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Iraqi Journal for Computer Science and Mathematics 2024年第3期5卷 45-91页

作者： Ali, Guma Mijwil, Maad M. Buruga, Bosco Apparatus Abotaleb, Mostafa Muni University Arua00256 Uganda Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of Library and Information Services Muni University Arua00256 Uganda Department of System Programming South Ural State University Chelyabinsk Russia

The fourth industrial revolution has seen the evolution and wide adoption of game-changing and disruptive innovation "financial technologies (FinTech)" around the globe. However, the security of FinTech systems and networks remains critical. This paper comprehensively reviews the evolving landscape of cybersecurity issues within the FinTech sector and explores effective mitigation measures. Four independent researchers reviewed relevant literature from IEEE Xplore Digital Library, ScienceDirect, Taylor & Francis, Emerald Insight, Springer, SAGE, Wiley Online Library, Hindawi, MDPI, ACM Digital Library, IGI Global, and Google Scholar. The research paper begins by examining the history and evolution of FinTech, drivers for the growth of FinTech, segments of the FinTech industry, FinTech ecosystem, FinTech business model, and FinTech application. Subsequently, it then delves into an analysis of the most pressing cybersecurity issues confronting FinTech firms, such as privacy concerns, data breaches, malware attacks, hacking, insider threats, identity theft, social engineering attacks, distributed denial-of-service attacks, and others. In response to these cybersecurity issues, the paper evaluates various mitigation strategies and best practices adopted by FinTech firms and regulatory bodies globally. These measures include technological solutions such as authentication and access control mechanisms, cryptography, big data analytics, intrusion detection/prevention systems, regular data backup, artificial intelligence and machine learning, cloud computing technologies, blockchain technologies, and fraud detection and prevention systems. The paper also emphasizes the importance of FinTech regulatory sandboxes, regulatory compliance, basic security training, continuous monitoring of threats, zero-trust policy, robust cybersecurity culture, regular testing, and stringent security policies to strengthen the FinTech ecosystem's cyber resilience. Based on empirical research, i

关键词： Denial-of-service attack

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Computer-oriented Training of Pre-retirement Aged Specialists within the Framework of the National Project 'Senior Generation' 3

Computer-oriented Training of Pre-retirement Aged Specialist...

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3rd International Conference on Technology Enhanced Learning in Higher Education, TELE 2023

作者： Filippova, Evgeniya Rybanov, Alexander Abramova, Oksana Sviridova, Olga Ict Volgograd State Socio- Pedagogical University The Department of Methods of Teaching Mathematics and Physics Volgograd Russia Volzhsky Polytechnic Institute Branch of the Volgograd State Technical University Informatics and Programming Techniques Department Volzhsky Russia

ISBN: (纸本)9798350326567

The article discusses the issue of developing computer literacy among pre-retirement aged specialists. The problem of training and retraining citizens of pre-retirement age is noted. The scientific novelty lies in describing current approaches to educating older citizens, which differ significantly from those used for younger people, and in developing an additional professional retraining program called 'Computer Operator' specifically designed for pre-retirement aged specialists. © 2023 IEEE.

关键词： Demography

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Deploying a web service application on the EdgeX open edge server: An evaluation of its viability for IoT services 2

Deploying a web service application on the EdgeX open edge s...

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2nd International Conference on Machine Learning and Data Engineering, ICMLDE 2023

作者： Dhulfiqar, Aalwahab Abdala, Mohammed A. Pataki, Norbert Tejfel, Máté Department of Programming Languages and Compilers Faculty of Informatics Eötvös Loránd University 1/C Pázmány Péter st. BudapestH-1117 Hungary AL-Hussain University College Department of Medical Instrumentation Techniques Engineering Karbala Iraq

With the advent of 5G and the promise of 6G, edge computing is becoming increasingly important. Edge computing involves the proximity of computational resources to the devices and sensors responsible for data generation, reducing delay and improving real time data processing capabilities. EdgeX is an openly available framework designed for edge computing. that provides a platform for building IoT services and applications. In this paper, we evaluate the EdgeX open edge server for use in IoT services. We first deploy a web service application into the edge using a specific port, and then test the EdgeX server to see whether it can be used as a reliable and effective open-source edge server. Our results show that the EdgeX server is capable of supporting IoT services and can be used as an open-source edge server for a variety of applications. We conclude that EdgeX is a valuable resource for developing edge computing solutions, and that the open edge server can significantly contribute to the advancement of forthcoming IoT service innovations. © 2024 Elsevier B.V.. All rights reserved.

