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Fine-Tuning Cyber Security Defenses: Evaluating Supervised Machine Learning Classifiers for Windows Malware Detection

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Computers, Materials & Continua 2024年第8期80卷 2917-2939页

作者： Islam Zada Mohammed Naif alatawi Syed Muhammad Saqlain Abdullah Alshahrani Adel Alshamran Kanwal Imran Hessa Alfraihi Department of Software Engineering International Islamic UniversityIslamabad25000Pakistan Information Technology Department Faculty of Computers and Information TechnologyUniversity of TabukTabuk71491Saudi Arabia Department of Computer Science and Artificial Intelligence College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Cybersecurity College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Computer Science University of PeshawarPeshawar25121Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Malware attacks on Windows machines pose significant cybersecurity threats,necessitating effective detection and prevention *** machine learning classifiers have emerged as promising tools for malware ***,there remains a need for comprehensive studies that compare the performance of different classifiers specifically for Windows malware *** this gap can provide valuable insights for enhancing cybersecurity *** numerous studies have explored malware detection using machine learning techniques,there is a lack of systematic comparison of supervised classifiers for Windows malware *** the relative effectiveness of these classifiers can inform the selection of optimal detection methods and improve overall security *** study aims to bridge the research gap by conducting a comparative analysis of supervised machine learning classifiers for detecting malware on Windows *** objectives include Investigating the performance of various classifiers,such as Gaussian Naïve Bayes,K Nearest Neighbors(KNN),Stochastic Gradient Descent Classifier(SGDC),and Decision Tree,in detecting Windows *** the accuracy,efficiency,and suitability of each classifier for real-world malware detection *** the strengths and limitations of different classifiers to provide insights for cybersecurity practitioners and *** recommendations for selecting the most effective classifier for Windows malware detection based on empirical *** study employs a structured methodology consisting of several phases:exploratory data analysis,data preprocessing,model training,and *** data analysis involves understanding the dataset’s characteristics and identifying preprocessing *** preprocessing includes cleaning,feature encoding,dimensionality reduction,and optimization to prepare the data for *** training utilizes various

关键词： Security and privacy challenges in the context of requirements engineering supervisedmachine learning malware detection windows systems comparative analysis Gaussian Naive Bayes K Nearest Neighbors Stochastic Gradient Descent Classifier Decision Tree

Potential Benefits and Obstacles of the Use of Internet of Things in Saudi Universities: Empirical Study

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Advances in Internet of Things 2024年第1期14卷 1-20页

作者： Najmah Adel Fallatah Fahad Mahmoud Ghabban Omair Ameerbakhsh Ibrahim Alfadli Wael Ghazy Alheadary salem Sulaiman alatawi Ashwaq Hasen Al-Shehri College of Computer Science and Engineering Taibah University Madinah Saudi Arabia Ministry of Education in Al-Madinah Al-Munawwarah Region Madinah Saudi Arabia

Internet of Things (IoT) among of all the technology revolutions has been considered the next evolution of the internet. IoT has become a far more popular area in the computing world. IoT combined a huge number of things (devices) that can be connected through the internet. The purpose: this paper aims to explore the concept of the Internet of Things (IoT) generally and outline the main definitions of IoT. The paper also aims to examine and discuss the obstacles and potential benefits of IoT in Saudi universities. Methodology: the researchers reviewed the previous literature and focused on several databases to use the recent studies and research related to the IoT. Then, the researchers also used quantitative methodology to examine the factors affecting the obstacles and potential benefits of IoT. The data were collected by using a questionnaire distributed online among academic staff and a total of 150 participants completed the survey. Finding: the result of this study reveals there are twelve factors that affect the potential benefits of using IoT such as reducing human errors, increasing business income and worker’s productivity. It also shows the eighteen factors which affect obstacles the IoT use, for example sensors’ cost, data privacy, and data security. These factors have the most influence on using IoT in Saudi universities.

关键词： Internet of Things (IoT) M2M Factors Obstacles Potential Benefits Universities

Anomaly Detection Framework in Fog-to-Things Communication for Industrial Internet of Things

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Computers, Materials & Continua 2022年第10期73卷 1067-1086页

作者： Tahani alatawi Ahamed Aljuhani College of Computing and Information Technology University of TabukTabuk71491Saudi Arabia

The rapid development of the Internet of Things(IoT)in the industrial domain has led to the new term the Industrial Internet of Things(IIoT).The IIoT includes several devices,applications,and services that connect the physical and virtual space in order to provide smart,cost-effective,and scalable *** the IIoT has been deployed and integrated into a wide range of industrial control systems,preserving security and privacy of such a technology remains a big *** anomaly-based Intrusion Detection System(IDS)can be an effective security solution for maintaining the confidentiality,integrity,and availability of data transmitted in IIoT *** this paper,we propose an intelligent anomalybased IDS framework in the context of fog-to-things communications to decentralize the cloud-based security solution into a distributed architecture(fog nodes)near the edge of the data *** anomaly detection system utilizes minimum redundancy maximum relevance and principal component analysis as the featured engineering methods to select the most important features,reduce the data dimensionality,and improve detection *** the classification stage,anomaly-based ensemble learning techniques such as bagging,LPBoost,RUSBoost,and Adaboost models are implemented to determine whether a given flow of traffic is normal or *** validate the effectiveness and robustness of our proposed model,we evaluate our anomaly detection approach on a new driven IIoT dataset called XIIoTID,which includes new IIoT protocols,various cyberattack scenarios,and different attack *** experimental results demonstrated that our proposed anomaly detection method achieved a higher accuracy rate of 99.91%and a reduced false alarm rate of 0.1%compared to other recently proposed techniques.

