Intrusion detection in metaverse environment internet of things systems by metaheuristics tuned two level framework

Internet of Things (IoT) is one of the most important emerging technologies that supports Metaverse integrating process, by enabling smooth data transfer among physical and virtual domains. Integrating sensor devices, wearables, and smart gadgets into Metaverse environment enables IoT to deepen inte...

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Published in:	Scientific reports Vol. 15; no. 1; pp. 3555 - 31
Main Authors:	Antonijevic, Milos, Zivkovic, Miodrag, Djuric Jovicic, Milica, Nikolic, Bosko, Perisic, Jasmina, Milovanovic, Marina, Jovanovic, Luka, Abdel-Salam, Mahmoud, Bacanin, Nebojsa
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 28.01.2025 Nature Publishing Group Nature Portfolio
Subjects:	631/114/2164 631/114/2397 631/114/2400 631/114/2401 Artificial intelligence CatBoost Chimp optimization algorithm Classification Data collection Datasets Decision making Electrical engineering Humanities and Social Sciences Internet Internet of Things LightGBM Machine learning Metaheuristics algorithms Metaverse multidisciplinary Neural networks Optimization Optimization algorithms Science Science (multidisciplinary) Metaheuristics algorithms Chimp optimization algorithm Metaverse LightGBM CatBoost Optimization
ISSN:	2045-2322, 2045-2322
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Abstract	Internet of Things (IoT) is one of the most important emerging technologies that supports Metaverse integrating process, by enabling smooth data transfer among physical and virtual domains. Integrating sensor devices, wearables, and smart gadgets into Metaverse environment enables IoT to deepen interactions and enhance immersion, both crucial for a completely integrated, data-driven Metaverse. Nevertheless, because IoT devices are often built with minimal hardware and are connected to the Internet, they are highly susceptible to different types of cyberattacks, presenting a significant security problem for maintaining a secure infrastructure. Conventional security techniques have difficulty countering these evolving threats, highlighting the need for adaptive solutions powered by artificial intelligence (AI). This work seeks to improve trust and security in IoT edge devices integrated in to the Metaverse. This study revolves around hybrid framework that combines convolutional neural networks (CNN) and machine learning (ML) classifying models, like categorical boosting (CatBoost) and light gradient-boosting machine (LightGBM), further optimized through metaheuristics optimizers for leveraged performance. A two-leveled architecture was designed to manage intricate data, enabling the detection and classification of attacks within IoT networks. A thorough analysis utilizing a real-world IoT network attacks dataset validates the proposed architecture’s efficacy in identification of the specific variants of malevolent assaults, that is a classic multi-class classification challenge. Three experiments were executed utilizing data open to public, where the top models attained a supreme accuracy of 99.83% for multi-class classification. Additionally, explainable AI methods offered valuable supplementary insights into the model’s decision-making process, supporting future data collection efforts and enhancing security of these systems.
AbstractList	Abstract Internet of Things (IoT) is one of the most important emerging technologies that supports Metaverse integrating process, by enabling smooth data transfer among physical and virtual domains. Integrating sensor devices, wearables, and smart gadgets into Metaverse environment enables IoT to deepen interactions and enhance immersion, both crucial for a completely integrated, data-driven Metaverse. Nevertheless, because IoT devices are often built with minimal hardware and are connected to the Internet, they are highly susceptible to different types of cyberattacks, presenting a significant security problem for maintaining a secure infrastructure. Conventional security techniques have difficulty countering these evolving threats, highlighting the need for adaptive solutions powered by artificial intelligence (AI). This work seeks to improve trust and security in IoT edge devices integrated in to the Metaverse. This study revolves around hybrid framework that combines convolutional neural networks (CNN) and machine learning (ML) classifying models, like categorical boosting (CatBoost) and light gradient-boosting machine (LightGBM), further optimized through metaheuristics optimizers for leveraged performance. A two-leveled architecture was designed to manage intricate data, enabling the detection and classification of attacks within IoT networks. A thorough analysis utilizing a real-world IoT network attacks dataset validates the proposed architecture’s efficacy in identification of the specific variants of malevolent assaults, that is a classic multi-class classification challenge. Three experiments were executed utilizing data open to public, where the top models attained a supreme accuracy of 99.83% for multi-class classification. Additionally, explainable AI methods offered valuable supplementary insights into the model’s decision-making process, supporting future data collection efforts and enhancing security of these systems. Internet of Things (IoT) is one of the most important emerging technologies that supports Metaverse integrating process, by enabling smooth data transfer among physical and virtual domains. Integrating sensor devices, wearables, and smart gadgets