[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121889-en":3,"doc-seo-121889-105":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},121889,4398048949847,"Eliana","https://ap-avatar.wpscdn.com/avatar/400002536579ef2da7f?_k=1778318612642679267",8,"Research & Report","Securing smart cities through machine learning - A honeypot-driven approach to attack detection in Internet of Things ecosystems","The rapid growth and adoption of Internet of Things (IoT) devices bring major convenience, while simultaneously enabling large-scale cyberattacks on systems that are often exposed and poorly defended. Smart cities, built on interconnected sensors, expand the attack surface and increase exposure of critical infrastructure and personal data. Conventional defenses struggle against attacker sophistication. This research uses honeypot data combined with machine learning to improve IoT threat detection by selecting suitable honeypot datasets, evaluating models for attack detection, and proposing security solutions based on analyzed real-world datasets.","Received: 2 January 2024 - Revised: 5 April 2024 - Accepted: 2 May 2024 - IET Smart Cities  \nDOI: 10. 1049/smc2 .12084  \nORIGINAL RESEARCH  \nSecuring smart cities through machine learning: A honeypot‐ driven approach to attack detection in Internet of Things ecosystems  \nYussuf Ahmed  | Kehinde Beyioku | Mehdi Yousefi  \nCollege of Computing, Birmingham City University, Birmingham, UK  \nCorrespondence  \nYussuf Ahmed, College of Computing, Birmingham City University, Steam House, Birmingham B4 7RQ, UK.  \n[Email: Yussuf.Ahmed@bcu.ac.uk](Email: Yussuf.Ahmed@bcu.ac.uk)  \nFunding information  \nBirmingham City University  \nAbstract  \nThe rapid increase and adoption of Internet of Things (IoT) devices have introduced unprecedented conveniences into modern life. However, this growth has also ushered in a wave of cyberattacks targeting these often‐vulnerable systems. Smart cities, relying on interconnected sensors, are particularly susceptible to attacks due to the expanded entry points created by these devices. A security breach in such systems can compromise personal data and disrupt entire ecosystems. Traditional security measures are inadequate against the evolving sophistication of cyberattacks. The authors aim to address these challenges by leveraging honeypot data and machine learning to enhance IoT security. The research focuses on three objectives: identifying datasets from IoT‐targeted honeypots, evaluating machine learning algorithms for threat detection, and proposing comprehensive security solutions. Real‐world cyber‐attack datasets from diverse honeypots simulating IoT devices are analysed using various machine learning and neural network algorithms. Results demonstrate significant improvement in cyber‐attack detection and mitigation when integrating honeypot data into IoT security frameworks. The authors advance knowledge and provides practical insights for implementing robust security measures in diverse IoT applications, filling a crucial research gap.  \nKEYW ORDS  \nartificial intelligence, computer network security, data analytics and machine learning, data structures, information security and privacy, IoT and mobile communications, networks and telematics, smart cities  \n1 | INTRODUCTION  \nInternet of Things (IoT) can be defined in many ways, but it simply refers to the connectivity of everything around us (watches, cars, houses, cities, etc.) to the internet with some level of intelligence available to these things [1] . It is a term for basic internet technologies that link low‐power gadgets such as sensors and actuators (things), and it involves both specialised technology and millions of devices. In comparison to a few years ago, the IoT technology has significantly influenced the daily lives of many people, and this is because of its broad adoption not just by businesses but also by individuals. The adoption rate is exponential, and according to a report [2], it is predicted there will be 29.42 billion linked gadgets by 2030,  \nrepresenting a growth of almost double the installed base of IoT in 2020.  \nThe proliferation ofIoT usage in ecosystems such as Smart Cities brings numerous advantages. However, it also introduces significant concerns and challenges, including susceptibility to cyberattacks, compromising user privacy, and device hijacking, among others. In a Smart City setup, the infrastructure heavily relies on network connectivity to gather crucial data from sensors, some of which are linked to critical safety systems [3] . Hackers exploit this connectivity and the multitude of sensors to gain unauthorised access, raising concerns about various vulnerabilities inherent in Smart City features. Components such as smart streetlights and traffic systems are prime targets for threat actors, often utilised in Denial of Service (DoS)  \nThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original ","cbCaisYwg0HRIb9e","https://ap.wps.com/l/cbCaisYwg0HRIb9e","pdf",1584851,1,19,"English","en",105,"# Introduction\n## Background and rationale","[{\"question\":\"Why are smart cities particularly vulnerable to cyberattacks from IoT devices?\",\"answer\":\"Smart cities rely on interconnected sensors and widespread device connectivity, which creates expanded entry points. This increases exposure of services and sensitive data to malicious access and exploitation.\"},{\"question\":\"What is the role of honeypot data in improving attack detection?\",\"answer\":\"The study analyzes real-world cyber-attack datasets generated by diverse honeypots simulating IoT devices. Integrating honeypot data into IoT security frameworks improves detection and mitigation.\"},{\"question\":\"Which attack types are highlighted as common threats to IoT and smart city ecosystems?\",\"answer\":\"The document names threats including DDoS, ransomware, device exploitation, data manipulation, Mirai botnet, port scanning, and brute-force attacks.\"}]","Securing smart cities through machine learning - A honeypot-driven approach to attack detection in Internet of Things ecosystems | PDF",1785807533,48,{"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},"securing-smart-cities-through-machine-learning-a-honeypot-driven-approach-to-attack-detection-in-internet-of-things-ecosystems","",{"@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/securing-smart-cities-through-machine-learning-a-honeypot-driven-approach-to-attack-detection-in-internet-of-things-ecosystems/121889/",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":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why are smart cities particularly vulnerable to cyberattacks from IoT devices?","Question",{"text":75,"@type":76},"Smart cities rely on interconnected sensors and widespread device connectivity, which creates expanded entry points. This increases exposure of services and sensitive data to malicious access and exploitation.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What is the role of honeypot data in improving attack detection?",{"text":80,"@type":76},"The study analyzes real-world cyber-attack datasets generated by diverse honeypots simulating IoT devices. Integrating honeypot data into IoT security frameworks improves detection and mitigation.",{"name":82,"@type":73,"acceptedAnswer":83},"Which attack types are highlighted as common threats to IoT and smart city ecosystems?",{"text":84,"@type":76},"The document names threats including DDoS, ransomware, device exploitation, data manipulation, Mirai botnet, port scanning, and brute-force attacks.","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":21,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},"General","general"]