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Toward Secure Software-Defined Networks Using Machine Learning: A Review, Research Challenges, and Future Directions

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Computer Systems Science & Engineering 2023年第11期47卷 2201-2217页

作者： muhammad waqas nadeem Hock Guan Goh Yichiet Aun Vasaki Ponnusamy Faculty of Information and Communication Technology Universiti Tunku Abdul RahmanKamparPerakMalaysia Higher Colleges of Technology Fujairah Men’s CampusFujairahUAE

Over the past few years,rapid advancements in the internet and communication technologies have led to increasingly intricate and diverse networking *** a result,greater intelligence is necessary to effectively manage,optimize,and maintain these *** to their distributed nature,machine learning models are challenging to deploy in traditional ***,Software-Defined Networking(SDN)presents an opportunity to integrate intelligence into networks by offering a programmable architecture that separates data and control *** provides a centralized network view and allows for dynamic updates of flow rules and softwarebased traffic *** the programmable nature of SDN makes it easier to deploy machine learning techniques,the centralized control logic also makes it vulnerable to *** address these issues,recent research has focused on developing powerful machine-learning methods for detecting and mitigating attacks in SDN *** paper highlighted the countermeasures for cyberattacks on SDN and how current machine learningbased solutions can overcome these emerging *** also discuss the pros and cons of using machine learning algorithms for detecting and mitigating these ***,we highlighted research issues,gaps,and challenges in developing machine learning-based solutions to secure the SDN controller,to help the research and network community to develop more robust and reliable solutions.

关键词： Botnet attack deep learning distributed denial of service machine learning network security software-defined network

Design and Synthesis of NiO@Co_(3)O_(4)@ZSM-5 Heterogeneous Multitask Hollow Structures for Tandem Catalysis

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Chemical Research in Chinese Universities 2024年第3期40卷 529-535页

作者： muhammad waqas Interdisciplinary Research Center for Refining and Advanced Chemicals King Fahd University of Petroleum&MineralsDhahran 31261Saudi Arabia

Precipitation and impregnation procedures unevenly distribute metals on zeolite,limiting chemical transformation in Lewis-acid,Brönsted-acid and metal-catalyzed tandem ***,heterogeneous multitask transition metals oxides@zeolites are promising catalysts for sustainable processes;nevertheless,synthesis is fascinating and ***,the construction of purposely designed multitask materials segregated in selective shells reveals the remarkable spatial organization of metals-zeolite,resulting in them being suitable for a wide range of tandem *** synthesis of multi-site catalysts begins with a universal wet chemistry approach that yields nickel oxide(NiO)***,the NiO crystals are stabilized using cationic dodecyltrimethylammonium bromide,followed by achieving cross-linking carbon growth by emulsion polymerization of glucose in hydrothermal treatment to yield uniformed NiO@carbon spheres(NiO@CSs).Next,sequential adsorption of cobalt cations and colloidal ZSM-5(1%in H_(2)O,mass fraction),followed by calcination in air,yielded NiO@cobalt oxide@zeolite denoted as NiO@Co_(3)O_(4)@ZEO hollow *** hollowing mechanism and materials segregation within shells are revealed by scanning and transmission electron microscopy,thermogravimetric analysis,and X-ray *** finding advances the rational synthesis of heterogenous core-shell hollow structures for various gas phase catalytic tandem reactions to yield valuable chemicals.

关键词： Multifunctional Core-shell hollow spheres Gas-phase reaction Valuable chemical

Fusion-Based Machine Learning Architecture for Heart Disease Prediction

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Computers, Materials & Continua 2021年第5期67卷 2481-2496页

作者： muhammad waqas nadeem Hock Guan Goh muhammad Adnan Khan Muzammil Hussain muhammad Faheem Mushtaq Vasaki a/p Ponnusamy Faculty of Information and Communication Technology(FICT) Universiti Tunku Abdul Rahman(UTAR)KamparPerak31900Malaysia Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Computer Science School of Systems and TechnologyUniversity of Management and TechnologyLahore54000Pakistan Department of Information Technology Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan

The contemporary evolution in healthcare technologies plays a considerable and signicant role to improve medical services and save human *** disease or cardiovascular disease is the most fatal and complex disease which it is hardly to be detected through our naked eyes,as numerous people have been suffering from this disease *** attacks occur when the ranges of vital signs such as blood pressure,pulse rate,and body temperature exceed their normal *** efcient diagnosis of heart diseases could play a substantial role in the eld of cardiology,while diagnostic time could be *** has been a key challenge for researchers and medical experts to diagnose heart diseases accurately and ***,machine learning-based techniques are used for the diagnosis with higher accuracy,using datasets compiled from former medical patients’*** recent years,numerous studies have been presented in the literature propose machine learning techniques for diagnosing heart ***,the existing techniques have some limitations in terms of their *** this paper,a novel Support Vector Machine(SVM)based architecture for heart disease prediction,empowered with a fuzzy based decision level fusion,is *** SVMbased architecture has improved the accuracy signicantly as compared to existing solutions,where 96.23%accuracy has been achieved.