into Metaverse environment enables IoT to deepen interactions and enhance immersion, both crucial for a completely integrated, data-driven Metaverse. Nevertheless, because IoT devices are often built with minimal hardware and are connected to the Internet, they are highly susceptible to different types of cyberattacks, presenting a significant security problem for maintaining a secure infrastructure. Conventional security techniques have difficulty countering these evolving threats, highlighting the need for adaptive solutions powered by artificial intelligence (AI). This work seeks to improve trust and security in IoT edge devices integrated in to the Metaverse. This study revolves around hybrid framework that combines convolutional neural networks (CNN) and machine learning (ML) classifying models, like categorical boosting (CatBoost) and light gradient-boosting machine (LightGBM), further optimized through metaheuristics optimizers for leveraged performance. A two-leveled architecture was designed to manage intricate data, enabling the detection and classification of attacks within IoT networks. A thorough analysis utilizing a real-world IoT network attacks dataset validates the proposed architecture’s efficacy in identification of the specific variants of malevolent assaults, that is a classic multi-class classification challenge. Three experiments were executed utilizing data open to public, where the top models attained a supreme accuracy of 99.83% for multi-class classification. Additionally, explainable AI methods offered valuable supplementary insights into the model’s decision-making process, supporting future data collection efforts and enhancing security of these systems. Internet of Things (IoT) is one of the most important emerging technologies that supports Metaverse integrating process, by enabling smooth data transfer among physical and virtual domains. Integrating sensor devices, wearables, and smart gadgets into Metaverse environment enables IoT to deepen interactions and enhance immersion, both crucial for a completely integrated, data-driven Metaverse. Nevertheless, because IoT devices are often built with minimal hardware and are connected to the Internet, they are highly susceptible to different types of cyberattacks, presenting a significant security problem for maintaining a secure infrastructure. Conventional security techniques have difficulty countering these evolving threats, highlighting the need for adaptive solutions powered by artificial intelligence (AI). This work seeks to improve trust and security in IoT edge devices integrated in to the Metaverse. This study revolves around hybrid framework that combines convolutional neural networks (CNN) and machine learning (ML) classifying models, like categorical boosting (CatBoost) and light gradient-boosting machine (LightGBM), further optimized through metaheuristics optimizers for leveraged performance. A two-leveled architecture was designed to manage intricate data, enabling the detection and classification of attacks within IoT networks. A thorough analysis utilizing a real-world IoT network attacks dataset validates the proposed architecture's efficacy in identification of the specific variants of malevolent assaults, that is a classic multi-class classification challenge. Three experiments were executed utilizing data open to public, where the top models attained a supreme accuracy of 99.83% for multi-class classification. Additionally, explainable AI methods offered valuable supplementary insights into the model's decision-making process, supporting future data collection efforts and enhancing security of these systems.Internet of Things (IoT) is one of the most important emerging technologies that supports Metaverse integrating process, by enabling smooth data transfer among physical and virtual domains. Integrating sensor devices, wearables, and smart gadgets into Metaverse environment enables IoT to deepen interactions and enhance immersion, both crucial for a completely integrated, data-driven Metaverse. Nevertheless, because IoT devices are often built with minimal hardware and are connected to the Internet, they are highly susceptible to different types of cyberattacks, presenting a significant security problem for maintaining a secure infrastructure. Conventional security techniques have difficulty countering these evolving threats, highlighting the need for adaptive solutions powered by artificial intelligence (AI). This work seeks to improve trust and security in IoT edge devices integrated in to the Metaverse. This study revolves around hybrid framework that combines convolutional neural networks (CNN) and machine learning (ML) classifying models, like categorical boosting (CatBoost) and light gradient-boosting machine (LightGBM), further optimized through metaheuristics optimizers for leveraged performance. A two-leveled architecture was designed to manage intricate data, enabling the detection and classification of attacks within IoT networks. A thorough analysis utilizing a real-world IoT network attacks dataset validates the proposed architecture's efficacy in identification of the specific variants of malevolent assaults, that is a classic multi-class classification challenge. Three experiments were executed utilizing data open to public, where the top models attained a supreme accuracy of 99.83% for multi-class classification. Additionally, explainable AI methods offered valuable supplementary insights into the model's decision-making process, supporting future data collection efforts and enhancing security of these systems.