关键词： Anomaly detection anomaly-based IDS fog computing Internet of Things(IoT) Industrial Internet of Things(IIoT) IDS Industrial Control Systems(ICSs)

Continuous Mobile User Authentication Using a Hybrid CNN-Bi-LSTM Approach

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计算机、材料和连续体（英文） 2023年第4期75卷 651-667页

作者： Sarah Alzahrani Joud Alderaan Dalya alatawi Bandar Alotaibi Department of Information Technology University of TabukTabuk71491Saudi Arabia Sensor Networks and Cellular Systems Research Center University of TabukTabuk71491Saudi Arabia

Internet of Things (IoT) devices incorporate a large amount ofdata in several fields, including those of medicine, business, and *** authentication is paramount in the IoT era to assure connecteddevices’ security. However, traditional authentication methods and conventionalbiometrics-based authentication approaches such as face recognition,fingerprints, and password are vulnerable to various attacks, including smudgeattacks, heat attacks, and shoulder surfing attacks. Behavioral biometrics isintroduced by the powerful sensing capabilities of IoT devices such as smartwearables and smartphones, enabling continuous authentication. ArtificialIntelligence (AI)-based approaches introduce a bright future in refining largeamounts of homogeneous biometric data to provide innovative user authenticationsolutions. This paper presents a new continuous passive authenticationapproach capable of learning the signatures of IoT users utilizing smartphonesensors such as a gyroscope, magnetometer, and accelerometer to recognizeusers by their physical activities. This approach integrates the convolutionalneural network (CNN) and recurrent neural network (RNN) models to learnsignatures of human activities from different users. A series of experiments areconducted using the MotionSense dataset to validate the effectiveness of theproposed method. Our technique offers a competitive verification accuracyequal to 98.4%.We compared the proposed method with several conventionalmachine learning and CNN models and found that our proposed modelachieves higher identification accuracy than the recently developed verificationsystems. The high accuracy achieved by the proposed method proves itseffectiveness in recognizing IoT users passively through their physical activitypatterns.

关键词： Human activity recognition recurrent neural network(RNN) internet of things(IoT) machine learning(ML)

Barriers of Asthma Care among Asthmatic Children in Saudi Arabia: Maternal Perspectives

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Open Journal of Pediatrics 2020年第2期10卷 302-313页

作者： Abeer alatawi Meshaal Alanazi Department of Nursing Faculty of Applied Medical Sciences Tabuk University Tabuk Saudi Arabia Department of Emergency Medical Services Saudi Red Crescent Authority Tabuk Saudi Arabia

Background Bronchial asthma is one of the most common chronic conditions among children. Despite the improvement in asthma treatment regimens, its prevalence and related morbidity are increasing, especially among underserved, minority children. There are barriers in the management of asthma, which may impact the quality of outcomes. The goal of this study is to explore these barriers. Methods A cross-sectional study was conducted on interview data collected through 2019 from mothers of children (aged 6 - 12 years) with asthma visiting, for convenience, a public shopping mall. The interviewees were randomly selected, because they met the inclusion criteria. Participants were considered if the mother answered “yes” to the following questions: Has your child had physician-diagnosed asthma? Is your child currently taking asthma medications of asthma? Two community nurses conducted the interviews. Data was obtained using administrative questionnaires. Data were analyzed using SPSS version 21.0 (IBM Inc., Chicago, IL, USA). Descriptive statistics of percentage, mean, frequency and standard deviation were applied for categorical and continuous variables. Results Three hundred mothers participated in this study. Their average age was 36.8 years, 55% were housekeepers by profession, and 34% had obtained less than high school education. The majority of children (61%) were males, 45% had moderate asthma, and 42% had mild asthma. The most frequent types of barriers identified by parents were environmental factors (67.7%), followed by health care providers (63%),

关键词： Barriers to Asthma Care Mothers Children and Saudi Arabia

Representing the Knowledge of Public Construction Project Cost Estimator by Using Rule-Based Method

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Journal of Building Construction and Planning Research 2015年第4期3卷 189-195页

作者： Abelrahman Osman Elfaki Saleh alatawi University of Tabuk Tabuk KSA Binladen Research Chair of Quality and Productivity Improvement in the Construction Industry College of Engineering University of Hail Hail KSA

Despite the presence of various construction project cost estimate softwares, human experience and knowledge cannot be disregarded. This fact has been proven in practice, where the success of construction cost estimate process is mainly based on knowledge of human estimator. The main question concerns what human knowledge determines the success of the construction cost estimation process. To address this question we have applied Delphi technique and the output is eleven factors that are enough to precisely represent construction cost estimator knowledge. Then we have used First Order Logic (FOL) to represent these factors in terms of predicates and rules. These FOL rules could be used for evaluating construction cost estimator knowledge in five classes: fail, pass, acceptable, good, and very good. As a validation process we have done experiments using history data and the results have proved the accuracy of our proposed method.