关键词： Edge computing

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Informatics Leveling Training Methodical System Development for the First-year Students of a Technical University 4

Informatics Leveling Training Methodical System Development ...

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4th International Conference on Technology Enhanced Learning in Higher Education, TELE 2024

作者： Filippova, Evgeniya Shemyakina, Svetlana Rybanov, Alexander Sviridova, Olga ICT Volgograd State Socio- Pedagogical University The Department of Methods of Teaching Mathematics and Physics Volgograd Russia Volgograd State Medical University The Department of Methods of Teaching Mathematics and Physics ICT Volgograd State Socio- Pedagogical University The Department of Physics Mathematics and Informatics Volgograd Russia Volzhsky Polytechnic Institute Branch of the Volgograd State Technical University Informatics and Programming Techniques Department Volzhsky Russia

ISBN: (纸本)9798350353532

The article presents a leveling training methodical system development of students' knowledge, skills and abilities to use the information technologies due to their different pre- university training, explains the authors' idea of leveling training methodical system development at example of teaching the first-year students to computer science. Suggested methodical system permits to determine the goals, content, forms, methods and means of training taken into account the profile of technical specialties such as 'Construction', 'Operation of transport and transport-technological mechanisms and complexes' and 'Software Engineering'. Features and specifics of educational material on computer science using information technologies are described due to the profile of different areas of technical specialists' training. © 2024 IEEE.

关键词： Students

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Sensing Metric-Based Hybrid Underlay/Overlay Transmission Framework for CR-IoT Networks for Smart City Applications 7

Sensing Metric-Based Hybrid Underlay/Overlay Transmission Fr...

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7th IET Smart Cities Symposium, SCS 2023

作者： Bala, Indu Mijwil, Maad M. Abotaleb, Mostafa El-Kenawy, El-Sayed M. Ibrahim, Abdelhameed School of Electrical and Electronics Engineering Lovely Professional University Punjab India Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

With the increasing number of IoT devices, there is a growing need for bandwidth to support their communication. Unfortunately, there is a shortage of available bandwidth due to preallocated bands for various services. To address this issue, Cognitive Internet of Things (CR-IoT) enables devices to optimize their efficiency and enhance their communication capabilities by intelligently accessing available bandwidth. This is achieved through the use of soft sensing metrics, where devices continuously monitor the RF environment and transmit data opportunistically in overlay mode if a free channel is detected, or in underlay mode if not. In this paper, a soft sensing metric based hybrid transmission framework is proposed for CR-IoT devices to meet the data rate requirement for the smart city applications. The efficacy of this approach is demonstrated through simulation results. © The Institution of Engineering & Technology 2023.

关键词： Smart city

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Optimizing Machine Learning Algorithms to Enhance Blood Donation for Liver Patients: A Case Study 7

Optimizing Machine Learning Algorithms to Enhance Blood Dona...

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7th IET Smart Cities Symposium, SCS 2023

作者： Mijwil, Maad M. El-Kenawy, El-Sayed M. Bala, Indu Aljanabi, Mohammad Abotaleb, Mostafa Ibrahim, Abdelhameed Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt School of Electrical and Electronics Engineering Lovely Professional University Punjab India Department of Computer Aliraqia University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Blood is vital for transporting oxygen, nutrients, and hormones to all body parts as it circulates through arteries and veins. It removes carbon dioxide, regulates body temperature, and maintains the body's immune system. Individuals constantly need blood and its derivatives to save their lives and improve their health through medical treatments and surgical operations. Liver diseases are one of the diseases that affects the health of individuals and requires blood to continue living. These diseases cause significant damage to people's health, and early diagnosis plays a crucial role in saving lives. In this paper, machine learning algorithms (support vector machine and random forest) are involved in detecting liver diseases and determining whether donors are suitable to donate blood from blood values. This paper is applied research that found that the performance measures of the random forest algorithm achieved excellent performance in identifying suitable people to donate blood. © The Institution of Engineering & Technology 2023.

