[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125363-en":3,"doc-seo-125363-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},125363,13056703019662,"Evangeline","https://ap-avatar.wpscdn.com/avatar/be000253a8e92610077?_k=1778726343310543188",8,"Research & Report","MACHINE LEARNING FOR NETWORK ANOMALY DETECTION - Thesis Master of Science","Network-connected Internet of Things (IoT) systems expand rapidly, enabling AIOT technologies that collect, process, and autonomously decide across IoT networks. Yet IoT networks face frequent disturbances and attacks, including fraud and intrusion-driven failures that degrade reliability. This thesis evaluates five machine learning classification algorithms—SVM, decision trees, random forests, artificial neural networks, and k-nearest neighbors—using open-source data from the Kugel dataset built with DS2OS, comparing anomaly/attack predictions via accuracy, recall, precision, and F1 score.","REPUBLIC OF TÜRKİYE ALTINBAŞ UNIVERSITY  \nInstitute of Graduate Studies  \nElectrical and Computer Engineering  \nMACHINE LEARNING FOR NETWORK  \nANOMALY DETECTION  \nRusul Tareq KHUDHAIR  \nMaster’s Thesis  \nSupervisor  \nAsst. Prof. Dr. Abdullahi Abdu IBRAHIM  \nIstanbul, 2023  \nMACHINE LEARNING FOR NETWORK ANOMALY DETECTION  \nRusul Tareq KHUDHAIR  \nElectrical and Computer Engineering  \nMaster’s Thesis  \nALTINBAŞ UNIVERSITY  \nThe thesis titled MACHINE LEARNING FOR NETWORK ANOMALY DETECTION prepared by RUSUL TAREQ KHUDHAIR and submitted on 00/04/2023 has been accepted unanimously for the degree of Master of Science in Electrical and Computer Engineering.  \nAsst. Prof. Dr. Abdullahi Abdu IBRAHIM  \nSupervisor  \nThesis Defense Committee Members:  \n[Asst. prof. Dr. Abdullahi Abdu IBRAHIM](Asst. prof. Dr. Abdullahi Abdu IBRAHIM)  \n[Asst. prof. Dr. Ay](Asst. prof. Dr. Ay)ça Kurnaz TÜRKBEN  \n[Asst. prof. Dr Tariq Mohammed](Asst. prof. Dr Tariq Mohammed)  \nDepartment of Computer Engineering,  \nAltınbaş university  \nDepartment of Software Engineering,  \nAltınbaş university  \nDepartment of Biomedical Engineering,  \n__________________  \n__________________  \nİstanbul Arel University  \n__________________  \nI hereby declare that this thesis meets all format and submission requirements ofa Master’s thesis.  \nSubmission date of the thesis to Institute of Graduate Studies:  / /   \nI hereby declare that all information/data presented in this graduation project has been obtained in full accordance with academic rules and ethical conduct. I also declare all unoriginal materials and conclusions have been cited in the text and all references mentioned in the Reference List have been cited in the text, and vice versa as required by the abovementioned rules and conduct.  \nRusul Tareq KHUDHAIR  \nSignature  \nDEDICATION  \nI would like to start by thanking God Almighty for giving me the knowledge, health, and stamina to finish my research, and I thank my supervisor Dr Abdullahi Abdu IBRAHIM for all the support during my academic career. I dedicate this letter to my parents. There are not enough words to express, and I cannot repay what they have done for me. I will continue to work hard to meet their expectations, and finally, I dedicate this to my close family members and friends who have supported me through this study.  \nABSTRACT  \nMACHINE LEARNING FOR NETWORK ANOMALY DETECTION  \nKHUDHAIR, Rusul Tareq  \nM.Sc., Electrical and Computer Engineering, Altınbaş University,  \nSupervisor: Asst. Prof. Dr. Abdullahi Abdu IBRAHIM  \nDate: April / 2023  \nPages: 60  \nIn previous years, the Internet of Things (IoT) developed rapidly from its wide application in many fields, and the use of Internet of Things devices recently, for example, in health, agriculture, industry, and so on. It devotes integrated attention to AI with the Internet of Things and defines Artificial Intelligence of Things (AIOT) technology that aims to collect, process, and make decisions autonomously and without human intervention in relation to IoT networks. Many problems occur in the Internet of Things networks, such as bank fraud, an increase in the number of attacks on Internet of Things networks, and other problems. The Internet of Things is the result of an increase in the number of attacks and distortions that hinder movement, and the failure of the IoT system. This study demonstrated the performance of five machine learning classification algorithms (support vector machine, decision trees, random forests, artificial neural network, and k-nearest neighbours) . It was measured based on a set of data taken from the open-source Kugel website, built using the Intelligent Space Distribution System DS2OS, and compared with the prediction of many anomalies and attacks on the network, then the performance evaluation measures were used, which are accuracy, recall, Precision, and f1 score. In the thesis, high performance was obtained with several algorithms, but one algorithm gave the support vector mach","cbCaiq2JfJAizBiH","https://ap.wps.com/l/cbCaiq2JfJAizBiH","pdf",1374029,1,65,"English","en",105,"# 1. INTRODUCTION\n## 1.1 GENERAL INFORMATION\n## 1.1.1 Internet of Things (IoT)\n## 1.1.2 Anomaly Detection\n## 1.1.3 Challenges and Possibilities of Anomaly Detection in the IOT\n## 1.1.4 Security for IOT Using Machine Learning\n## 1.1.5 Machine Learning Technologies\n## 1.1.6 Supervised Machine Lear","[{\"question\":\"What problem does the thesis address?\",\"answer\":\"The thesis addresses anomaly and attack issues in IoT networks, including disturbances that hinder reliable operation.\"},{\"question\":\"Which machine learning algorithms are evaluated?\",\"answer\":\"Support vector machine, decision trees, random forests, artificial neural networks, and k-nearest neighbors are tested for classification performance.\"},{\"question\":\"How is performance measured in the study?\",\"answer\":\"Performance is evaluated using accuracy, recall, precision, and F1 score, along with a confusion matrix for the best-performing method.\"}]","MACHINE LEARNING FOR NETWORK ANOMALY DETECTION - Thesis Master of Science | PDF",1785898426,164,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-for-network-anomaly-detection-master-of-science-thesis","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-for-network-anomaly-detection-master-of-science-thesis/125363/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What problem does the thesis address?","Question",{"text":75,"@type":76},"The thesis addresses anomaly and attack issues in IoT networks, including disturbances that hinder reliable operation.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which machine learning algorithms are evaluated?",{"text":80,"@type":76},"Support vector machine, decision trees, random forests, artificial neural networks, and k-nearest neighbors are tested for classification performance.",{"name":82,"@type":73,"acceptedAnswer":83},"How is performance measured in the study?",{"text":84,"@type":76},"Performance is evaluated using accuracy, recall, precision, and F1 score, along with a confusion matrix for the best-performing method.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]