关键词： Heart disease machine learning support vector machine fuzzy logic fusion cardiovascular

Elevating Image Steganography:A Fusion of MSB Matching and LSB Substitution for Enhanced Concealment Capabilities

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Computers, Materials & Continua 2024年第5期79卷 2923-2943页

作者： muhammad Zaman Ali Omer Riaz Hafiz muhammad Hasnain waqas Sharif Tenvir Ali Gyu Sang Choi Department of Information Technology The Islamia University of BahawalpurBahawalpur63100Pakistan Department of Computer Science The Islamia University of BahawalpurBahawalpur63100Pakistan School of Computer Science and Engineering Yeungnam UniversityGyeongbuk38541Korea

In today’s rapidly evolving landscape of communication technologies,ensuring the secure delivery of sensitive data has become an essential *** overcome these difficulties,different steganography and data encryption methods have been proposed by researchers to secure *** of the proposed steganography techniques achieve higher embedding capacities without compromising visual imperceptibility using LSB *** this work,we have an approach that utilizes a combinationofMost SignificantBit(MSB)matching andLeast Significant Bit(LSB)*** proposed algorithm divides confidential messages into pairs of bits and connects them with the MSBs of individual pixels using pair matching,enabling the storage of 6 bits in one pixel by modifying a maximum of three *** proposed technique is evaluated using embedding capacity and Peak Signal-to-Noise Ratio(PSNR)score,we compared our work with the Zakariya scheme the results showed a significant increase in data concealment *** achieved results of ourwork showthat our algorithmdemonstrates an improvement in hiding capacity from11%to 22%for different data samples while maintaining a minimumPeak Signal-to-Noise Ratio(PSNR)of 37 *** findings highlight the effectiveness and trustworthiness of the proposed algorithm in securing the communication process and maintaining visual integrity.

关键词： Steganography most significant bit(MSB) least significant bit(LSB) peak signal-to-noise ratio(PSNR)

Osteoporosis Prediction for Trabecular Bone using Machine Learning: A Review

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Computers, Materials & Continua 2021年第4期67卷 89-105页

作者： Marrium Anam Vasaki a/p Ponnusamy Muzammil Hussain muhammad waqas nadeem Mazhar Javed Hock Guan Goh Sadia Qadeer Department of Computer Science Government College UniversityFaisalabadPakistan Faculty of Information and Communication Technology(FICT) Universiti Tunku Abdul Rahman(UTAR)KamparMalaysia Department of Computer Science School of Systems and TechnologyUniversity of Management and TechnologyLahorePakistan Department of Computer Science Lahore Garrison UniversityLahorePakistan

Trabecular bone holds the utmost importance due to its significance regarding early bone *** like osteoporosis greatly affect the structure of the Trabecular bone which results in different outcomes like high risk of *** objective of this paper is to inspect the characteristics of the Trabecular Bone by using the Magnetic Resonance Imaging(MRI)*** characteristics prove to be quite helpful in studying different studies related to Trabecular bone such as *** things that were considered before the selection of the articles for the systematic review were language,research field,and electronic *** those articles written in the English language were selected as it is the most prominent language used in scientific,engineering,computer science,and biomedical *** literature review was conducted on the articles published between 2006 and 2020.A total of 62 research papers out of 1050 papers were extracted which were according to our topic of review after screening abstract and article content for the title and abstract *** findings from those researches were compiled at the end of the result *** systematic literature review presents a comprehensive report on scientific researches and studies that have been done in the medical area concerning trabecular bone.

