[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126322-en":3,"doc-seo-126322-105":31,"detail-sidebar-cat-0-en-105":93},{"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":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},126322,962085570644,"Evangeline","https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d",8,"Research & Report","Enhanced IoT cybersecurity through machine learning-based penetration testing - Research paper","The Internet of Things (IoT) expands the traditional Internet by connecting physical objects through RFID, sensors, GPS, and M2M communication, yet security concerns continue to hinder its adoption. Current research often overlooks IoT security from the attacker’s viewpoint. This study proposes a penetration-testing approach that combines the Belief-Desire-Intention (BDI) model with machine learning to identify and defend against cyberattacks targeting IoT devices. Experimental results report 85% recall, 90% precision, 87.4% F1-score, and 95% accuracy.","Submitted: 2025-03-08 | Revised: 2025-04-24 | Accepted: 2025-04-30  \nCC-BY 4.0  \nKeywords: Belief-Desire-Intention model, internet of things, penetration testing, cybersecurity attacks, machine learning  \nMohammed J. BAWANEH 1 , ObaidaM. AL-HAZAIMEH 1, 2*,  \nMalekM. AL-NAWASHI 1 , MontherH. AL-BSOOL 1 , Essam HANANDAH 2  \n1 Al-Balqa Applied University, Jordan, [dr_mjab@bau.edu.jo](dr_mjab@bau.edu.jo), [dr_obaida@bau.edu.jo](dr_obaida@bau.edu.jo), [nawashi@bau.edu.jo](nawashi@bau.edu.jo), [monther.bsool@bau.edu.jo](monther.bsool@bau.edu.jo)  \n2 Philadelphia University, Jordan, [ehanandeh@philadelphia.edu.jo](ehanandeh@philadelphia.edu.jo)  \n* [Corresponding author: dr_obaida@bau.edu.jo](Corresponding author: dr_obaida@bau.edu.jo)  \nEnhanced IoT cybersecurity  \nthrough machine learning-based penetration testing  \nAbstract  \nThe Internet of Things (IoT) is a new technology that builds on the old Internet. A network connects all objects using technologies such as Radio Frequency Identification (RFID), sensors, GPS, or Machine-toMachine (M2M) communication. The development of IoT has been negatively impacted by security concerns, which has led to a significant increase in research interest. However, very few methods look atthe security of IoT from the attacker's point of view. As of today, penetration testing is a common way to check the security of traditional internet or systems. It usually takes a lot of time and money. In this paper, we look at the security problems of the Internet of Things (IoT) and suggest a way to test for them. This way is based on a combination of the belief-desire intention (BDI) model and machine learning. The results of the experiments showed that they were very good at detecting and defending against cyberattacks onIoT devices. The proposed BDI-based recall method provided 85% of the results. The 90% precision suggests that the measurements are very accurate. The F1-score was 87.4%, and the accuracy was 95%. The proposed BDI is of exceptional quality in every part of the penetration-testing model. Therefore, it is possible to create a system that can detect and defend against cyberattacks based on the proposed BDI model.  \n1. INTRODUCTION  \nThe Internet of Things (IoT) was a big deal when it came out in 1999. MIT came up with the idea, and it's been a huge part of the next generation of information technology ever since (Yalli et al., 2024) . The \"Internet of Things\" is like an expansion of the original Internet. It links physical objects to the web so that they can transfer data, identify things, find locations, track things, monitor things, and manage them. It uses technologies like Machine to Machine (M2M) communication, Radio Frequency Identification (RFID), and sensors (Mphale et al., 2024; Santos et al., 2014) . As the current literature says, the application, network, and perception layers make up the framework of the Internet of Things (IoT), as shown in Figure 1 (Gokhale et al., 2018) . Users get a bunch of different services from the application layer in all sorts of situations. Data processing and transmission happen at the network layer. At the end of the day, it's the perception layer's job to gather data and identify physical things using various hardware terminals like RFID, sensors, GPS, and more. Smart grids, intelligent traffic, smart cities, smart homes, intelligent healthcare, physical activity, and smart buildings are just a few of the current areas that have made use ofIoT technology. But security has been a big worry because of the growing number of attacks (Abu-Ein et al., 2025; Al-Hazaimeh et al., 2022; Cao et al., 2022; Tahat et al., 2020) .  \nFig. 1. Architecture of IoT layers  \nPenetration testing is a prevalent method that emulates authentic attacks to evaluate the security of traditional Internet or systems (Hu et al., 2020) . Penetration testing execution standard (PTES) (Safitra et al., 2023) defines penetration testing as a process that includes pre-engagement interact","cbCaijxEukuqMCBf","https://ap.wps.com/l/cbCaijxEukuqMCBf","pdf",928751,7,1,15,"English","en",105,"# Introduction\n## IoT architecture and security concerns\n## Penetration testing background and process\n## Proposed BDI-based machine learning approach","[{\"question\":\"Why is IoT security a major concern in this work?\",\"answer\":\"IoT adoption has been negatively affected by escalating cyberattacks. The paper highlights that existing work often lacks attacker-centric evaluation across the IoT attack surface.\"},{\"question\":\"What does the proposed method combine to perform penetration testing?\",\"answer\":\"It combines the Belief-Desire-Intention (BDI) model with machine learning to test IoT security from the attacker’s perspective.\"},{\"question\":\"How effective is the BDI-based penetration-testing approach according to the reported metrics?\",\"answer\":\"The experiments report 85% recall, 90% precision, 87.4% F1-score, and 95% accuracy, indicating strong detection and measurement reliability.\"}]","Enhanced IoT cybersecurity through machine learning-based penetration testing - Research paper | PDF",1785904446,38,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":88,"head_meta":90,"extra_data":92,"updated_unix":29},"enhanced-iot-cybersecurity-through-machine-learning-based-penetration-testing-research-paper","",{"@graph":37,"@context":87},[38,55,70],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,52],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/document/","Document",2,{"item":50,"name":12,"@type":44,"position":51},"https://docshare.wps.com/document/research-report/",3,{"item":53,"name":13,"@type":44,"position":54},"https://docshare.wps.com/document/enhanced-iot-cybersecurity-through-machine-learning-based-penetration-testing-research-paper/126322/",4,{"url":53,"name":13,"@type":56,"author":57,"headline":13,"publisher":59,"fileFormat":62,"inLanguage":24,"description":14,"dateModified":63,"datePublished":64,"encodingFormat":62,"isAccessibleForFree":65,"interactionStatistic":66},"DigitalDocument",{"name":9,"@type":58},"Person",{"url":42,"name":60,"@type":61},"DocShare","Organization","application/pdf","2026-08-23","2026-08-05",true,{"@type":67,"interactionType":68,"userInteractionCount":20},"InteractionCounter",{"@type":69},"ViewAction",{"@type":71,"mainEntity":72},"FAQPage",[73,79,83],{"name":74,"@type":75,"acceptedAnswer":76},"Why is IoT security a major concern in this work?","Question",{"text":77,"@type":78},"IoT adoption has been negatively affected by escalating cyberattacks. The paper highlights that existing work often lacks attacker-centric evaluation across the IoT attack surface.","Answer",{"name":80,"@type":75,"acceptedAnswer":81},"What does the proposed method combine to perform penetration testing?",{"text":82,"@type":78},"It combines the Belief-Desire-Intention (BDI) model with machine learning to test IoT security from the attacker’s perspective.",{"name":84,"@type":75,"acceptedAnswer":85},"How effective is the BDI-based penetration-testing approach according to the reported metrics?",{"text":86,"@type":78},"The experiments report 85% recall, 90% precision, 87.4% F1-score, and 95% accuracy, indicating strong detection and measurement reliability.","https://schema.org",{"og:url":53,"og:type":89,"og:title":13,"og:site_name":60,"og:description":14},"article",{"robots":91,"canonical":53},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":94},[95,99,103,107,112,117,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":96,"show_sort_weight":97,"slug":98},"Story & Novel",90,"story-novel",{"id":48,"doc_module":4,"doc_module_name":47,"category_name":100,"show_sort_weight":101,"slug":102},"Literature",80,"literature",{"id":54,"doc_module":4,"doc_module_name":47,"category_name":104,"show_sort_weight":105,"slug":106},"Exam",70,"exam",{"id":108,"doc_module":4,"doc_module_name":47,"category_name":109,"show_sort_weight":110,"slug":111},5,"Comic",60,"comic",{"id":113,"doc_module":4,"doc_module_name":47,"category_name":114,"show_sort_weight":115,"slug":116},6,"Technology",50,"technology",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":108,"slug":139},19,"General","general"]