[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122218-en":3,"doc-seo-122218-105":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":20,"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},122218,13056703019404,"Miles","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","Enhancing Security in 5G Edge Networks - Predicting Real-Time Zero Trust Attacks Using Machine Learning in SDN Environments","The Internet faces persistent threats including spoofing, viruses, malicious code, and Distributed Denial of Service (DDoS). Reported attack trends emphasize viruses as well as DoS and DDoS, while advanced variants exceed the detection capacity of traditional defenses such as intrusion detection systems and firewalls. This study integrates machine learning-driven detection with an SDN testbed, using Mininet and the POX controller to simulate real-time conditions and applying the CICDDoS2019 dataset to classify attacks. Pre-trained models analyze collected traffic and predict intrusions in real time, evaluated via accuracy and detection time.","Article  \nEnhancing Security in 5G Edge Networks: Predicting Real-Time Zero Trust Attacks Using Machine Learning in  \nSDN Environments  \nFiza Ashfaq 1, Muhammad Wasim 1, Mumtaz Ali Shah 2, Abdul Ahad 3,4, * and Ivan Miguel Pires 5, *  \nAcademic Editor: Nikolaos Pitropakis  \nReceived: 1 February 2025  \nRevised: 27 February 2025  \nAccepted: 14 March 2025  \nPublished: 19 March 2025  \nCitation: Ashfaq, F.; Wasim, M.; Shah, M.A.; Ahad, A.; Pires, I.M. Enhancing Security in 5G Edge Networks: Predicting Real-Time Zero Trust Attacks Using Machine Learning inSDN Environments. Sensors 2025, 25, 1905. [https://](https://)[ ](https://)[doi.org/10.3390/s25061905](doi.org/10.3390/s25061905)  \n[Copyright:](Copyright:) © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://creativecommons.org/](https://creativecommons.org/)[ ](https://creativecommons.org/)[licenses/by/4.0/](licenses/by/4.0/)) .  \n1 Department of Computer Science, UMT Sialkot Campus, KUST, Sialkot 51040, Pakistan;  \nfi[za.muhammadashfaq03@gmail.com](za.muhammadashfaq03@gmail.com) (F.A.); [muhammad-wasim@skt.umt.edu.pk](muhammad-wasim@skt.umt.edu.pk) (M.W.)  \n2 Department of Computer Science, University of Wah, Wah Cantt 47040, Pakistan; [dr.mumtaz.shah@uow.edu.pk](dr.mumtaz.shah@uow.edu.pk)  \n3 School of Software, Northwestern Polytechnical University, Xi'an 710072, China  \n4 Department of Electronics and Communication Engineering, Istanbul Technical University (ITU), Maslak, Istanbul 34469, Turkey  \n5 Instituto de Telecomunicações, Escola Superior de Tecnologia e Gestão de Águeda, Universidade de Aveiro, 3810-193 Águeda, Portugal  \n* Correspondence: [ahad9388@gmail.com](ahad9388@gmail.com) (A.A.); [impires@ua.pt](impires@ua.pt) (I.M.P.)  \nAbstract: The Internet has been vulnerable to several attacks as it has expanded, including spoofing, viruses, malicious code attacks, and Distributed Denial of Service (DDoS) . The three main types of attacks most frequently reported in the current period are viruses, DoS attacks, and DDoS attacks. Advanced DDoS and DoS attacks are too complex for traditional security solutions, such as intrusion detection systems and firewalls, to detect. The combination of machine learning methods with AI-based machine learning has led to the introduction of several novel attack detection systems. Due to their remarkable performance, machine learning models, in particular, have been essential in identifying DDoS attacks. However, there is a considerable gap in the work on real-time detection of such attacks. This study uses Mininet with the POX Controller to simulate an environment to detect DDoS attacks in real-time settings. The CICDDoS2019 dataset identifies and classifies such attacks in the simulated environment. In addition, a virtual software-defined network (SDN) is used to collect network information from the surrounding area. When an attack occurs, the pre-trained models are used to analyze the traffic and predict the attack in real-time. The performance of the proposed methodology is evaluated based on two metrics: accuracy and detection time. The results reveal that the proposed model achievesan accuracy of 99% within 1 s of the detection time.  \nKeywords: cyber security; SDN; machine learning; zero trust; real-time; intrusion detection; intrusion prevention  \n1. Introduction  \nThe development of 5G technology has completely changed communication systems. Faster and more reliable connectivity opens up a world of high-capacity applications atthe network edge. However, with this paradigm comes a broad attack on the surface, raising security as a significant challenge. Complex networks may now be controlled and protected with the help of a Software-Defined Network (SDN) [1] . SDNs allow for more centralized management and enhance visibility by separating the control plane from the data plane. The researcher [2]","cbCaiePrLtrEbCt3","https://ap.wps.com/l/cbCaiePrLtrEbCt3","pdf",1980945,1,29,"English","en",105,"# Introduction\n## SDN and 5G Security Context\n## Common SDN Controllers (RYU, ONOS, Floodlight, POX)\n## Proposed Real-Time Detection Approach\n## Evaluation Metrics and Results","[{\"question\":\"What security problem does the study address in 5G edge networks?\",\"answer\":\"It addresses the difficulty of detecting advanced DoS and DDoS attacks that traditional security mechanisms struggle to identify, especially under real-time requirements at the network edge.\"},{\"question\":\"How is the real-time attack prediction environment implemented?\",\"answer\":\"The study simulates the environment using Mininet with the POX controller and uses SDN-based collection of network information for analysis.\"},{\"question\":\"Which dataset and evaluation metrics are used to assess performance?\",\"answer\":\"The CICDDoS2019 dataset is used to identify and classify attacks in the simulated environment, and performance is evaluated using accuracy and detection time.\"}]","Enhancing Security in 5G Edge Networks - Predicting Real-Time Zero Trust Attacks Using Machine Learning in SDN Environments | PDF",1785809433,73,{"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},"enhancing-security-in-5g-edge-networks-predicting-real-time-zero-trust-attacks-using-machine-learning-in-sdn-environments","",{"@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/enhancing-security-in-5g-edge-networks-predicting-real-time-zero-trust-attacks-using-machine-learning-in-sdn-environments/122218/",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","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What security problem does the study address in 5G edge networks?","Question",{"text":75,"@type":76},"It addresses the difficulty of detecting advanced DoS and DDoS attacks that traditional security mechanisms struggle to identify, especially under real-time requirements at the network edge.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How is the real-time attack prediction environment implemented?",{"text":80,"@type":76},"The study simulates the environment using Mininet with the POX controller and uses SDN-based collection of network information for analysis.",{"name":82,"@type":73,"acceptedAnswer":83},"Which dataset and evaluation metrics are used to assess performance?",{"text":84,"@type":76},"The CICDDoS2019 dataset is used to identify and classify attacks in the simulated environment, and performance is evaluated using accuracy and detection time.","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"]