关键词： Magnetic resonance imaging high resolution trabecular bone(TB) bone structure machine learning

Enhanced Object Detection and Classification via Multi-Method Fusion

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Computers, Materials & Continua 2024年第5期79卷 3315-3331页

作者： muhammad waqas Ahmed Nouf Abdullah Almujally Abdulwahab Alazeb Asaad Algarni Jeongmin Park Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Computer Engineering Tech University of Korea237 Sangidaehak-roSiheung-siGyeonggi-do15073South Korea

Advances in machine vision systems have revolutionized applications such as autonomous driving,robotic navigation,and augmented *** substantial progress,challenges persist,including dynamic backgrounds,occlusion,and limited labeled *** address these challenges,we introduce a comprehensive methodology toenhance image classification and object detection *** proposed approach involves the integration ofmultiple methods in a complementary *** process commences with the application of Gaussian filters tomitigate the impact of noise *** images are then processed for segmentation using Fuzzy C-Meanssegmentation in parallel with saliency mapping techniques to find the most prominent *** Binary RobustIndependent Elementary Features(BRIEF)characteristics are then extracted fromdata derived fromsaliency mapsand segmented *** precise object separation,Oriented FAST and Rotated BRIEF(ORB)algorithms *** Algorithms(GAs)are used to optimize Random Forest classifier parameters which lead toimproved *** method stands out due to its comprehensive approach,adeptly addressing challengessuch as changing backdrops,occlusion,and limited labeled data concurrently.A significant enhancement hasbeen achieved by integrating Genetic Algorithms(GAs)to precisely optimize *** minor adjustmentnot only boosts the uniqueness of our system but also amplifies its overall *** proposed methodologyhas demonstrated notable classification accuracies of 90.9%and 89.0%on the challenging Corel-1k and MSRCdatasets,***,detection accuracies of 87.2%and 86.6%have been *** ourmethod performed well in both datasets it may face difficulties in real-world data especially where datasets havehighly complex *** these limitations,GAintegration for parameter optimization shows a notablestrength in enhancing the overall adaptability and performance of our system.

关键词： BRIEF features saliency map fuzzy c-means object detection object recognition

Enhancing Energy Efficiency with a Dynamic Trust Measurement Scheme in Power Distribution Network

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Computers, Materials & Continua 2024年第3期78卷 3909-3927页

作者： Yilei Wang Xin Sun Guiping Zheng Ahmar Rashid Sami Ullah Hisham Alasmary muhammad waqas Zhejiang Electric-Power Corporation Research Institute Zhejiang310014China Faculty of Information Technology Beijing University of TechnologyBeijing100124China Beijing Trusty Cloud Technology Co. Ltd.Beijing100022China Department of Computer Science and Engineering Ghulam Ishaq Khan Institute of Engineering Sciences and EngineeringTopi23640Pakistan Department of Computer Science Shaheed Benazir Bhutto UniversitySheringalUpper Dir18050Pakistan Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha61421Saudi Arabia School of Computing and Mathematical Science Faculty of Engineering and ScienceUniversity of GreenwichLondonSE109LSUK School of Engineering Edith Cowan UniversityPerth6027Australia

The application of Intelligent Internet of Things(IIoT)in constructing distribution station areas strongly supports platform transformation,upgrade,and intelligent *** sensing layer of IIoT comprises the edge convergence layer and the end sensing layer,with the former using intelligent fusion terminals for real-time data collection and ***,the influx of multiple low-voltage in the smart grid raises higher demands for the performance,energy efficiency,and response speed of the substation fusion ***,it brings significant security risks to the entire distribution substation,posing a major challenge to the smart *** response to these challenges,a proposed dynamic and energy-efficient trust measurement scheme for smart grids aims to address these *** scheme begins by establishing a hierarchical trust measurement model,elucidating the trust relationships among smart IoT *** then incorporates multidimensional measurement factors,encompassing static environmental factors,dynamic behaviors,and energy *** comprehensive approach reduces the impact of subjective factors on trust ***,the scheme incorporates a detection process designed for identifying malicious low-voltage end sensing units,ensuring the prompt identification and elimination of any malicious ***,in turn,enhances the security and reliability of the smart grid *** effectiveness of the proposed scheme in pinpointing malicious nodes has been demonstrated through simulation ***,the scheme outperforms established trust metric models in terms of energy efficiency,showcasing its significant contribution to the field.