ArticleNumber	3555
Author	Nikolic, Bosko Bacanin, Nebojsa Djuric Jovicic, Milica Jovanovic, Luka Zivkovic, Miodrag Perisic, Jasmina Antonijevic, Milos Milovanovic, Marina Abdel-Salam, Mahmoud
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Cites_doi	10.1002/cpe.8252 10.1016/j.eswa.2020.113338 10.1002/ett.4969 10.1145/3065386 10.1002/cpe.8091 10.1016/j.knosys.2023.111081 10.57019/jmv.1286526 10.1016/j.caeai.2022.100082 10.1016/j.engfailanal.2023.107219 10.1109/ACCESS.2022.3233596 10.3390/s20133625 10.1109/ACCESS.2024.3446653 10.1145/2939672.2939785 10.4310/SII.2009.v2.n3.a8 10.1016/j.asoc.2024.111434 10.1016/j.aei.2023.102130 10.1007/s11042-024-18295-9 10.1109/CEC48606.2020.9185583 10.1016/j.swevo.2021.100973 10.3390/math12182918 10.3390/s23135941 10.1109/ICACITE53722.2022.9823766 10.1504/IJBIC.2013.055093 10.1080/01621459.1972.10481232 10.7717/peerj-cs.1565 10.1002/ett.5056 10.3390/encyclopedia2010031 10.1109/JIOT.2023.3278329 10.3390/app10124102 10.1109/JAS.2021.1004129 10.1007/978-981-97-1488-9_26 10.3390/axioms12030266 10.1109/MCOM.018.2300095 10.1007/s00521-023-09366-3 10.1002/wics.1278 10.3390/jimaging6100110 10.3390/su151612563 10.1016/j.ijcip.2024.100674 10.1109/4235.585893 10.1002/0470011815.b2a15177 10.21037/atm.2020.02.44 10.7717/peerj-cs.1795 10.26599/BDMA.2022.9020047 10.1109/COMST.2020.2988293 10.1007/s10586-024-04351-4 10.1023/A:1010933404324 10.1109/MSP.2012.2205597 10.1016/S0305-0548(97)00031-2 10.1016/j.sintl.2024.100297 10.1016/j.rineng.2024.103171 10.1145/507533.507538 10.1093/sysbio/34.4.449 10.3390/app132312687 10.1117/1.JEI.31.6.061815 10.1007/s11831-023-09975-0 10.1016/j.eswa.2021.116158 10.1016/j.eswa.2020.114107 10.1109/JIOT.2022.3232845 10.1016/j.asoc.2023.110659 10.1109/ICNN.1995.488968 10.1155/2018/6973103 10.1007/s00500-022-07780-8 10.1109/COMST.2022.3202047 10.1109/ACCESS.2023.3299589 10.1016/j.jhydrol.2023.129599 10.1016/j.advengsoft.2016.01.008 10.3390/electronics11223798 10.1016/j.engappai.2021.104210 10.1007/s10462-023-10678-y 10.3390/app10196620 10.1109/CEC.2007.4424748 10.1002/dac.5886 10.1007/s10462-023-10567-4 10.1038/s41598-024-73932-5 10.1186/s12864-019-6413-7 10.1007/s40747-023-01265-3 10.1109/FG.2017.137 10.1007/s10898-007-9149-x 10.1109/COMST.2020.2986444 10.1038/s41598-020-57897-9
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Keywords	Metaheuristics algorithms Chimp optimization algorithm Metaverse LightGBM CatBoost Optimization
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References	P Dakic (88135_CR77) 2024; 14 M Zivkovic (88135_CR18) 2022; 11 YK Saheed (88135_CR32) 2024; 155 MA Al-Garadi (88135_CR14) 2020; 22 YK Saheed (88135_CR27) 2024; 45 J Zou (88135_CR87) 2009 F Hussain (88135_CR15) 2020; 22 BB Schultz (88135_CR89) 1985; 34 X-S Yang (88135_CR61) 2013; 5 SS Shapiro (88135_CR90) 1972; 67 Y Huang (88135_CR12) 2023; 6 Y Wang (88135_CR7) 2022; 25 88135_CR64 A Petrovic (88135_CR17) 2024; 12 BAS Emambocus (88135_CR52) 2023; 11 R Zhao (88135_CR10) 2023; 3 R Cheng (88135_CR11) 2023; 62 S Mystakidis (88135_CR1) 2022; 2 S Albawi (88135_CR36) 2018; 2018 88135_CR62 M Khishe (88135_CR21) 2020; 