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Security Monitoring and Management for the Network Services in the Orchestration of SDN-NFV Environment Using Machine Learning Techniques

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Computer Systems Science & Engineering 2024年第2期48卷 363-394页

作者： Nasser Alshammari Shumaila Shahzadi Saad Awadh Alanazi Shahid Naseem muhammad Anwar Madallah Alruwaili muhammad rizwan abid Omar Alruwaili Ahmed Alsayat Fahad Ahmad Department of Computer Science College of Computer and Information SciencesJouf UniversitySakakaAl Jouf72341Saudi Arabia Department of Computer Sciences Kinnaird College forWomenLahorePunjab54700Pakistan Department of Information Sciences Division of Sciences and TechnologyUniversity of EducationLahore54770Pakistan Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySakaka72341Saudi Arabia Computer Science Florida Polytechnic UniversityLakelandFlorida33805USA Delta3T LahorePunjab54700Pakistan Department of Basic Sciences Common First YearJouf UniversitySakaka72341Saudi Arabia

Software Defined Network(SDN)and Network Function Virtualization(NFV)technology promote several benefits to network operators,including reduced maintenance costs,increased network operational performance,simplified network lifecycle,and policies *** vulnerabilities try to modify services provided by Network Function Virtualization MANagement and Orchestration(NFV MANO),and malicious attacks in different scenarios disrupt the NFV Orchestrator(NFVO)and Virtualized Infrastructure Manager(VIM)lifecycle management related to network services or individual Virtualized Network Function(VNF).This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and handle security functions in order to enhance the quality of experience for end *** anomaly detector investigates these identified risks and provides secure network *** enables virtual network security functions and identifies anomalies in Kubernetes(a cloud-based platform).For training and testing purpose of the proposed approach,an intrusion-containing dataset is used that hold multiple malicious activities like a Smurf,Neptune,Teardrop,Pod,Land,IPsweep,etc.,categorized as Probing(Prob),Denial of Service(DoS),User to Root(U2R),and Remote to User(R2L)*** anomaly detector is anticipated with the capabilities of a Machine Learning(ML)technique,making use of supervised learning techniques like Logistic Regression(LR),Support Vector Machine(SVM),Random Forest(RF),Naïve Bayes(NB),and Extreme Gradient Boosting(XGBoost).The proposed framework has been evaluated by deploying the identified ML algorithm on a Jupyter notebook in Kubeflow to simulate Kubernetes for validation *** classifier has shown better outcomes(99.90%accuracy)than other classifiers in detecting anomalies/intrusions in the containerized environment.

关键词： Software defined network network function virtualization network function virtualization management and orchestration virtual infrastructure manager virtual network function Kubernetes Kubectl artificial intelligence machine learning

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Improving the Position Accuracy and Computational Efficiency of UAV Terrain Aided Navigation Using a Two-Stage Hybrid Fuzzy Particle Filtering Method

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Computers, Materials & Continua 2025年第1期82卷 1193-1210页

作者： Sofia Yousuf muhammad Bilal Kadri College of Engineering Karachi Institute of Economics&TechnologyKarachi75190Pakistan College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia

Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is *** recent years,TAN systems have been extensively researched for both aerial and underwater navigation ***,many TAN systems that rely on recursive Unmanned Aerial Vehicle(UAV)position estimation methods,such as Extended Kalman Filters(EKF),often face challenges with divergence and instability,particularly in highly non-linear *** address these issues,this paper proposes and investigates a hybrid two-stage TAN positioning system for UAVs that utilizes Particle *** enhance the system’s robustness against uncertainties caused by noise and to estimate additional system states,a Fuzzy Particle Filter(FPF)is employed in the first *** approach introduces a novel terrain composite feature that enables a fuzzy expert system to analyze terrain non-linearities and dynamically adjust the number of particles in *** design allows the UAV to be efficiently localized in GPS-denied environments while also reducing the computational complexity of the particle filter in real-time *** the second stage,an Error State Kalman Filter(ESKF)is implemented to estimate the UAV’s *** ESKF is chosen over the conventional EKF method because it is more suitable for non-linear *** results demonstrate that the proposed fuzzy-based terrain composite method achieves high positional accuracy while reducing computational time and memory usage.