关键词： IIoT trusted measure energy efficient

An Innovative Approach Using TKN-Cryptology for Identifying the Replay Assault

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Computers, Materials & Continua 2024年第1期78卷 589-616页

作者： Syeda Wajiha Zahra muhammad nadeem Ali Arshad Saman Riaz muhammad Abu Bakr Ashit Kumar Dutta Zaid Alzaid Badr Almutairi Sultan Almotairi Department of Computer Science Alhamd Islamic UniversityIslamabad44000Pakistan Department of Computer Science and Technology University of Science and Technology BeijingBeijing100083China Department of Computer Science National University of TechnologyIslamabad44000Pakistan Department of Electrical Engineering National University of TechnologyIslamabad44000Pakistan Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia Department of Computer Science Faculty of Computer and Information SystemsIslamic University of MadinahMedinah42351Saudi Arabia Department of Information Technology College of Computer Sciences and Information Technology CollegeMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Natural and Applied Sciences Faculty of Community CollegeMajmaah UniversityMajmaah11952Saudi Arabia

Various organizations store data online rather than on physical *** the number of user’s data stored in cloud servers increases,the attack rate to access data from cloud servers also *** researchers worked on different algorithms to protect cloud data from replay *** of the papers used a technique that simultaneously detects a full-message and partial-message replay *** study presents the development of a TKN(Text,Key and Name)cryptographic algorithm aimed at protecting data from replay *** program employs distinct ways to encrypt plain text[P],a user-defined Key[K],and a Secret Code[N].The novelty of the TKN cryptographic algorithm is that the bit value of each text is linked to another value with the help of the proposed algorithm,and the length of the cipher text obtained is twice the length of the original *** the scenario that an attacker executes a replay attack on the cloud server,engages in cryptanalysis,or manipulates any data,it will result in automated modification of all associated values inside the *** mechanism has the benefit of enhancing the detectability of replay ***,the attacker cannot access data not included in any of the papers,regardless of how effective the attack strategy *** the end of paper,the proposed algorithm’s novelty will be compared with different algorithms,and it will be discussed how far the proposed algorithm is better than all other algorithms.

关键词： Replay attack malware message attack file encryption cryptology data security

Multiplicity dependence of the freezeout parameters in high energy hadron-hadron collisions

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Chinese Physics C 2024年第5期48卷 124-133页

作者： muhammad Ajaz Majid Shehzad muhammad waqas Haifa I.Alrebdi Mohammad Ayaz Ahmad Antalov Jagnandan Shawn Jagnandan Murad Badshah Jalal Hasan Baker Abdul Mosawir Quraishi Department of Physics Abdul Wali Khan University MardanMardan 23200Pakistan School of Mathematics Physics and Optoelectronic EngineeringHubei University of Automotive TechnologyShiyan 442002China Department of Physics College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Mathematics Physics and StatisticsFaculty of Natural SciencesUniversity of Guyana101110 GeorgetownGuyananSouth America Department of Physics Faculty of ScienceUniversity of TabukTabukKingdom of Saudi Arabia Department of Electrical Engineering College of EngineeringQassim UniversityUnaizahSaudi Arabia

We examined the transverse momentum(pT)spectra of various identified particles,encompassing both light-flavored and strange hadrons(π++π−,K++K−,p+p¯,ϕ,K0s,Λ+Λ¯,Ξ−+Ξ¯+,andΩ−+Ω¯+),across different multiplicity classes in proton-proton collisions(p-p)at a center-of-mass energy of s√=7 *** the Tsallis and Hagedorn models,parameters relevant to the bulk properties of nuclear matter were *** models exhibit good agreement with experimental *** our analyses,we observed a consistent decrease in the effective temperature(T)for the Tsallis model and the kinetic or thermal freeze-out temperature(T0)for the Hagedorn model,as we transitioned from higher multiplicity(class-I)to lower multiplicity(class-X).This trend is attributed to the diminished energy transfer in higher multiplicity ***,we observed that the transverse flow velocity(βT)experiences a decline from class-I to *** normalization constant,which represents the multiplicity of produced particles,was observed to decrease as we moved toward higher multiplicity *** the effective and kinetic freeze-out temperatures,as well as the transverse flow velocity,show a mild dependency on multiplicity for lighter particles,this dependency becomes more pronounced for heavier *** multiplicity parameter for heavier particles was observed to be smaller than that of lighter particles,indicating a greater abundance of lighter hadrons compared to heavier *** particle species were observed to undergo decoupling from the fireball at distinct temperatures:lighter particles exhibit lower temperatures,while heavier ones show higher temperatures,thereby supporting the concept of multiple freeze-out ***,we identified a positive correlation between the kinetic freeze-out temperature and transverse flow velocity,a scenario where particles experience stronger collective motion at a higher freeze-out *** reason for this positive correlation is th

关键词： multiplicity dependence collective properties thermal energy