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Edge-Computing with Graph Computation:A Novel Mechanism to Handle Network Intrusion and Address Spoofing in SDN

Computers, Materials & Continua 2020年第12期65卷 1869-1890页

作者： rashid amin Mudassar Hussain Mohammed Alhameed Syed Mohsan Raza Fathe Jeribi Ali Tahir University of Engineering and Technology TaxilaPakistan University of Wah Wah CanttPakistan Jazan University JazanSaudi Arabia Abasyn University Islamabad IslamabadPakistan

Software Defined Networking(SDN)being an emerging network control model is widely recognized as a control and management *** model provides efficient techniques to control and manage the enterprise *** emerging paradigm is edge computing in which data processing is performed at the edges of the network instead of a central *** data processing at the edge nodes reduces the latency and bandwidth *** SDN,the controller is a single point of *** security issues related to the traditional network can be solved by using SDN central management and *** Spoofing and Network Intrusion are the most common *** attacks severely degrade performance and *** propose an edge computing-based mechanism that automatically detects and mitigates those *** this mechanism,an edge system gets the network topology from the controller and the Address Resolution Protocol(ARP)traffic is directed to it for further *** such,the controller is saved from unnecessary processing related to addressing *** propose a graph computation based method to identify the location of an attacker or intruder by implementing a graph difference *** using the correct location information,the exact attacker or intruder is blocked,while the legitimate users get access to the network *** proposed mechanism is evaluated in a Mininet simulator and a POX *** results show that it improves system performance in terms of attack mitigation time,attack detection time,and bandwidth requirements.

关键词： Software Defined Networking(SDN) edge computing Address Resolution Protocol(ARP) ARP inspection security graph difference

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Enhanced DDoS Detection Using Advanced Machine Learning and Ensemble Techniques in Software Defined Networking

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Computers, Materials & Continua 2024年第11期81卷 3003-3031页

作者： Hira Akhtar Butt Khoula Said Al Harthy Mumtaz Ali Shah Mudassar Hussain rashid amin Mujeeb Ur Rehman Department of Computer Science University of Management and TechnologySialkot51040Pakistan Department of Computer Science and Creative Technologies Global College of Engineering and TechnologyMuscat2546Sultanate of Oman Department of Computer Science University of WahWah Cantt47040Pakistan Department of Computer Science and IT University of ChakwalChakwal48800Pakistan

Detecting sophisticated cyberattacks,mainly Distributed Denial of Service(DDoS)attacks,with unexpected patterns remains challenging in modern *** detection systems often struggle to mitigate such attacks in conventional and software-defined networking(SDN)*** Machine Learning(ML)models can distinguish between benign and malicious traffic,their limited feature scope hinders the detection of new zero-day or low-rate DDoS attacks requiring frequent *** this paper,we propose a novel DDoS detection framework that combines Machine Learning(ML)and Ensemble Learning(EL)techniques to improve DDoS attack detection and mitigation in SDN *** model leverages the“DDoS SDN”dataset for training and evaluation and employs a dynamic feature selection mechanism that enhances detection accuracy by focusing on the most relevant *** adaptive approach addresses the limitations of conventional ML models and provides more accurate detection of various DDoS attack *** proposed ensemble model introduces an additional layer of detection,increasing reliability through the innovative application of ensemble *** proposed solution significantly enhances the model’s ability to identify and respond to dynamic threats in *** provides a strong foundation for proactive DDoS detection and mitigation,enhancing network defenses against evolving *** comprehensive runtime analysis of Simultaneous Multi-Threading(SMT)on identical configurations shows superior accuracy and efficiency,with significantly reduced computational time,making it ideal for real-time DDoS detection in dynamic,rapidly changing *** results demonstrate that our model achieves outstanding performance,outperforming traditional algorithms with 99%accuracy using Random Forest(RF)and K-Nearest Neighbors(KNN)and 98%accuracy using XGBoost.

关键词： Table 1(continued)OSI layer Possible DDoS attack Data link MAC Address Flooding Physical Cable disconnection JaMMING physical impersonation

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An Efficient Mechanism for Product Data Extraction from E-Commerce Websites

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Computers, Materials & Continua 2020年第12期65卷 2639-2663页

作者： Malik Javed Akhtar Zahur Ahmad rashid amin Sultan H.Almotiri Mohammed A.Al Ghamdi Hamza Aldabbas University of Engineering and Technology TaxilaPakistan Computer Science Department Umm Al-Qura UniversityMakkah CitySaudi Arabia Al-Balqa Applied University Al-SaltJordan

