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

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

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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

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Injury Pattern among Road Traffic Accidents’ Victims in Najran City, Saudi Arabia

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International Journal of Clinical Medicine 2018年第4期9卷 270-280页

作者： Mahdi Yahya al-Zamanan abdullah Saleh al-Yami ali abdullah al-najrani Mansour Yousef al-Asmari Abdulrahman alamri Manaa Awad Mohammed al-Qahtani Mohammed Helmy Faris Shalayel Abdulhadi Mohamed Elbashir Saeed ali alsareii College of Medicine Najran University Najran Saudi Arabia Department of Surgery College of Medicine Najran University Najran Saudi Arabia Department of Surgery College of Medicine Najran University Najran Saudi Arabia Department of Family and Community Medicine College of Medicine Najran University Najran Saudi Arabia

Traffic accidents constitute the substantial cause of disability and mortality in the young Saudi individuals reaching horrible figures. The aim of this study was to review and identify the pattern of injury among road traffic accident (RTA) victims as well as the peak time of accidents and their implications. This retrospective hospital-based cross-sectional study was carried out in the period between April 2016 to March 2017 in King Khalid Hospital, Maternity and Children Hospital and Najran General Hospital, Najran, Saudi Arabia. all RTA victims admitted to the emergency departments of the pre-mentioned hospitals. Data collected from 435 Saudis and non-Saudis’ files were statistically analyzed with regard to age, gender, the timing of road traffic accidents, injury pattern, and neurological deficits incidence. Most of the RTAs’ cases (92%) were male victims with the highest peak in the age group 20 - 29 years. 58% of the RTAs happened in the evening (6:00 PM-9:00 PM) while 20% occurred in the morning. Head injury represented the most frequent pattern (36%) followed by the spinal injury (23%), lower limb injury (23%), upper limb injury (20%), thoracic injury (17%), pelvic injury and abdominal injury (8%). 4.4% of RTAs resulted in death whilst 9% of cases experienced neurological deficits. In conclusion, young male drivers in Najran recorded the highest frequency of RTAs. Initiation of road safety education and expansion of speed detectors (Saher) system deployment is highly recommended.

关键词： Road Traffic Accidents (RTA) Road Traffic Injuries (RTIs) Disability

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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

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Nasal Dermoid Cyst with Sinus Tract Intranasal Bone: A Case Report

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International Journal of Otolaryngology and Head & Neck Surgery 2024年第2期13卷 149-156页

作者： Sultan Kadasah abdullah alhelali Saud aldhabaan Abdulaziz al Qahtani abdullah Musleh ali alshahrani Shahd Dlboh Sahar al-Otaibi Department of Surgery College of Medicine University of Bisha Bisha Saudi Arabia Department of Otolaryngology Head and Neck Surgery Abha Children’s Hospital Abha Saudi Arabia Department of Otolaryngology Head and Neck Surgery Armed Forces Southern Region Hospital Khamis Mushait Saudi Arabia Department of Surgery College of Medicine King Khalid University Abha Saudi Arabia College of Medicine King Khalid University Abha Saudi Arabia

Dermoid cysts are benign tumors originating from germ cells, which can form in various locations, including the nasal area in rare cases. They are of unknown exact etiology, but it is suggested that it is due to abnormal tissue migration during early embryonic development. Nasal dermoid cysts albeit rare, can present in various forms such as sinuses, fistulas, or intracranially extending tracts. They can be asymptomatic and incidentally discovered or present with a visible external mass or sinus that is either painful, infected or cosmetically concerning. If nasal dermoid cysts with an intra-nasal bone sinus tract are left untreated, they can lead to life-threatening complications. This report describes the case of a 6-year-old girl with a nasal dermoid cyst connected to a superficial punctum by an intra-nasal tract. She had undergone surgical excision of a nasal swelling previously diagnosed as a dermoid cyst. One year later, she returned to our clinic with a recurrence of the nasal swelling. Imaging tests revealed a nasal dermoid cyst with a tract extending to the nasal tip, without intracranial expansion. The cyst, along with the entire tract, was successfully removed surgically, and the postoperative follow-up indicated no complications. Histopathology confirmed the diagnosis of a dermoid cyst. This case underscores the significance of considering the dermoid tract in nasal cyst cases and the necessity of its complete removal to prevent recurrence.

关键词： Dermoid Cyst Nasal Sinus Sinus Tract Intranasal Bone Benign Tumor Congenital Anomaly

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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

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Contrast Normalization Strategies in Brain Tumor Imaging:From Preprocessing to Classification

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1539-1562页

作者： Samar M.alqhtani Toufique A.Soomro Faisal Bin Ubaid Ahmed ali Muhammad Irfan abdullah A.Asiri Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Electronic Engineering The University of LarkanoLarkanaSindh75660Pakistan Computer Science Department Sukkur IBA UniversitySukkurSindh65200Pakistan Eletrical Engineering Department Sukkur IBA UniversitySukkurSindh65200Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia

Cancer-related to the nervous system and brain tumors is a leading cause of mortality in various *** resonance imaging(MRI)and computed tomography(CT)are utilized to capture brain *** plays a crucial role in the diagnosis of brain tumors and the examination of other brain ***,manual assessment of MRI images by radiologists or experts is performed to identify brain tumors and abnormalities in the early stages for timely ***,early diagnosis of brain tumors is intricate,necessitating the use of computerized *** research introduces an innovative approach for the automated segmentation of brain tumors and a framework for classifying different regions of brain *** proposed methods consist of a pipeline with several stages:preprocessing of brain images with noise removal based on Wiener Filtering,enhancing the brain using Principal Component Analysis(PCA)to obtain well-enhanced images,and then segmenting the region of interest using the Fuzzy C-Means(FCM)clustering technique in the third *** final step involves classification using the Support Vector Machine(SVM)*** classifier is applied to various types of brain tumors,such as meningioma and pituitary tumors,utilizing the Contrast-Enhanced Magnetic Resonance Imaging(CE-MRI)*** proposed method demonstrates significantly improved contrast and validates the effectiveness of the classification framework,achieving an average sensitivity of 0.974,specificity of 0.976,accuracy of 0.979,and a Dice Score(DSC)of ***,this method exhibits a shorter processing time of 0.44 s compared to existing *** performance of this method emphasizes its significance when compared to state-of-the-art methods in terms of sensitivity,specificity,accuracy,and *** enhance the method further in the future,it is feasible to standardize the approach by incorporating a set of classifiers to increase the robustness of the brain classi

关键词： Brain tumor magnetic resonance imaging principal component analysis fuzzy c-clustering support vector machine

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Human Gait Recognition for Biometrics Application Based on Deep Learning Fusion Assisted Framework

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Computers, Materials & Continua 2024年第1期78卷 357-374页

作者： Ch Avais Hanif Muhammad ali Mughal Muhammad Attique Khan Nouf abdullah almujally Taerang Kim Jae-Hyuk Cha Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea

The demand for a non-contact biometric approach for candidate identification has grown over the past ten *** on the most important biometric application,human gait analysis is a significant research topic in computer *** have paid a lot of attention to gait recognition,specifically the identification of people based on their walking patterns,due to its potential to correctly identify people far *** recognition systems have been used in a variety of applications,including security,medical examinations,identity management,and access *** systems require a complex combination of technical,operational,and definitional *** employment of gait recognition techniques and technologies has produced a number of beneficial and well-liked *** proposes a novel deep learning-based framework for human gait classification in video *** framework’smain challenge is improving the accuracy of accuracy gait classification under varying conditions,such as carrying a bag and changing *** proposed method’s first step is selecting two pre-trained deep learningmodels and training fromscratch using deep transfer ***,deepmodels have been trained using static hyperparameters;however,the learning rate is calculated using the particle swarmoptimization(PSO)***,the best features are selected from both trained models using the Harris Hawks controlled Sine-Cosine optimization *** algorithm chooses the best features,combined in a novel correlation-based fusion ***,the fused best features are categorized using medium,bi-layer,and tri-layered neural *** the publicly accessible dataset known as the CASIA-B dataset,the experimental process of the suggested technique was carried out,and an improved accuracy of 94.14% was *** achieved accuracy of the proposed method is improved by the recent state-of-the-art techniques that show the significance of this wor

关键词： Gait recognition covariant factors biometric deep learning fusion feature selection

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Smart Farming for Sustainable Rice Production:An Insight into Application,Challenge,and Future Prospect

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Rice science 2024年第1期31卷 47-61页

作者： Norhashila HASHIM Maimunah Mohd ali Muhammad Razif MAHADI Ahmad Fikri abdullah Aimrun WAYAYOK Muhamad Saufi Mohd KASSIM Askiah JAMalUDDIN Department of Biological and Agricultural Engineering/SMART Farming Technology Research Centre Faculty of EngineeringUniversiti Putra MalaysiaSelangor 43400Malaysia Department of Food Sciences Faculty of Science and TechnologyUniversiti Kebangsaan MalaysiaSelangor 43600Malaysia Department of Resource Management&Consumer Studies Faculty of Human EcologyUniversiti Putra MalaysiaSelangor 43400Malaysia

Rice has a huge impact on socio-economic growth,and ensuring its sustainability and optimal utilization is *** review provides an insight into the role of smart farming in enhancing rice *** applications of smart farming in rice production including yield estimation,smart irrigation systems,monitoring disease and growth,and predicting rice quality and classifications are *** challenges of smart farming in sustainable rice production to enhance the understanding of researchers,policymakers,and stakeholders are *** efforts have been exerted to combat the issues in rice production in order to promote rice sector *** effective implementation of smart farming in rice production has been facilitated by various technical advancements,particularly the integration of the Internet of Things and artificial *** future prospects of smart farming in transforming existing rice production practices are also *** the utilization of smart farming,the rice industry can attain sustainable and resilient production systems that could mitigate environmental impact and safeguard food ***,the rice industry holds a bright future in transforming current rice production practices into a new outlook in rice smart farming development.

关键词： rice production smart farming food security agriculture sustainability

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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

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