关键词： Sensor fusion fuzzy logic particle filter composite feature terrain aided navigation

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Single-cell and spatial omics:exploring hypothalamic heterogeneity

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Neural Regeneration Research 2025年第6期20卷 1525-1540页

作者： muhammad Junaid Eun Jeong Lee Su Bin Lim Department of Biochemistry&Molecular Biology Ajou University School of MedicineSuwonSouth Korea Department of Biomedical Sciences Graduate School of Ajou UniversitySuwonSouth Korea Department of Brain Science Ajou University School of MedicineSuwonSouth Korea

Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges in capturing and analyzing individual cells. These high-throughput omics technologies now offer a remarkable opportunity to comprehend the complex spatiotemporal patterns of transcriptional diversity and cell-type characteristics across the entire hypothalamus. Current single-cell and single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes across various subregions of the hypothalamus. However, single-cell/single-nucleus RNA sequencing requires isolating the cell/nuclei from the tissue, potentially resulting in the loss of spatial information concerning neuronal networks. Spatial transcriptomics methods, by bypassing the cell dissociation, can elucidate the intricate spatial organization of neural networks through their imaging and sequencing technologies. In this review, we highlight the applicative value of single-cell and spatial transcriptomics in exploring the complex molecular-genetic diversity of hypothalamic cell types, driven by recent high-throughput achievements.

关键词： cellular diversity hypothalamus multi-omics single-cell transcriptomics spatial transcriptomics

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Adaptation of Federated Explainable Artificial Intelligence for Efficient and Secure E-Healthcare Systems

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Computers, Materials & Continua 2024年第3期78卷 3413-3429页

作者： Rabia abid muhammad rizwan Abdulatif Alabdulatif Abdullah Alnajim Meznah Alamro Mourade Azrour Department of Computer Science Kinnaird College for WomenLahorePakistan College of Science and Engineering University of DerbyDerbyDE221GBUK Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia STI Laboratory IDMS TeamFaculty of Sciences and TechniquesMoulay Ismail University of MeknèsMeknesMorocco

Explainable Artificial Intelligence(XAI)has an advanced feature to enhance the decision-making feature and improve the rule-based technique by using more advanced Machine Learning(ML)and Deep Learning(DL)based *** this paper,we chose e-healthcare systems for efficient decision-making and data classification,especially in data security,data handling,diagnostics,laboratories,and *** Machine Learning(FML)is a new and advanced technology that helps to maintain privacy for Personal Health Records(PHR)and handle a large amount of medical data *** this context,XAI,along with FML,increases efficiency and improves the security of e-healthcare *** experiments show efficient system performance by implementing a federated averaging algorithm on an open-source Federated Learning(FL)*** experimental evaluation demonstrates the accuracy rate by taking epochs size 5,batch size 16,and the number of clients 5,which shows a higher accuracy rate(19,104).We conclude the paper by discussing the existing gaps and future work in an e-healthcare system.

关键词： Artificial intelligence data privacy federated machine learning healthcare system security

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Modeling and Comprehensive Review of Signaling Storms in 3GPP-Based Mobile Broadband Networks:Causes,Solutions,and Countermeasures

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 123-153页

作者： muhammad Qasim Khan Fazal Malik Fahad Alturise Noor Rahman Department of Computer Science Iqra National UniversityPeshawar25000Pakistan Department of Cybersecurity College of ComputerQassim UniversityBuraydah52555Saudi Arabia Department of Computer Science and Engineering Al-Fayha CollegeAl Jubayl31961Saudi Arabia

Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband ***,they consume important and scarce network resources such as bandwidth and processing *** have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial *** paper draws its motivation from such real network disaster incidents attributed to signaling *** this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and *** provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding *** important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a *** paper presents an update and an extension of our earlier conference *** our knowledge,no similar survey study exists on the subject.

关键词： Signaling storm problems control signaling load analytical modeling 3GPP networks smart devices diameter signaling mobile broadband data access data traffic mobility management signaling network architecture 5G mobile communication

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Comprehensive Review and Analysis on Facial Emotion Recognition:Performance Insights into Deep and Traditional Learning with Current Updates and Challenges

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Computers, Materials & Continua 2025年第1期82卷 41-72页

作者： Amjad Rehman muhammad Mujahid Alex Elyassih Bayan AlGhofaily Saeed Ali Omer Bahaj Artificial Intelligence&Data Analytics Lab College of Computer&Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia MIS Department College of Business Administration Prince Sattam Bin Abdulaziz UniversityAlKharj11942Saudi Arabia

