[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-290383-105":3,"doc-detail-290383-en":81,"detail-sidebar-cat-0-en-105":99},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":74,"head_meta":76,"extra_data":78,"updated_unix":80},105,"en","using-machine-learning-algorithms-to-detect-phishing-attack-msc-research-project","Using Machine Learning Algorithms to Detect Phishing attack - MSc Research Project","","Cyberfraud, especially phishing attempts, poses a serious risk to corporate operations by both disrupting business activities and exposing valuable, critical information. This study focuses on identifying phishing without intruding on employees via harmful email attacks, proposing an intelligent machine-learning pipeline. Multiple machine learning and deep learning approaches are evaluated to determine effectiveness in detecting inappropriate behavior within greedy search-based pipeline network structures, supporting a response system adaptable across organizations and datasets while maintaining server security.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/using-machine-learning-algorithms-to-detect-phishing-attack-msc-research-project/290383/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/using-machine-learning-algorithms-to-detect-phishing-attack-msc-research-project/290383.png","ImageObject",300,407,{"name":42,"@type":43},"Eliana","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-29","2026-09-17",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",9,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What problem does the project aim to address?","Question",{"text":63,"@type":64},"The project targets cyberfraud caused by phishing attempts and seeks to reduce their impact on business operations and information security.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How does the proposed solution work?",{"text":68,"@type":64},"It proposes an intelligent machine-learning pipeline to detect phishing attempts, evaluating machine learning and deep learning models for their effectiveness.",{"name":70,"@type":61,"acceptedAnswer":71},"Why is two-factor authentication discussed in the introduction?",{"text":72,"@type":64},"The text explains that while 2FA is effective against phishing, organizations may still need additional measures, and machine learning can help recognize phishing behaviors and related threats.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},290383,1790175811,{"code":4,"msg":82,"data":83},"success",{"doc_id":79,"user_id":84,"nickname":42,"user_avatar":85,"doc_module":4,"category_id":86,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":87,"file_id":88,"file_url":89,"file_type":90,"file_size":91,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":92,"language":93,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":94,"faqs":95,"seo_title":96,"seo_description":12,"update_tm":97,"read_time":98,"preview_page_count":4},4398048949847,"https://ap-avatar.wpscdn.com/avatar/400002536579ef2da7f?_k=1778318612642679267",8,"Using Machine Learning Algorithms to Detect Phishing  \nattack  \nMSc Research Project  \nMSc Cybersecurity  \nShreyas Chandrakanth Kulkarni  \nStudent ID: X23173106  \nSchool of Computing  \nNational College of Ireland  \nSupervisor: Jawad Salahuddin  \nNational College of Ireland MSc Project  \nSubmission SheetSchool of Computing  \nStudent Name: Shreyas Chandrakanth Kulkarni  \nStudent ID: X23173106  \nProgramme: MSc In Cybersecurity Year: 2024  \nModule: MSc Research Practicum  \nSupervisor: Jawad Salahuddin  \nSubmission Due  \nDate: 12/08/2024  \nProject Title: Real-Time Detection of Social Engineering Threats in Social Media Posts.  \nWord Count: Page Count 26  \nI hereby certify that the information contained in this (my submission) is information about research I conducted for this project. All information other than my contribution will be fully referenced and listed in the relevant bibliography section at the rear of the project. 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.  \nSignature: Shreyas Chandrakanth Kulkarni  \nDate: 12/08/2024  \nPLEASE READ THE FOLLOWING INSTRUCTIONS AND CHECKLIST  \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 isnot sufficient to keep a copy on computer. | □ |\n\nAssignments that are submitted to the Programme Coordinator Office must be placedinto the assignment box located outside the office.  \n\n| Office Use Only |  |\n| --- | --- |\n| Signature: |  |\n| Date: |  |\n| Penalty Applied (if applicable): |  |\n\nUsing Machine Learning Algorithms to Detect Phishing  \nattack  \nAbstract  \nCyberfraud, particularly through phishing attempts, is a significant issue in corporate operations. This might impede business operations but also deprive valuable and critical information. This study's main objective is to address the issue of identifying phishing and not disturbing employees with these harmful email attacks. The proposal is to make an intelligent pipeline using machine learning to mitigate the case of phishing attacks. Various Machine Learning techniques including deep learning models, will be evaluated to determine their effectiveness in detecting inappropriate behavior in greedy search-based pipeline networks. Since machine learning has been identified as a crucial instrument in combating cybercrime, this response system can work agnostic to any organization and data to give a proper security service and maintain the server networks. These results further emphasize the significance of employing adaptable techniques to address emerging security challenges.  \nKeywords: DDoS attack, Phishing Email attacks, Machine Learning, Deep Learning, Response System  \nChapter 1: Introduction  \nPhishing is one of the social engineering attacks commonly used by hackers to obtain user information, such as login passwords and credit card data. Phishing refers to the deliberate act of tricking a target into accessing an email, instant message, or text message by assuming the identity of a reliable source. Afterwards, the receiver is deceived into clicking on a harmful hyperlink, which can install harmful software.  \nFigure 1: An example depicting the suspicious email link ([Source: www.impreva.com](Source: www.impreva.com))  \nPhishing is a fraudulent technique in which false communications are transmitted across the internet, usually in the form of emails or messages, to give the false impression that they come from reliable sources. The primary objective is to deceive the receivers into sending s","cbCaiiCXJq2g1p7R","https://ap.wps.com/l/cbCaiiCXJq2g1p7R","pdf",2329354,27,"English","# Abstract\n# Keywords\n# Chapter 1: Introduction\n## 1.1 Research Motivation\n## 1.2 Research Aim","[{\"question\":\"What problem does the project aim to address?\",\"answer\":\"The project targets cyberfraud caused by phishing attempts and seeks to reduce their impact on business operations and information security.\"},{\"question\":\"How does the proposed solution work?\",\"answer\":\"It proposes an intelligent machine-learning pipeline to detect phishing attempts, evaluating machine learning and deep learning models for their effectiveness.\"},{\"question\":\"Why is two-factor authentication discussed in the introduction?\",\"answer\":\"The text explains that while 2FA is effective against phishing, organizations may still need additional measures, and machine learning can help recognize phishing behaviors and related threats.\"}]","Using Machine Learning Algorithms to Detect Phishing attack - MSc Research Project | PDF",1789641534,68,{"code":4,"msg":82,"data":100},[101,105,109,113,118,123,128,131,135,138,142],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":103,"slug":104},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":106,"show_sort_weight":107,"slug":108},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":110,"show_sort_weight":111,"slug":112},"Exam",70,"exam",{"id":114,"doc_module":4,"doc_module_name":25,"category_name":115,"show_sort_weight":116,"slug":117},5,"Comic",60,"comic",{"id":119,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":121,"slug":122},6,"Technology",50,"technology",{"id":124,"doc_module":4,"doc_module_name":25,"category_name":125,"show_sort_weight":126,"slug":127},7,"Healthcare",40,"healthcare",{"id":86,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":129,"slug":130},30,"research-report",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":132,"show_sort_weight":133,"slug":134},"Religion & Spirituality",20,"religion-spirituality",{"id":133,"doc_module":4,"doc_module_name":25,"category_name":136,"show_sort_weight":133,"slug":137},"World Cup","world-cup",{"id":139,"doc_module":4,"doc_module_name":25,"category_name":140,"show_sort_weight":139,"slug":141},10,"Lifestyle","lifestyle",{"id":143,"doc_module":4,"doc_module_name":25,"category_name":144,"show_sort_weight":114,"slug":145},19,"General","general"]