A large amount of data is present on the web which can be used for useful purposes like a product recommendation,price comparison and demand forecasting for a particular *** are designed for human understanding and not for ***,to make data machine-readable,it requires techniques to grab data from web *** have addressed the problem using two approaches,i.e.,knowledge engineering and machine *** of the art knowledge engineering approaches use the structure of documents,visual cues,clustering of attributes of data records and text processing techniques to identify data records on a web *** learning approaches use annotated pages to learn *** rules are used to extract data from unseen web *** structure of web documents is continuously ***,new techniques are needed to handle the emerging requirements of web data *** this paper,we have presented a novel,simple and efficient technique to extract data from web pages using visual styles and structure of *** proposed technique detects Rich Data Region(RDR)using query and correlative words of the *** is then divided into data records using style *** elements are removed using a Common Tag Sequence(CTS)and formatting *** system is implemented using JAVA and runs on the dataset of real-world working *** effectiveness of results is evaluated using precision,recall,and F-measure and compared with five existing systems.A comparison of the proposed technique to existing systems has shown encouraging results.

关键词： Document object model rich data region common tag sequence web data extraction deep web mining

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An IoT Environment Based Framework for Intelligent Intrusion Detection

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Computers, Materials & Continua 2023年第5期75卷 2365-2381页

作者： Hamza Safwan Zeshan Iqbal rashid amin Muhammad Attique Khan Majed Alhaisoni Abdullah Alqahtani Ye Jin Kim Byoungchol Chang Deparment of Computer Science UET TaxilaTaxila47080Pakistan Department of Computer Science HITEC UniversityTaxila47080Pakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea Center for Computational Social Science Hanyang UniversitySeoul04763Korea

Software-defined networking(SDN)represents a paradigm shift in network traffic *** distinguishes between the data and control *** are then used to communicate between these *** controller is central to the management of an SDN network and is subject to security *** research shows how a deep learning algorithm can detect intrusions in SDN-based IoT ***,low accuracy,and efficient feature selection is all *** propose a hybrid machine learning-based approach based on Random Forest and Long Short-Term Memory(LSTM).In this study,a new dataset based specifically on Software Defined Networks is used in *** obtain the best and most relevant features,a feature selection technique is *** experiments have revealed that the proposed solution is a superior method for detecting flow-based *** performance of our proposed model is also measured in terms of accuracy,recall,and precision.F1 rating and detection time Furthermore,a lightweight model for training is proposed,which selects fewer features while maintaining the model’s *** show that the adopted methodology outperforms existing models.

关键词： Software-defined networks prediction modeling machine learning deep learning

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Detection Collision Flows in SDN Based 5G Using Machine Learning Algorithms

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Computers, Materials & Continua 2023年第1期74卷 1413-1435页

作者： Aqsa Aqdus rashid amin Sadia Ramzan Sultan S.Alshamrani Abdullah Alshehri El-Sayed M.El-kenawy Department of Computer Science University of Engineering and Technology Taxila47050Pakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Information Technology Al Baha UniversityAl BahaSaudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt

The rapid advancement of wireless communication is forming a hyper-connected 5G network in which billions of linked devices generate massive amounts of *** traffic control and data forwarding functions are decoupled in software-defined networking(SDN)and allow the network to be *** switch in SDN keeps track of forwarding information in a flow *** SDN switches must search the flow table for the flow rules that match the packets to handle the incoming *** to the obvious vast quantity of data in data centres,the capacity of the flow table restricts the data plane’s forwarding ***,the SDN must handle traffic from across the whole *** flow table depends on Ternary Content Addressable Memorable Memory(TCAM)for storing and a quick search of regulations;it is restricted in capacity owing to its elevated cost and energy *** the flow table is abused and overflowing,the usual regulations cannot be executed *** this case,we consider lowrate flow table overflowing that causes collision flow rules to be installed and consumes excessive existing flow table capacity by delivering packets that don’t fit the flow table at a low *** study introduces machine learning techniques for detecting and categorizing low-rate collision flows table in SDN,using Feed ForwardNeuralNetwork(FFNN),K-Means,and Decision Tree(DT).We generate two network topologies,Fat Tree and Simple Tree Topologies,with the Mininet simulator and coupled to the OpenDayLight(ODL)*** efficiency and efficacy of the suggested algorithms are assessed using several assessment indicators such as success rate query,propagation delay,overall dropped packets,energy consumption,bandwidth usage,latency rate,and *** findings showed that the suggested technique to tackle the flow table congestion problem minimizes the number of flows while retaining the statistical consistency of the 5G *** putting the proposed flow method

关键词： 5G networks software-defined networking(SDN) OpenFlow load balancing machine learning(ML) feed forward neural network(FFNN) k-means and decision tree(DT)