In computer vision and artificial intelligence,automatic facial expression-based emotion identification of humans has become a popular research and industry *** demonstrations and applications in several fields,including computer games,smart homes,expression analysis,gesture recognition,surveillance films,depression therapy,patientmonitoring,anxiety,and others,have brought attention to its significant academic and commercial *** study emphasizes research that has only employed facial images for face expression recognition(FER),because facial expressions are a basic way that people communicate meaning to each *** immense achievement of deep learning has resulted in a growing use of its much architecture to enhance *** review is on machine learning,deep learning,and hybrid methods’use of preprocessing,augmentation techniques,and feature extraction for temporal properties of successive frames of *** following section gives a brief summary of assessment criteria that are accessible to the public and then compares them with benchmark results the most trustworthy way to assess FER-related research topics *** this review,a brief synopsis of the subject matter may be beneficial for novices in the field of FER as well as seasoned scholars seeking fruitful avenues for further *** information conveys fundamental knowledge and provides a comprehensive understanding of the most recent state-of-the-art research.

关键词： Face emotion recognition deep learning hybrid learning CK+ facial images machine learning technological development

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Regression analysis of squeezing-induced hybrid nanofluid flow in Darcy-Forchheimer porous medium

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 193-208页

作者： K.muhammad M.SARFRAZ Department of Humanities and Sciences School of Electrical Engineering and Computer Science National University of Sciences and Technology Department of Mathematics Quaid-i-Azam University

This article presents a mathematical model addressing a scenario involving a hybrid nanofluid flow between two infinite parallel plates. One plate remains stationary, while the other moves downward at a squeezing velocity. The space between these plates contains a Darcy-Forchheimer porous medium. A mixture of water-based fluid with gold(Au) and silicon dioxide(Si O2) nanoparticles is formulated. In contrast to the conventional Fourier's heat flux equation, this study employs the Cattaneo-Christov heat flux equation. A uniform magnetic field is applied perpendicular to the flow direction, invoking magnetohydrodynamic(MHD) effects. Further, the model accounts for Joule heating, which is the heat generated when an electric current passes through the fluid. The problem is solved via NDSolve in MATHEMATICA. Numerical and statistical analyses are conducted to provide insights into the behavior of the nanomaterials between the parallel plates with respect to the flow, energy transport, and skin *** findings of this study have potential applications in enhancing cooling systems and optimizing thermal management strategies. It is observed that the squeezing motion generates additional pressure gradients within the fluid, which enhances the flow rate but reduces the frictional drag. Consequently, the fluid is pushed more vigorously between the plates, increasing the flow velocity. As the fluid experiences higher flow rates due to the increased squeezing effect, it spends less time in the region between the plates. The thermal relaxation, however, abruptly changes the temperature, leading to a decrease in the temperature fluctuations.

关键词： Nanofluidics

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Exploring Nanoscale Perovskite Materials for Next‑Generation Photodetectors:A Comprehensive Review and Future Directions

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Nano-Micro Letters 2025年第2期17卷 46-108页

作者： Xin Li Sikandar Aftab Maria Mukhtar Fahmid Kabir muhammad Farooq Khan Hosameldin Helmy Hegazy Erdi Akman State Key Laboratory of Pulsed Power Laser Technology National University of Defense TechnologyHefei 230037AnhuiPeople’s Republic of China Anhui Laboratory of Advanced Laser Technology Hefei 230037AnhuiPeople’s Republic of China Nanhu Laser Laboratory Changsha 410015HunanPeople’s Republic of China Department of Semiconductor Systems Engineering and Clean Energy Sejong UniversitySeoul 05006Republic of Korea Department of Artificial Intelligence and Robotics Sejong UniversitySeoul 05006Republic of Korea School of Engineering Science Simon Fraser UniversityBurnabyBC V5A 1S6Canada Department of Electrical Engineering Sejong UniversitySeoul 05006South Korea Department of Physics Faculty of ScienceKing Khalid UniversityP.O.Box 9004AbhaSaudi Arabia Central Labs King Khalid UniversityAlQura’aP.O.Box 96061413 AbhaSaudi Arabia Scientific and Technological Research and Application Center Karamanoglu Mehmetbey University70100 KaramanTurkey

The rapid advancement of nanotechnology has sparked much interest in applying nanoscale perovskite materials for photodetection *** materials are promising candidates for next-generation photodetectors(PDs)due to their unique optoelectronic properties and flexible synthesis *** review explores the approaches used in the development and use of optoelectronic devices made of different nanoscale perovskite architectures,including quantum dots,nanosheets,nanorods,nanowires,and *** a thorough analysis of recent literature,the review also addresses common issues like the mechanisms underlying the degradation of perovskite PDs and offers perspectives on potential solutions to improve stability and scalability that impede widespread *** addition,it highlights that photodetection encompasses the detection of light fields in dimensions other than light intensity and suggests potential avenues for future research to overcome these obstacles and fully realize the potential of nanoscale perovskite materials in state-of-the-art photodetection *** review provides a comprehensive overview of nanoscale perovskite PDs and guides future research efforts towards improved performance and wider applicability,making it a valuable resource for researchers.