关键词： Support vector machines

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Deploying a web service application on the EdgeX open edge server: An evaluation of its viability for IoT services

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Procedia Computer Science 2024年 235卷 852-862页

作者： Aalwahab Dhulfiqar Mohammed A. Abdala Norbert Pataki Máté Tejfel Department of Programming Languages and Compilers Faculty of Informatics Eötvös Loránd University 1/C Pázmány Péter st. Budapest H-1117 Hungary AL-Hussain University College Department of Medical Instrumentation Techniques Engineering Karbala Iraq

关键词： Microservices Edge-computing EdgeX server APIs Edge devices Sensor data

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AbotalebNet: A Novel Deep Learning Architecture for Time Series Forecasting with Convolutional and LSTM Layers Enhanced by Multi-Head Attention 2

AbotalebNet: A Novel Deep Learning Architecture for Time Ser...

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2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Abotaleb, Mostafa Makarovskikh, Tatiana Mijwil, Maad M. Bala, Indu Hiran, Kamal Kant Doshi, Ruchi South Ural State University Dep. of System Programming Chelyabinsk454080 Russia Baghdad College of Economic Sciences University Computer Techniques Engineering Department Baghdad Iraq Lovely Professional University Electrical and Electronics Engineering Punjab India Sir Padampat Singhania University Dep. of Computer Science Udaipur India Universidad Azteca Dep. of Computer Science and Engineering Chalco Mexico

ISBN: (纸本)9798350384277

This paper introduces AbotalebNet, a novel deep learning architecture optimized for time series forecasting, with a particular focus on the complexities of COVID-19 data. AbotalebNet's architecture is mathematically represented as:\begin{equation*}\hat Y = {\text{Attention}}(\operatorname{LSTM} ({\text{CNN}}(X)))\tag{1}\end{equation*}Here, X represents the input time series data, and Ŷ is the forecasted output. AbotalebNet integrates the feature extraction capabilities of Convolutional Neural Networks (CNNs) with the sequential data processing power of Long Short-Term Memory (LSTM) networks, further enhanced by a Multi-Head Attention *** address overfitting, a key challenge in deep learning, the model incorporates regularization strategies, dropout mechanisms, and batch normalization:\begin{equation*}\mathop {\min }\limits_\Theta ( Loss (X,\hat Y;\Theta ) + \lambda R(\Theta ))\tag{2}\end{equation*}In this equation, Θ denotes the model parameters, R(Θ) represents regularization terms, and λ is the regularization coefficient. These additions aid in preventing the model from overfitting to the training data, ensuring robust performance on unseen *** evaluation on COVID-19 time series data demonstrates AbotalebNet's enhanced predictive accuracy over traditional models, solidifying its potential for advanced non-linear time series analysis. © 2024 IEEE.

关键词： Convolutional neural networks

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Data Poisoning: Issues, Challenges, and Needs 7

Data Poisoning: Issues, Challenges, and Needs

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7th IET Smart Cities Symposium, SCS 2023

作者： Aljanabi, Mohammad Omran, Alaa Hamza Mijwil, Maad M. Abotaleb, Mostafa El-Kenawy, El-Sayed M. Mohammed, Sahar Yousif Ibrahim, Abdelhameed Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Science Department Computer Science &Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence. © The Institution of Engineering & Technology 2023.

关键词： Machine learning

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Computer-oriented Training of Pre-retirement Aged Specialists within the Framework of the National Project “Senior Generation”

Computer-oriented Training of Pre-retirement Aged Specialist...

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Technology Enhanced Learning in Higher Education (TELE), International Conference on

作者： Evgeniya Filippova Alexander Rybanov Oksana Abramova Olga Sviridova The Department of Methods of Teaching Mathematics and Physics ICT Volgograd State Socio- Pedagogical University Volgograd Russia Informatics and Programming Techniques Department Volzhsky Polytechnic Institute Branch of the Volgograd State Technical University Volzhsky Russia

The article discusses the issue of developing computer literacy among pre-retirement aged specialists. The problem of training and retraining citizens of pre-retirement age is noted. The scientific novelty lies in describing current approaches to educating older citizens, which differ significantly from those used for younger people, and in developing an additional professional retraining program called “Computer Operator” specifically designed for pre-retirement aged specialists.

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