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Hybrid Grey Wolf and Dipper Throated Optimization in Network Intrusion Detection Systems

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Computers, Materials & Continua 2023年第2期74卷 2695-2709页

作者： Reem Alkanhel Doaa Sami Khafaga El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim rashid amin Mostafa Abotaleb B.M.El-den Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science University of Engineering and TechnologyTaxilaPakistan Department of System Programming South Ural State UniversityChelyabinsk454080Russia

The Internet of Things(IoT)is a modern approach that enables connection with a wide variety of devices *** to the resource constraints and open nature of IoT nodes,the routing protocol for low power and lossy(RPL)networks may be vulnerable to several routing ***’s why a network intrusion detection system(NIDS)is needed to guard against routing assaults on RPL-based IoT *** imbalance between the false and valid attacks in the training set degrades the performance of machine learning employed to detect network ***,we propose in this paper a novel approach to balance the dataset classes based on metaheuristic optimization applied to locality-sensitive hashing and synthetic minority oversampling technique(LSH-SMOTE).The proposed optimization approach is based on a new hybrid between the grey wolf and dipper throated optimization *** prove the effectiveness of the proposed approach,a set of experiments were conducted to evaluate the performance of NIDS for three cases,namely,detection without dataset balancing,detection with SMOTE balancing,and detection with the proposed optimized LSHSOMTE *** results showed that the proposed approach outperforms the other approaches and could boost the detection *** addition,a statistical analysis is performed to study the significance and stability of the proposed *** conducted experiments include seven different types of attack cases in the RPL-NIDS17 *** on the 2696 CMC,2023,vol.74,no.2 proposed approach,the achieved accuracy is(98.1%),sensitivity is(97.8%),and specificity is(98.8%).

关键词： Metaheuristics grey wolf optimization dipper throated optimization dataset balancing locality sensitive hashing SMOTE

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Modeling the dynamical behavior of the interaction of T-cells and human immunodeficiency virus with saturated incidence

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Communications in Theoretical Physics 2024年第3期76卷 1-14页

作者： Salah Boulaaras rashid Jan amin Khan Ali Allahem Imtiaz Ahmad Salma Bahramand Department of Mathematics College of ScienceQassim UniversityBuraydah51452Saudi Arabia Institute of Energy Infrastructure(IEI) Department of Civil EngineeringCollege of EngineeringUniversiti Tenaga Nasional(UNITEN)Putrajaya CampusJalan IKRAM-UNITEN43000 KajangSelangorMalaysia Department of Mathematics University of SwabiSwabi 23561Pakistan Department of Mathematics College of SciencesQassim UniversitySaudi Arabia Institute of Informatics and Computing in Energy(IICE) Universiti Tenaga NasionalKajangSelangorMalaysia Department of Political Science Bacha Khan University CharsaddaCharsadda 24420KPK Pakistan

In the last forty years,the rise of HIV has undoubtedly become a major concern in the field of public health,imposing significant economic burdens on affected ***,it becomes imperative to undertake comprehensive investigations into the mechanisms governing the dissemination of HIV within the human *** this work,we have devised a mathematical model that elucidates the intricate interplay between CD4^(+)T-cells and viruses of HIV,employing the principles of fractional *** production rate of CD4^(+)T-cells,like other immune cells depends on certain factors such as age,health status,and the presence of infections or ***,we incorporate a variable source term in the dynamics of HIV infection with a saturated incidence rate to enhance the precision of our *** introduce the fundamental concepts of fractional operators as a means of scrutinizing the proposed HIV *** facilitate a deeper understanding of our system,we present an iterative scheme that elucidates the trajectories of the solution pathways of the *** show the time series analysis of our model through numerical findings to conceptualize and understand the key factors of the *** addition to this,we present the phase portrait and the oscillatory behavior of the system with the variation of different input *** information can be utilized to predict the long-term behavior of the system,including whether it will converge to a steady state or exhibit periodic or chaotic oscillations.