关键词： Nanoscale perovskites Photodetectors Nanosheets Nanorods Nanowires Quantum dots Nanocrystals

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Prediction of Time Series Empowered with a Novel SREKRLS Algorithm

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Computers, Materials & Continua 2021年第5期67卷 1413-1427页

作者： Bilal Shoaib Yasir Javed muhammad Adnan Khan Fahad Ahmad rizwan Majeed muhammad Saqib Nawaz muhammad Adeel Ashraf abid Iqbal muhammad Idrees School of Computer Science Minhaj University LahoreLahore54000Pakistan Prince Sultan University Riyadh11586Saudi Arabia Department of Computer Science Riphah International University Lahore CampusLahore54000Pakistan Department of Basic Sciences Deanship of Common First YearJouf UniversitySakakaAljouf72341Saudi Arabia Directorate of IT The Islamia University of BahawalpurBahawalpur63100Pakistan Department of Computer Science University of Management and TechnologyLahore54770Pakistan PUCIT University of the PunjabLahore54000Pakistan

For the unforced dynamical non-linear state–space model,a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this *** proposed algorithm lends itself towards the parallel implementation as in the FPGA *** the help of an ortho-normal triangularization method,which relies on numerically stable givens rotation,matrix inversion causes a computational burden,is *** computation possesses many excellent numerical properties such as singularity,symmetry,skew symmetry,and triangularity is achieved by using this *** proposed method is validated for the prediction of stationary and non-stationary Mackey–Glass Time Series,along with that a component in the x-direction of the Lorenz Times Series is also predicted to illustrate its *** the learning curves regarding mean square error(MSE)are witnessed for demonstration with prediction performance of the proposed algorithm from where it’s concluded that the proposed algorithm performs better than *** new SREKRLS based design positively offers an innovative era towards non-linear systolic arrays,which is efficient in developing very-large-scale integration(VLSI)applications with non-linear input *** experiments are carried out to validate the reliability,effectiveness,and applicability of the proposed algorithm and with different noise levels compared to the Extended kernel recursive least-squares(EKRLS)algorithm.

关键词： Kernel methods square root adaptive filtering givens rotation mackey glass time series prediction recursive least squares kernel recursive least squares extended kernel recursive least squares square root extended kernel recursive least squares algorithm

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A Hybrid Approach for Network Intrusion Detection

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Computers, Materials & Continua 2022年第1期70卷 91-107页

作者： Mavra Mehmood Talha Javed Jamel Nebhen Sidra Abbas Rabia abid Giridhar Reddy Bojja muhammad rizwan Department of Computer Science Kinnaird College for WomenLahore54000Pakistan ASET Labs IslamabadPakistan Prince Sattam bin Abdulaziz University College of Computer Science and EngineeringAlkharj11942Saudi Arabia College of Business and Information Systems Dakota State UniversityMadisonUnited States of America

Due to the widespread use of the internet and smart devices,various attacks like intrusion,zero-day,Malware,and security breaches are a constant threat to any organization’s network ***,a Network Intrusion Detection System(NIDS)is required to detect attacks in network *** paper proposes a new hybrid method for intrusion detection and attack *** proposed approach comprises three steps to address high false and low false-negative rates for intrusion detection and attack *** the first step,the dataset is preprocessed through the data transformation technique and min-max ***,the random forest recursive feature elimination method is applied to identify optimal features that positively impact the model’s ***,we use various Support Vector Machine(SVM)types to detect intrusion and the Adaptive Neuro-Fuzzy System(ANFIS)to categorize probe,U2R,R2U,and DDOS *** validation of the proposed method is calculated through Fine Gaussian SVM(FGSVM),which is 99.3%for the binary *** Square Error(MSE)is reported as 0.084964 for training data,0.0855203 for testing,and 0.084964 to validate multiclass categorization.

关键词： Network security intrusion detection system machine learning attacks data mining classification feature selection

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