149 H Wang (88135_CR3) 2023; 10 S Mirjalili (88135_CR57) 2019 N Savanović (88135_CR76) 2023; 15 D Micci-Barreca (88135_CR45) 2001; 3 L Jovanovic (88135_CR20) 2023; 22 B de Ville (88135_CR82) 2013; 5 88135_CR29 G-J Hwang (88135_CR5) 2022; 3 D Połap (88135_CR23) 2021; 166 M Bjekic (88135_CR43) 2023; 9 D Karaboga (88135_CR59) 2007; 39 Z Lao (88135_CR51) 2023; 148 88135_CR31 B Predić (88135_CR66) 2024; 10 88135_CR30 X-S Yang (88135_CR60) 2013; 1 88135_CR74 88135_CR37 M Bukumira (88135_CR44) 2022; 31 J Tang (88135_CR54) 2021; 8 M Pavlov-Kagadejev (88135_CR71) 2024; 57 88135_CR79 RF Woolson (88135_CR91) 2005 D Wolpert (88135_CR16) 1997; 1 88135_CR78 D Chicco (88135_CR80) 2020; 21 S Thapa (88135_CR25) 2020; 53 K Li (88135_CR6) 2022; 10 88135_CR70 L Li (88135_CR50) 2023; 58 S Lundberg (88135_CR93) 2017; 1705 H Mrabet (88135_CR8) 2020; 20 88135_CR39 A Chattopadhyay (88135_CR42) 2020; 10 T Zivkovic (88135_CR65) 2023; 146 YK Saheed (88135_CR92) 2024; 24 Z Amiri (88135_CR73) 2024; 35 K Zanbouri (88135_CR75) 2024; 37 88135_CR41 L Breiman (88135_CR83) 2001; 45 88135_CR85 88135_CR47 88135_CR46 L Velasco (88135_CR69) 2024; 31 J Bai (88135_CR63) 2023; 282 T Hastie (88135_CR86) 2009; 2 N Mladenović (88135_CR58) 1997; 24 X Guo (88135_CR49) 2023; 621 88135_CR2 C Stoean (88135_CR68) 2023; 12 C-F Tsai (88135_CR28) 2020; 10 A Heidari (88135_CR4) 2024; 36 L Tawalbeh (88135_CR9) 2020; 10 M Asadi (88135_CR13) 2024; 35 A Krizhevsky (88135_CR35) 2017; 60 M Salb (88135_CR19) 2023; 13 YK Saheed (88135_CR33) 2025; 6 M Dobrojevic (88135_CR72) 2024; 80 L Abualigah (88135_CR24) 2022; 191 BB Sinha (88135_CR48) 2023; 15 MA Tawhid (88135_CR53) 2023; 27 O Kramer (88135_CR84) 2013 F Lombardi (88135_CR40) 2020; 6 S Mirjalili (88135_CR81) 2016; 95 A LaTorre (88135_CR88) 2021; 67 H Jia (88135_CR22) 2023; 56 88135_CR56 M Rostami (88135_CR55) 2021; 100 Z Amiri (88135_CR26) 2024; 36 G Hinton (88135_CR38) 2012; 29 A Vakili (88135_CR67) 2024; 36 ECP Neto (88135_CR34) 2023; 23
References_xml	– volume: 36 year: 2024 ident: 88135_CR4 publication-title: Concurr. Comput. Pract. Exp. doi: 10.1002/cpe.8252 – volume: 149 year: 2020 ident: 88135_CR21 publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2020.113338 – volume: 35 year: 2024 ident: 88135_CR73 publication-title: Trans. Emerg. Telecommun. Technol. doi: 10.1002/ett.4969 – volume: 60 start-page: 84 year: 2017 ident: 88135_CR35 publication-title: Commun. ACM doi: 10.1145/3065386 – volume: 36 year: 2024 ident: 88135_CR67 publication-title: Concurr. Comput. Pract. Exp. doi: 10.1002/cpe.8091 – volume: 282 year: 2023 ident: 88135_CR63 publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2023.111081 – volume: 3 start-page: 93 year: 2023 ident: 88135_CR10 publication-title: J. Metaverse doi: 10.57019/jmv.1286526 – volume: 3 year: 2022 ident: 88135_CR5 publication-title: Comput. Educ. Artif. Intell. doi: 10.1016/j.caeai.2022.100082 – volume: 148 year: 2023 ident: 88135_CR51 publication-title: Eng. Fail. Anal. doi: 10.1016/j.engfailanal.2023.107219 – volume: 11 start-page: 1280 year: 2023 ident: 88135_CR52 publication-title: IEEE Access doi: 