关键词： Construction Management Construction Cost Estimation Rule-Based System

Aquatic Ecosystem and Biodiversity: A Review

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Open Journal of Ecology 2019年第1期9卷 1-13页

作者： Sufia Irfan Aishah Mohammed Motir alatawi Biology Department Faculty of Science College of Science University of Tabuk Tabuk KSA

Aquatic ecosystems support a substantial source of the earth’s biological diversity. They are an essential reservoir and share an enormous proportion of earth’s biological productivity. Both aquatic resources and its biodiversity are interrelated to each other and they perform a myriad of functions and are valuable and essential for the sustainability of biotic communities. Aquatic biodiversity in both freshwater and marine environments are under continuous decline because of overexploitation of species, introduced exotic plant or animal, pollution sources from cities, industries and agricultural zones, loss and changes in ecological niche. Their conservation and management in the form of bio reserve points and bioregional management and worldwide monitoring are needed for the protection of the aquatic biodiversity. This review is presenting information on biodiversity in aquatic habitats and their resources, in marine and fresh water ecosystems, their importance conservation and restoration mechanisms.

关键词： Aquatic Ecosystem Biodiversity Conservation Restoration

Investigating How Parental Perceptions of Cybersecurity Influence Children’s Safety in the Cyber World: A Case Study of Saudi Arabia

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Intelligent Information Management 2023年第5期15卷 350-372页

作者： Tariq Saeed Mian Eman M. alatawi Department of IS College of Computer Science and Engineering Taibah University Madinah Almunwarah Saudi Arabia

This paper explores the convergence of Saudi Arabia’s Vision 2030 with the increasing dependence on the Internet for educational purposes. It sheds light on the potential cybersecurity risks and how parental perception impacts children’s willingness to adapt cybersecurity features. By instilling the significance of cybersecurity awareness in early stages, society can provide children with the necessary skills to navigate the digital realm responsibly. As we progress, ongoing research and collaborative endeavors will be pivotal in formulating effective strategies to shield the digital generation from the potential pitfalls of the virtual realm. Regular Internet usage is essential for various purposes such as communication, education, and leisure. The cohorts of Generation Z and Alpha were born during a period of exponential Internet growth, leading them to heavily engage with the Internet. Consequently, they are equally vulnerable to cybersecurity threats just like adults. Addressing potential security risks for today’s youth becomes the responsibility of parents as the primary line of defense. This research focuses on raising awareness about the imperative of ensuring children’s safety in the online sphere, particularly by their parents. The study is conducted within the specific context of Saudi Arabia, aiming to examine how Saudi parents’ perception of cybersecurity influences their children’s cyber safety. The study identifies critical factors, including attitudes towards cybersecurity, awareness of cybersecurity, and prevailing social norms regarding cybersecurity. These factors contribute to the development of parents’ intention to prioritize cybersecurity, which consequently affects their children’s behaviors in the digital realm. Utilizing a quantitative approach based on a questionnaire, the study employs a Structural Equation Modeling (SEM) framework to analyze the collected data. The study’s findings underscore that parents’ intent towards cybersecurity pl

关键词： E-Learning Cybersecurity Saudi Arabia Saudi Vision 2030 Cybersecurity Awareness Parenting in Cyber Era Adolescence

1.05 Tb/s Optical-OFDM Using ROF over 3600 km

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Optics and Photonics Journal 2013年第5期3卷 318-323页

作者： Fahad Almasoudi Khaled alatawi Mohammad A. Matin Department of Electrical and Computer Engineering University of Denver Denver USA

In this paper, an effort is made to analyze the integration of direct detection optical orthogonal frequency division multiplexing (DDO-OFDM) with wavelength division multiplexing (WDM) to reach high data rates of 1.050 Tb/s over 3600 km single mode fiber (SMF). The 1.050 Tb/s signal is generated by multiplexing 30 OFDM signals with 35 Gb/s for each OFDM. The performance of the system is studied by measuring the optical signal to noise ratio (OSNR) of each WDM channel;signal to noise ratio (SNR);and bit error rate (BER);while analyzing the constellation diagram of all users. Also, the relationship between the OSNR and BER is studied and it is noticed that as the OSNR increased, the BER decreased. As can be seen form the results, as the transmission distance increased the BER increases and to keep the BER less than 10-3 we need to increase the OSNR.

关键词： BER O-OFDM DCF ICI ISI