ENHANCING INTRUSION DETECTION SYSTEMS (IDS) USING MACHINE LEARNING TECHNIQUES - A COMPARATIVE STUDY OF DEEP LEARNING AND CLASSICAL MACHINE LEARNING METHODS

Sep 17, 2026

Uploaded by Levi

Project configuration manual for an MSc Cybersecurity research work focused on enhancing an intrusion detection system (IDS) by building and reproducing models in a Jupyter Notebook environment. The manual specifies system and software requirements, including Python 3.10 on Windows, and lists key libraries such as NumPy, Pandas, scikit-learn, Matplotlib, and TensorFlow. It provides installation guidance via pip and references a Kaggle dataset for intrusion detection in wireless sensor networks to support the comparative study between deep learning and classical machine learning approaches.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages4

Reading Time10 min

AccessFree to download

System requirements

Software requirements

Configuration Manual MSc Research Project MSc Cybersecurity Chinedu Nelson Egwu x23258608 School of Computing National College of Ireland Supervisor: Michael Pantridge National College of Ireland MSc Project Submission Sheet School of Computing Student Chinedu Nelson Egwu Name: …….…………………………………………………………………………………………………………… X23258608 Student ID: ……………………………………………………………………………………………………………..…… MSc Cybersecurity 2025 Programme: ……………………………………………………………… Year: ………………………….. Module: Lecturer: Submission Due Date: Project Title: Research Project Michael Pantridge 29-01-2025 ENHANCING INTRUSION DETECTION SYSTEMS (IDS) USING MACHINE LEARNING TECHNIQUES: A COMPARATIVE STUDY OF DEEP LEARNING AND CLASSICAL MACHINE LEARNING METHODS FOR IMPROVED DETECTION ACCURACY AND SPEED 95 1 Word Count: ……………………………………… Page Count: ………………………………….…….……… I hereby certify that the information contained in this (my submission) is information pertaining to research I conducted for this project. All information other than my own contribution will be fully referenced and listed in the relevant bibliography section at the rear of the project. ALL internet material must be referenced in the bibliography section. Students are required to use the Referencing Standard specified in the report template. To use other author's written or electronic work is illegal (plagiarism) and may result in disciplinary action. Chinedu Nelson Egwu Signature: ……………………………………………………………………………………………………………… 29th January 2025 Date: ……………………………………………………………………………………………………………… PLEASE READ THE FOLLOWING INSTRUCTIONS AND CHECKLIST | Attach a completed copy of this sheet to each project (including multiple copies) | □ | | --- | --- | | Attach a Moodle submission receipt of the online project submission, to each project (including multiple copies) . | □ | | You must ensure that you retain a HARD COPY of the project, both for your own reference and in case a project is lost or mislaid. It is not sufficient to keep a copy on computer. | □ | Assignments that are submitted to the Programme Coordinator Office must be placed into the assignment box located outside the office. | Office Use Only | | | --- | --- | | Signature: | | | Date: | | | --- | --- | | Penalty Applied (if applicable): | | Configuration Manual Chinedu Nelson Egwu Student ID: x23258608 ENHANCING INTRUSION DETECTION SYSTEMS (IDS) USING MACHINE LEARNING TECHNIQUES: A COMPARATIVE STUDY OF DEEP LEARNING AND CLASSICAL MACHINE LEARNING METHODS FOR IMPROVED DETECTION ACCURACY AND SPEED This project involves building an intrusion detection system using a dataset obtained from kaggle. The manual provides configuration and setup instructions to replicate the project in Jupyter notebook 1.0. System requirements: Operating System: Windows OS Python Version: Python 3.10. 2.0. Software requirements - Jupyter Notebook - NumPy 1.21.0 - Pandas 1.3.0 - Scikit-learn 0.24.2 - Matplotlib 3.4.2 - TensorFlow 2.6.0 Installation command: pip install numpy pandas scikit-learn matplotlib tensorflow Reference WSN-DS: A dataset for intrusion detection systems in wireless sensor network: [ online ] Available: [https://www.kaggle.com/datasets/bassamkasasbeh1/wsnds/data](https://www.kaggle.com/datasets/bassamkasasbeh1/wsnds/data. Accessed on:18)[. Accessed on:18](https://www.kaggle.com/datasets/bassamkasasbeh1/wsnds/data. Accessed on:18)[ ](https://www.kaggle.com/datasets/bassamkasasbeh1/wsnds/data. Accessed on:18)[Oct 2024](Oct 2024) .

FAQs

What dataset is used to build the intrusion detection system?

The project uses a dataset obtained from Kaggle, referenced as WSN-DS: A dataset for intrusion detection systems in wireless sensor network.

Which software and libraries are required for the configuration?

The manual requires Jupyter Notebook and libraries including NumPy 1.21.0, Pandas 1.3.0, scikit-learn 0.24.2, Matplotlib 3.4.2, and TensorFlow 2.6.0.

What environment does the manual target for running the project?

The system requirements specify a Windows OS and Python 3.10, with the project configured to run in a Jupyter Notebook.

Sep 17, 2026

Uploaded by Levi