10.1109/ACCESS.2022.3233596 – volume: 20 start-page: 3625 year: 2020 ident: 88135_CR8 publication-title: Sensors doi: 10.3390/s20133625 – ident: 88135_CR30 doi: 10.1109/ACCESS.2024.3446653 – ident: 88135_CR85 doi: 10.1145/2939672.2939785 – ident: 88135_CR37 – volume: 2 start-page: 349 year: 2009 ident: 88135_CR86 publication-title: Stat. Interface doi: 10.4310/SII.2009.v2.n3.a8 – volume: 155 year: 2024 ident: 88135_CR32 publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2024.111434 – volume: 22 start-page: 543 year: 2023 ident: 88135_CR20 publication-title: J. Web Eng. – volume: 58 year: 2023 ident: 88135_CR50 publication-title: Adv. Eng. Inform. doi: 10.1016/j.aei.2023.102130 – ident: 88135_CR31 doi: 10.1007/s11042-024-18295-9 – ident: 88135_CR62 doi: 10.1109/CEC48606.2020.9185583 – ident: 88135_CR46 – volume: 67 year: 2021 ident: 88135_CR88 publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2021.100973 – volume: 12 start-page: 2918 year: 2024 ident: 88135_CR17 publication-title: Mathematics doi: 10.3390/math12182918 – volume: 23 start-page: 5941 year: 2023 ident: 88135_CR34 publication-title: Sensors doi: 10.3390/s23135941 – ident: 88135_CR2 doi: 10.1109/ICACITE53722.2022.9823766 – volume: 5 start-page: 141 year: 2013 ident: 88135_CR61 publication-title: Int. J. Bio-Inspired Comput. doi: 10.1504/IJBIC.2013.055093 – volume: 67 start-page: 215 year: 1972 ident: 88135_CR90 publication-title: J. Am. Stat. Assoc. doi: 10.1080/01621459.1972.10481232 – ident: 88135_CR78 – ident: 88135_CR47 – volume: 9 year: 2023 ident: 88135_CR43 publication-title: PeerJ Comput. Sci. doi: 10.7717/peerj-cs.1565 – volume: 35 year: 2024 ident: 88135_CR13 publication-title: Trans. Emerg. Telecommun. Technol. doi: 10.1002/ett.5056 – volume: 2 start-page: 486 year: 2022 ident: 88135_CR1 publication-title: Encyclopedia doi: 10.3390/encyclopedia2010031 – volume: 10 start-page: 14671 year: 2023 ident: 88135_CR3 publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2023.3278329 – volume: 15 start-page: 2053 year: 2023 ident: 88135_CR48 publication-title: Int. J. Inf. Technol. – volume: 10 start-page: 4102 year: 2020 ident: 88135_CR9 publication-title: Appl. Sci. doi: 10.3390/app10124102 – volume: 8 start-page: 1627 year: 2021 ident: 88135_CR54 publication-title: IEEE/CAA J. Autom. Sin. doi: 10.1109/JAS.2021.1004129 – ident: 88135_CR70 doi: 10.1007/978-981-97-1488-9_26 – volume: 12 start-page: 266 year: 2023 ident: 88135_CR68 publication-title: Axioms doi: 10.3390/axioms12030266 – volume: 62 start-page: 156 year: 2023 ident: 88135_CR11 publication-title: IEEE Commun. Mag. doi: 10.1109/MCOM.018.2300095 – volume: 36 start-page: 5757 year: 2024 ident: 88135_CR26 publication-title: Neural Comput. Appl. doi: 10.1007/s00521-023-09366-3 – volume: 5 start-page: 448 year: 2013 ident: 88135_CR82 publication-title: WIREs Comput. Stat. doi: 10.1002/wics.1278 – volume: 6 start-page: 110 year: 2020 ident: 88135_CR40 publication-title: J. Imaging doi: 10.3390/jimaging6100110 – volume: 15 start-page: 12563 year: 2023 ident: 88135_CR76 publication-title: Sustainability doi: 10.3390/su151612563 – volume: 45 year: 2024 ident: 88135_CR27 publication-title: Int. J. Crit. Infrastruct. Prot. doi: 10.1016/j.ijcip.2024.100674 – volume: 1 start-page: 67 year: 1997 ident: 88135_CR16 publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/4235.585893 – volume-title: In Encyclopedia of Biostatistics year: 2005 ident: 88135_CR91 doi: 10.1002/0470011815.b2a15177 – ident: 88135_CR41 doi: 10.21037/atm.2020.02.44 – ident: 88135_CR64 doi: 10.7717/peerj-cs.1795 – volume: 6 start-page: 234 year: 2023 ident: 88135_CR12 publication-title: Big Data Min. Anal. doi: 10.26599/BDMA.2022.9020047 – volume: 22 start-page: 1646 year: 2020 ident: 88135_CR14 publication-title: IEEE Commun. Surv. Tutor. doi: 10.1109/COMST.2020.2988293 – ident: 88135_CR74 doi: 10.1007/s10586-024-04351-4 – volume: 45 start-page: 5 year: 2001 ident: 88135_CR83 publication-title: Mach. Learn. doi: 10.1023/A:1010933404324 – volume: 29 start-page: 82 year: 2012 ident: 88135_CR38 publication-title: IEEE Signal Process. Mag. doi: 10.1109/MSP.2012.2205597 – volume: 24 start-page: 1097 year: 1997 ident: 88135_CR58 publication-title: Comput. Oper. Res. doi: 10.1016/S0305-0548(97)00031-2 – volume: 6 year: 2025 ident: 88135_CR33 publication-title: Sens. Int. doi: 10.1016/j.sintl.2024.100297 – volume: 24 year: 2024 ident: 88135_CR92 publication-title: Results Eng. doi: 10.1016/j.rineng.2024.103171 – volume: 3 start-page: 27 year: 2001 ident: 88135_CR45 publication-title: ACM SIGKDD Explor. Newsl. doi: 10.1145/507533.507538 – volume: 1705 start-page: 07874 year: 2017 ident: 88135_CR93 publication-title: A unified approach to interpreting model predictions – volume: 34 start-page: 449 year: 1985 ident: 88135_CR89 publication-title: Syst. Biol. doi: 10.1093/sysbio/34.4.449 – volume: 13 start-page: 12687 year: 2023 ident: 88135_CR19 publication-title: Appl. Sci. doi: 10.3390/app132312687 – volume: 31 start-page: 061815 year: 2022 ident: 88135_CR44 publication-title: J. Electron. Imaging doi: 10.1117/1.JEI.31.6.061815 – volume: 31 start-page: 125 year: 2024 ident: 88135_CR69 publication-title: Arch. Comput. Methods Eng. doi: 10.1007/s11831-023-09975-0 – volume: 191 year: 2022 ident: 88135_CR24 publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2021.116158 – volume: 166 year: 2021 ident: 88135_CR23 publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2020.114107 – volume: 10 start-page: 4148 year: 2022 ident: 88135_CR6 publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2022.3232845 – volume: 146 year: 2023 ident: 88135_CR65 publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2023.110659 – volume: 80 start-page: 4997 year: 2024 ident: 88135_CR72 publication-title: Comput. Mater. Contin. – ident: 88135_CR56 doi: 10.1109/ICNN.1995.488968 – volume: 2018 start-page: 6973103 year: 2018 ident: 88135_CR36 publication-title: Comput. Intell. Neurosci. doi: 10.1155/2018/6973103 – volume: 27 start-page: 8867 year: 2023 ident: 88135_CR53 publication-title: Soft. Comput. doi: 10.1007/s00500-022-07780-8 – volume: 25 start-page: 319 year: 2022 ident: 88135_CR7 publication-title: IEEE