[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-290704-105":59,"doc-detail-290704-en":131},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","enhancing-intrusion-detection-systems-ids-using-machine-learning-techniques-a-comparative-study-of-deep-learning-and-classical-machine-learning-methods","ENHANCING INTRUSION DETECTION SYSTEMS (IDS) USING MACHINE LEARNING TECHNIQUES - A COMPARATIVE STUDY OF DEEP LEARNING AND CLASSICAL MACHINE LEARNING METHODS","","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.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/enhancing-intrusion-detection-systems-ids-using-machine-learning-techniques-a-comparative-study-of-deep-learning-and-classical-machine-learning-methods/290704/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/enhancing-intrusion-detection-systems-ids-using-machine-learning-techniques-a-comparative-study-of-deep-learning-and-classical-machine-learning-methods/290704.png","ImageObject",300,407,{"name":92,"@type":93},"Levi","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",15,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What dataset is used to build the intrusion detection system?","Question",{"text":113,"@type":114},"The project uses a dataset obtained from Kaggle, referenced as WSN-DS: A dataset for intrusion detection systems in wireless sensor network.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"Which software and libraries are required for the configuration?",{"text":118,"@type":114},"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.",{"name":120,"@type":111,"acceptedAnswer":121},"What environment does the manual target for running the project?",{"text":122,"@type":114},"The system requirements specify a Windows OS and Python 3.10, with the project configured to run in a Jupyter Notebook.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},290704,1789642399,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":19,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":130,"read_time":52,"preview_page_count":4},7971461740909,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Configuration Manual  \nMSc Research Project MSc Cybersecurity  \nChinedu Nelson Egwu  \nx23258608  \nSchool of Computing National College of Ireland  \nSupervisor: Michael Pantridge  \nNational College of Ireland MSc Project Submission Sheet School of Computing  \nStudent Chinedu Nelson Egwu Name: …….……………………………………………………………………………………………………………  \nX23258608  \nStudent ID: ……………………………………………………………………………………………………………..……  \nMSc Cybersecurity 2025  \nProgramme: ……………………………………………………………… Year: …………………………..  \nModule:  \nLecturer: Submission Due Date:  \nProject Title:  \nResearch Project  \nMichael Pantridge  \n29-01-2025  \nENHANCING 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  \n95 1  \nWord Count: ……………………………………… Page Count: ………………………………….…….………  \nI 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.  \nALL 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.  \nChinedu Nelson Egwu  \nSignature: ………………………………………………………………………………………………………………  \n29th January 2025  \nDate: ………………………………………………………………………………………………………………  \nPLEASE READ THE FOLLOWING INSTRUCTIONS AND CHECKLIST  \n\n| Attach a completed copy of this sheet to each project (including multiple copies) | □ |\n| --- | --- |\n| Attach a Moodle submission receipt of the online project submission, to each project (including multiple copies) . | □ |\n| 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. | □ |\n\nAssignments that are submitted to the Programme Coordinator Office must be placed into the assignment box located outside the office.  \n\n| Office Use Only |  |\n| --- | --- |\n| Signature: |  |\n\n\n| Date: |  |\n| --- | --- |\n| Penalty Applied (if applicable): |  |\n\nConfiguration Manual  \nChinedu Nelson Egwu  \nStudent ID: x23258608  \nENHANCING 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  \nThis 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  \n1.0. System requirements: Operating System: Windows OS Python Version: Python 3.10.  \n2.0. Software requirements  \n- Jupyter Notebook  \n- NumPy 1.21.0  \n- Pandas 1.3.0  \n- Scikit-learn 0.24.2  \n- Matplotlib 3.4.2  \n- TensorFlow 2.6.0  \nInstallation command: pip install numpy pandas scikit-learn matplotlib tensorflow  \nReference  \nWSN-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) .","cbCaidHvXT1niW0C","https://ap.wps.com/l/cbCaidHvXT1niW0C","pdf",386337,"English","# System requirements\n## Software requirements","[{\"question\":\"What dataset is used to build the intrusion detection system?\",\"answer\":\"The project uses a dataset obtained from Kaggle, referenced as WSN-DS: A dataset for intrusion detection systems in wireless sensor network.\"},{\"question\":\"Which software and libraries are required for the configuration?\",\"answer\":\"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.\"},{\"question\":\"What environment does the manual target for running the project?\",\"answer\":\"The system requirements specify a Windows OS and Python 3.10, with the project configured to run in a Jupyter Notebook.\"}]","ENHANCING INTRUSION DETECTION SYSTEMS (IDS) USING MACHINE LEARNING TECHNIQUES - A COMPARATIVE STUDY OF DEEP LEARNING AND CLASSICAL MACHINE LEARNING METHODS | PDF"]