Big data challenge for monitoring quality in higher education institutions using business intelligence dashboards

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Journal of Electronic science and Technology 2024年第1期22卷 25-41页

作者： ali sorour Anthony s.Atkins Faculty of Digital TechnologyInnovationand BusinessStaffordshire UniversityStoke-on-TrentST42DEUnited Kingdom

As big data becomes an apparent challenge to handle when building a business intelligence(BI)system,there is a motivation to handle this challenging issue in higher education institutions(HEIs).Monitoring quality in HEIs encompasses handling huge amounts of data coming from different *** paper reviews big data and analyses the cases from the literature regarding quality assurance(QA)in *** also outlines a framework that can address the big data challenge in HEIs to handle QA monitoring using BI dashboards and a prototype dashboard is presented in this *** dashboard was developed using a utilisation tool to monitor QA in HEIs to provide visual representations of big *** prototype dashboard enables stakeholders to monitor compliance with QA standards while addressing the big data challenge associated with the substantial volume of data managed by HEIs’QA *** paper also outlines how the developed system integrates big data from social media into the monitoring dashboard.

关键词： Big data Business intelligence(BI) Dashboards Higher education(HE) Quality assurance(QA) social media

Adaptive Cloud Intrusion Detection system Based on Pruned Exact Linear Time Technique

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Computers, Materials & Continua 2024年第6期79卷 3725-3756页

作者： Widad Elbakri Maheyzah Md.siraj Bander ali saleh al-rimy sultan Noman Qasem Tawfik al-Hadhrami Faculty of Computing Universiti Teknologi MalaysiaJohor BahruJohor81310Malaysia Computer science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia school of science and Technology Nottingham Trent UniversityNottinghamNG118NSUK

Cloud computing environments,characterized by dynamic scaling,distributed architectures,and complex work-loads,are increasingly targeted by malicious *** threats encompass unauthorized access,data breaches,denial-of-service attacks,and evolving malware *** security solutions often struggle with the dynamic nature of cloud environments,highlighting the need for robust Adaptive Cloud Intrusion Detection systems(CIDs).Existing adaptive CIDs solutions,while offering improved detection capabilities,often face limitations such as reliance on approximations for change point detection,hindering their precision in identifying *** can lead to missed attacks or an abundance of false alarms,impacting overall security *** address these challenges,we propose ACIDs(Adaptive Cloud Intrusion Detection system)-*** novel Adaptive CIDs framework leverages the Pruned Exact Linear Time(PELT)algorithm and a support Vector Machine(sVM)for enhanced accuracy and ***-PELT comprises four key components:(1)Feature selection:Utilizing a hybrid harmony search algorithm and the symmetrical uncertainty filter(HsO-sU)to identify the most relevant features that effectively differentiate between normal and anomalous network traffic in the cloud environment.(2)surveillance:Employing the PELT algorithm to detect change points within the network traffic data,enabling the identification of anomalies and potential security threats with improved precision compared to existing approaches.(3)Training set:Labeled network traffic data forms the training set used to train the sVM classifier to distinguish between normal and anomalous behaviour patterns.(4)Testing set:The testing set evaluates ACIDs-PELT’s performance by measuring its accuracy,precision,and recall in detecting security threats within the cloud *** evaluate the performance of ACIDs-PELT using the NsL-KDD benchmark *** results demonstrate that ACIDs-PELT outperf

关键词： Adaptive cloud IDs harmony search distributed denial of service(DDos) PELT machine learning sVM IsOTCID NsL-KDD

Posture Detection of Heart Disease Using Multi-Head Attention Vision Hybrid(MHAVH)Model

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Computers, Materials & Continua 2024年第5期79卷 2673-2696页

作者： Hina Naz Zuping Zhang Mohammed al-Habib Fuad A.Awwad Emad A.A.Ismail Zaid ali Khan school of Computer science and Engineering Central South UniversityChangsha410003China Department of Quantitative analysis College of Business AdministrationKing Saud UniversityP.O.Box 71115Riyadh11587Saudi Arabia Electrical and Computer Engineering University of VictoriaVictoriaV9A1B8Canada

