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All Journal Bulletin of Electrical Engineering and Informatics
Mohammed, Mostafa Abdulghafoor
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Electrical & Electronics Engineering

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Distributed denial of service attack defense system-based auto machine learning algorithm Aljanabi, Mohammad; Hayder, Russul; Talib, Shatha; Hussien Ali, Ahmed; Mohammed, Mostafa Abdulghafoor; Sutikno, Tole
Bulletin of Electrical Engineering and Informatics Vol 12, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i1.4537

Abstract

The use of network-connected gadgets is rising quickly in the internet age, which is escalating the number of cyberattacks. The detection of distributed denial of service (DDoS) attacks is a tedious task that has necessitated the development of a number of models for its identification recently. Nonetheless, because of major fluctuations in subscriptions and traffic rates, it continues to be a difficult challenge. A novel automatic detection technique was created to address this issue in this work, which reduces the feature space and consequently minimizes the computational time and model overfitting. Data preprocessing is done first to increase the model's generalizability; then, a feature selection method is used to choose the most pertinent features to increase the accuracy of the classification process. Additionally, hyperparameter tuning-choosing the proper parameters for the learning approach-improved model performance. Finally, the support vector machine (SVM) is compatible with the optimization and the hyperparameters offered by supervised learning methods. The CICDDoS2019 dataset was used to evaluate each of these assays, and the experimental findings demonstrated that, with an accuracy of 99.95%, the suggested model performs well when compared to more modern techniques.
The effectiveness of big data classification control based on principal component analysis Mohammed, Mostafa Abdulghafoor; Akawee, Mostafa Mahmood; Saleh, Ziyad Hussien; Hasan, Raed Abdulkareem; Ali, Ahmed Hussein; Sutikno, Tole
Bulletin of Electrical Engineering and Informatics Vol 12, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i1.4405

Abstract

Large-scale datasets are becoming more common, yet they can be challenging to understand and interpret. When dealing with big datasets, principal component analysis (PCA) is used to minimize the dimensionality of the data while maintaining interpretability and avoiding information loss. It accomplishes this by producing new uncorrelated variables that gradually reduce the variance of the system. In the field of data analysis, PCA is a multivariate statistical technique commonly used to obtain rules explaining the separation of groups in a given situation. Classes are predicted using a classification algorithm, a supervised learning technique that indicates which type of data points will be presented. Creating a classification model using classification algorithms is required before any successful classification can be achieved. It is possible to predict the future using a variety of categorized strategies. It is necessary to reduce the dimensionality of data sets using the PCA approach. This article will begin by introducing the basic ideas of PCA and discussing what it can and cannot do. It will then describe some variants of PCA and their application and then shows how PCA improves the performance using a series of experiments.
A proposed software for controlling operating system-dependent functionality Abdulameer Alazawi, Sundos; Mahmood Hussien, Nadia; Makki Mohialden, Yasmin; Mohammed, Mostafa Abdulghafoor
Bulletin of Electrical Engineering and Informatics Vol 12, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i1.4536

Abstract

When the operating system environment temperature rises above safety, the CPU may become unresponsive or even malfunction. To address this problem, to achieve this goal a two-part system was designed. The first, consists of a controlled sensor that constantly monitors the room environment temperature and alerts the user if it rises above acceptable levels for computer use. The second part adopts a Python that uses the OS module, which provides a portable interface for OS-dependent tasks and shuts down the device to prevent it from behaving unexpectedly. A series of experiments at different temperatures demonstrated the ability of the device to alert the user.
The software requirements process for designing a microcontroller-based voice-controlled system Hussien, Nadia Mahmood; Mohialden, Yasmin Makki; Akawee, Mustafa Mahmood; Mohammed, Mostafa Abdulghafoor
Bulletin of Electrical Engineering and Informatics Vol 12, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i1.4407

Abstract

Smartphones of today are capable of controlling motors, music systems, and lighting. This project's objective is to construct a robot car for the elderly and disabled that is based on the Arduino platform. Voice instructions can be used to wirelessly control the robotic car that the user is riding. The robot is able to move to the left and right, as well as forward and backward, and it can also stop. The voice-controlled robot vehicle built using Arduino and operated by an HC-05 module is connected to Bluetooth. The exact spoken commands are sent to the robot through the phone via an application that runs on android. The Arduino, which is in charge of controlling the robotic automobile, gets commands through a Bluetooth transceiver module, which then relays them to the Arduino. The hardware consists of an android phone, an android-powered motor drive, an Arduino, and Bluetooth. This system was developed with the help of Arduino C and the android-meets-robot framework. The primary goals of this piece of writing are to gain an understanding of how to create the criteria for a voice-controlled system that is based on Arduino.
Co-Authors Abdulameer Alazawi, Sundos Akawee, Mostafa Mahmood Akawee, Mustafa Mahmood Ali, Ahmed Hussein Aljanabi, Mohammad Hasan, Raed Abdulkareem Hayder, Russul Hussien Ali, Ahmed Hussien, Nadia Mahmood Mahmood Hussien, Nadia Makki Mohialden, Yasmin Mohialden, Yasmin Makki Saleh, Ziyad Hussien Talib, Shatha Tole Sutikno