关键词： HIV infection fractional-calculus dynamics of HIV iterative scheme dynamical behaviour mathematical model fractional derivatives

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Carbon potentials of different biochars derived from municipal solid waste in a saline soil

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Pedosphere 2022年第2期32卷 283-293页

作者： Hamna SALEEM Mahtab AHMAD Jamshaid rashid Munir AHMAD Mohammad I.AL-WABEL Memuna amin Department of Environmental Sciences Faculty of Biological SciencesQuaid-i-Azam UniversityIslamabad 45320Pakistan Soil Sciences Department College of Food&Agricultural SciencesKing Saud UniversityP.O.Box 2460Riyadh 11451Saudi Arabia

There are numerous studies conducted on biochar for its carbon (C) sequestration potential;however,there are limited studies available on the behavior of salt-affected soils related to biochar ***,more studies are needed to elucidate the mechanisms through which biochar affects saline soil *** this study,biochars were produced from solid waste at pyrolysis temperatures of 300,500,and 700?C (BC300,BC500,and BC700,respectively)and applied to a saline soil to evaluate their impacts on soil carbon dioxide (CO_(2)) efflux,C sequestration,and soil quality.A soil incubation experiment lasting for 107 d was *** results showed that soil CO_(2) efflux rate,cumulative CO_(2) emission,active organic C (AOC),and organic matter (OM)significantly increased with BC300 application to a greater extent than those with BC500 and BC700 as compared to those in the no-biochar control (CK).However,soil C non-lability did not significantly increase in the treatments with biochars,except BC700,as compared to that in *** improving the soil quality by increasing the soil AOC and OM,BC300 showed positive impacts in terms of increasing CO_(2) emission from the saline soil,while BC500 and BC700 showed greater potentials of sequestering C in the saline soil by increasing the soil non-labile C *** recalcitrance index (R50) values of BC500 and BC700 were>0.8,indicating their high stability in the saline *** could be concluded that biochars pyrolyzed at high temperatures (?500?C)could be suitable in terms of C sequestration,while biochars pyrolyzed at low temperatures (?300?C) could be suitable for improving saline soil quality.

关键词： carbon sequestration carbon storage climate change CO_(2)efflux CO_(2)emission pyrolysis temperature recalcitrance index soil quality

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Fuzzy-HLSTM(Hierarchical Long Short-Term Memory)for Agricultural Based Information Mining

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Computers, Materials & Continua 2023年第2期74卷 2397-2413页

作者： Ahmed Abdu Alattab Mohammed Eid Ibrahim Reyazur rashid Irshad Anwar Ali Yahya amin A.Al-Awady Department of Computer Science College of Science and ArtsSharurahNajran UniversityNajranSaudi Arabia Department of Computer Science College of Computer Science&Information SystemsNajran UniversityNajranSaudi Arabia Computer Skills Department Deanship of Preparatory YearNajran UniversityNajranSaudi Arabia

This research proposes a machine learning approach using fuzzy logic to build an information retrieval system for the next crop *** case-based reasoning systems,case representation is critical,and thus,researchers have thoroughly investigated textual,attribute-value pair,and ontological *** big databases result in slow case retrieval,this research suggests a fast case retrieval strategy based on an associated representation,so that,cases are interrelated in both either similar or dissimilar *** soon as a new case is recorded,it is compared to prior data to find a relative *** proposed method is worked on the number of cases and retrieval accuracy between the related case representation and conventional *** Long Short-Term Memory(HLSTM)is used to evaluate the efficiency,similarity of the models,and fuzzy rules are applied to predict the environmental condition and soil quality during a particular time of the *** on the results,the proposed approaches allows for rapid case retrieval with high accuracy.

关键词： Machine learning agriculture IoT HLSTM fuzzy rules

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Ab initio study of structural, electronic and optical properties of ternary CdOl-xSex alloys using special quasi-random structures

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Chinese Physics B 2014年第1期23卷 399-406页

作者： Muhammad rashid fayyazhussain248@*** Department of Physics University of the Punjab Quaid-e-Azam Campus Lahore 54590 Pakistan

The structural, electronic, and optical properties of binary CdO, CdSe, and their ternary CdO1 xSexalloys(0 ≤ x ≤ 1) in the rock salt and zinc blend phases have been studied by the special quasi-random structure(SQS) method. All the calculations are performed using full-potential linearized augmented plane wave plus local orbital’s(FP-LAPW+lo) method within the framework of density function theory(DFT). We use Wu–Cohen(WC) generalized gradient approximation(GGA) to calculate structural parameters, whereas both Wu–Cohen and Engel–Vosko(EV) GGA have been applied to calculate electronic structure of the materials. Our predicted results of lattice constant and bulk modulus show only a slight deviation from Vegard’s law for the whole concentrations. The obtained band structure indicates that for the rock-salt phase, the ternary alloys present semi-metallic behavior, while for the zinc blend phase, semiconductor behavior with direct bandgap is observed with decreasing order of x except for CdSe. Finally, by incorporating the basic optical properties, we discuss the dielectric function, refractive index, optical reflectivity, the absorption coefficient, and optical conductivity in terms of incident photon energy up to 14 eV. The calculated results of both binaries are in agreement with existing experimental and theoretical values.

关键词： density functional theory structural electronic and optical properties

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