Cardiovascular disease is the leading cause of death *** disease causes loss of heart muscles and is also responsible for the death of heart cells,sometimes damaging their functionality.A person’s life may depend on receiving timely assistance as soon as ***,minimizing the death ratio can be achieved by early detection of heart attack(HA)*** the United states alone,an estimated 610,000 people die fromheart attacks each year,accounting for one in every four ***,by identifying and reporting heart attack symptoms early on,it is possible to reduce damage and save many lives *** objective is to devise an algorithm aimed at helping individuals,particularly elderly individuals living independently,to safeguard their *** address these challenges,we employ deep learning *** have utilized a vision transformer(ViT)to address this ***,it has a significant overhead cost due to its memory consumption and computational complexity because of scaling dot-product ***,since transformer performance typically relies on large-scale or adequate data,adapting ViT for smaller datasets is more *** response,we propose a three-in-one steam model,theMulti-Head Attention Vision Hybrid(MHAVH).Thismodel integrates a real-time posture recognition framework to identify chest pain postures indicative of heart attacks using transfer learning techniques,such as ResNet-50 and VGG-16,renowned for their robust feature extraction *** incorporatingmultiple heads into the vision transformer to generate additional metrics and enhance heart-detection capabilities,we leverage a 2019 posture-based dataset comprising RGB images,a novel creation by the author that marks the first dataset tailored for posture-based heart attack *** the limited online data availability,we segmented this dataset into gender categories(male and female)and conducted testing on both segmented and original dat

关键词： Image analysis posture of heart attack(PHA)detection hybrid features VGG-16 ResNet-50 vision transformer advance multi-head attention layer

A contrasting analysis of CO_(2) and N_(2) foam flood for enhanced oil recovery and geological storage of CO_(2)

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Petroleum Research 2024年第1期9卷 55-60页

作者： alireza Roozbahani Farshad soofivan ali sagban Hassoon al-Tameemi Hadi Abdollahi sogand saatchi Abdolhamid Ansari Petroleum Engineering Department Faculty of Chemical EngineeringTarbiat Modares UniversityTehranIran school of Chemical and Petroleum Engineering Shiraz UniversityShirazIran school of Chemical and Petroleum Engineering Shiraz BranchIslamic Azad UniversityShirazIran Department of Petroleum Engineering Science and Research BranchAzad UniversityTehranIran Department of Chemistry and Chemical Engineering Rasht BranchIslamic Azad UniversityRashtIran Department of Petroleum Engineering Lamerd BranchIslamic Azad UniversityLamerdIran

Foam flooding using CO_(2)has emerged as a promising method for both enhanced oil recovery(EOR)and the storage of CO_(2)in geological *** study conducts a thorough analysis of the behavior of CO_(2)and N_(2)foams in bulk and porous media,utilizing bubble-scale analyses and foam flooding *** study compares the foamability and longevity of CO_(2)and N_(2)foams,with findings indicating that N_(2)foam bubbles tend to be smaller and less varied in size than CO_(2)foam bubbles,leading to increased foam ***,the study compares the half-lives of CO_(2)and N_(2)foams generated through sparging and winding methods,showing that N_(2)foam has half-lives 22 and 10 times greater than CO_(2)foam when produced using the sparging and winding methods,***,CO_(2)foam generated through the sparging method had a lower foaming volume than N_(2)foam due to CO_(2)'s *** the foam flooding experiments,N_(2)foam proved more effective in recovering oil from porous media than CO_(2)foam,thus demonstrating the effectiveness of the foam injection *** results offer valuable insights into the differing performance of N_(2)and CO_(2)foam floods for EOR and CO_(2)geological storage.

关键词： CO_(2) storage Foam flood Enhanced oil recovery N_(2) foam CO_(2) foam

5G Resource allocation Using Feature selection and Greylag Goose Optimization algorithm

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Computers, Materials & Continua 2024年第7期80卷 1179-1201页

作者： Amel ali alhussan s.K.Towfek Department of Computer sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer science and Intelligent systems Research Center BlacksburgVA 24060USA

In the contemporary world of highly efficient technological development,fifth-generation technology(5G)is seen as a vital step forward with theoretical maximum download speeds of up to twenty gigabits per second(Gbps).As far as the current implementations are concerned,they are at the level of slightly below 1 Gbps,but this allowed a great leap forward from fourth generation technology(4G),as well as enabling significantly reduced latency,making 5G an absolute necessity for applications such as gaming,virtual conferencing,and other interactive electronic *** of this change are not limited to connectivity alone;it urges operators to refine their business strategies and offers users better and improved digital *** essential factor is optimization and the application of artificial intelligence throughout the general arrangement of intricate and detailed 5G *** Binary Greylag Goose Optimization(bGGO)to achieve a significant reduction in the feature set while maintaining or improving model performance,leading to more efficient and effective 5G network management,and Greylag Goose Optimization(GGO)increases the efficiency of the machine ***,the model performs and yields more accurate *** work proposes a new method to schedule the resources in the next generation,5G,based on a feature selection using GGO and a regression model that is an ensemble of K-Nearest Neighbors(KNN),Gradient Boosting,and Extra Trees *** ensemble model shows better prediction performance with the coefficient of determination R squared value equal *** proposed framework is supported by several statistical analyses,such as theWilcoxon signed-rank *** of the benefits of this study are the introduction of new efficient optimization algorithms,the selection of features and more reliable ensemble models which improve the efficiency of 5G technology.

关键词： Optimization ensemble learning 5G technology artificial intelligence greylag goose optimization ANOVA test