Commun. Surv. Tutor. doi: 10.1109/COMST.2022.3202047 – ident: 88135_CR29 doi: 10.1109/ACCESS.2023.3299589 – volume: 621 year: 2023 ident: 88135_CR49 publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2023.129599 – volume: 95 start-page: 51 year: 2016 ident: 88135_CR81 publication-title: Adv. Eng. Softw. doi: 10.1016/j.advengsoft.2016.01.008 – start-page: 43 volume-title: Genetic Algorithm year: 2019 ident: 88135_CR57 – volume: 11 start-page: 3798 year: 2022 ident: 88135_CR18 publication-title: Electronics doi: 10.3390/electronics11223798 – volume: 100 year: 2021 ident: 88135_CR55 publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2021.104210 – volume: 57 start-page: 45 year: 2024 ident: 88135_CR71 publication-title: Artif. Intell. Rev. doi: 10.1007/s10462-023-10678-y – volume: 10 start-page: 6620 year: 2020 ident: 88135_CR28 publication-title: Appl. Sci. doi: 10.3390/app10196620 – ident: 88135_CR79 doi: 10.1109/CEC.2007.4424748 – volume: 37 year: 2024 ident: 88135_CR75 publication-title: Int. J. Commun Syst. doi: 10.1002/dac.5886 – volume: 56 start-page: 1919 year: 2023 ident: 88135_CR22 publication-title: Artif. Intell. Rev. doi: 10.1007/s10462-023-10567-4 – volume: 14 start-page: 22884 year: 2024 ident: 88135_CR77 publication-title: Sci. Rep. doi: 10.1038/s41598-024-73932-5 – volume: 21 start-page: 1 year: 2020 ident: 88135_CR80 publication-title: BMC Genom. doi: 10.1186/s12864-019-6413-7 – volume: 1 start-page: 36 year: 2013 ident: 88135_CR60 publication-title: Int. J. Swarm Intell. – start-page: 13 volume-title: K-Nearest Neighbors year: 2013 ident: 88135_CR84 – volume: 53 start-page: 1 year: 2020 ident: 88135_CR25 publication-title: In Conference: Midwest Instruction and Computing Symposium (MICS) – volume: 10 start-page: 2249 year: 2024 ident: 88135_CR66 publication-title: Complex Intell. Syst. doi: 10.1007/s40747-023-01265-3 – start-page: 14 volume-title: Overview of Artificial Neural Networks year: 2009 ident: 88135_CR87 – ident: 88135_CR39 doi: 10.1109/FG.2017.137 – volume: 39 start-page: 459 year: 2007 ident: 88135_CR59 publication-title: J. Glob. Optim. doi: 10.1007/s10898-007-9149-x – volume: 22 start-page: 1686 year: 2020 ident: 88135_CR15 publication-title: IEEE Commun. Surv. Tutor. doi: 10.1109/COMST.2020.2986444 – volume: 10 start-page: 1317 year: 2020 ident: 88135_CR42 publication-title: Sci. Rep. doi: 10.1038/s41598-020-57897-9
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SubjectTerms	631/114/2164 631/114/2397 631/114/2400 631/114/2401 Artificial intelligence CatBoost Chimp optimization algorithm Classification Data collection Datasets Decision making Electrical engineering Humanities and Social Sciences Internet Internet of Things LightGBM Machine learning Metaheuristics algorithms Metaverse multidisciplinary Neural networks Optimization Optimization algorithms Science Science (multidisciplinary)
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Title	Intrusion detection in metaverse environment internet of things systems by metaheuristics tuned two level framework
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