{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,14]],"date-time":"2026-06-14T00:01:10Z","timestamp":1781395270807,"version":"3.54.1"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2023,3,3]],"date-time":"2023-03-03T00:00:00Z","timestamp":1677801600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,3,3]],"date-time":"2023-03-03T00:00:00Z","timestamp":1677801600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100011698","name":"Junta de Comunidades de Castilla-La Mancha","doi-asserted-by":"publisher","award":["SBPLY\/21\/180501\/000195"],"award-info":[{"award-number":["SBPLY\/21\/180501\/000195"]}],"id":[{"id":"10.13039\/501100011698","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100011698","name":"Junta de Comunidades de Castilla-La Mancha","doi-asserted-by":"publisher","award":["SBPLY\/21\/180501\/000195"],"award-info":[{"award-number":["SBPLY\/21\/180501\/000195"]}],"id":[{"id":"10.13039\/501100011698","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100011698","name":"Junta de Comunidades de Castilla-La Mancha","doi-asserted-by":"publisher","award":["SBPLY\/21\/180501\/000195"],"award-info":[{"award-number":["SBPLY\/21\/180501\/000195"]}],"id":[{"id":"10.13039\/501100011698","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100011698","name":"Junta de Comunidades de Castilla-La Mancha","doi-asserted-by":"publisher","award":["SBPLY\/21\/180501\/000195"],"award-info":[{"award-number":["SBPLY\/21\/180501\/000195"]}],"id":[{"id":"10.13039\/501100011698","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["PID2021-123627OB-C52"],"award-info":[{"award-number":["PID2021-123627OB-C52"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["PID2021-123627OB-C52"],"award-info":[{"award-number":["PID2021-123627OB-C52"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["PID2021-123627OB-C52"],"award-info":[{"award-number":["PID2021-123627OB-C52"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["PID2021-123627OB-C52"],"award-info":[{"award-number":["PID2021-123627OB-C52"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004895","name":"European Social Fund","doi-asserted-by":"publisher","award":["PI001482"],"award-info":[{"award-number":["PI001482"]}],"id":[{"id":"10.13039\/501100004895","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004895","name":"European Social Fund","doi-asserted-by":"publisher","award":["2021-POST-20518"],"award-info":[{"award-number":["2021-POST-20518"]}],"id":[{"id":"10.13039\/501100004895","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014440","name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades","doi-asserted-by":"publisher","award":["FPU 17\/03105"],"award-info":[{"award-number":["FPU 17\/03105"]}],"id":[{"id":"10.13039\/100014440","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007480","name":"Universidad de Castilla la Mancha","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100007480","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"published-print":{"date-parts":[[2023,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>In recent years, the Industrial Internet of Things (IIoT) has grown rapidly, a fact that has led to an increase in the number of cyberattacks that target this environment and the technologies that it brings together. Unfortunately, when it comes to using tools for stopping such attacks, it can be noticed that there are inherent weaknesses in this paradigm, such as limitations in computational capacity, memory and network bandwidth. Under these circumstances, the solutions used until now in conventional scenarios cannot be directly adopted by the IIoT, and so it is necessary to develop and design new ones that can effectively tackle this problem. Furthermore, these new solutions must be tested in order to verify their performance and viability, which requires testing architectures that are compatible with newly introduced IIoT topologies. With the aim of addressing these issues, this work proposes MECInOT, which is an architecture based on openLEON and capable of generating test scenarios for the IIoT environment. The performance of this architecture is validated by creating an intelligent threat detector based on tree-based algorithms, such as decision tree, random forest and other machine learning techniques. Which allows us to generate an intelligent and to demonstrate, we could generate an intelligent threat detector and demonstrate the suitability of our architecture for testing solutions in IIoT environments. In addition, by using MECInOT, we compare the performance of the different machine learning algorithms in an IIoT network. Firstly, we present the benefits of our proposal, and secondly, we describe the emulation of an IIoT environment while ensuring the repeatability of the experiments.<\/jats:p>","DOI":"10.1007\/s11227-023-05098-2","type":"journal-article","created":{"date-parts":[[2023,3,3]],"date-time":"2023-03-03T10:05:48Z","timestamp":1677837948000},"page":"11895-11933","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["MECInOT: a multi-access edge computing and industrial internet of things emulator for the modelling and study of cybersecurity threats"],"prefix":"10.1007","volume":"79","author":[{"given":"Sergio","family":"Ruiz-Villafranca","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Javier","family":"Carrillo-Mond\u00e9jar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan Manuel","family":"Castelo G\u00f3mez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jos\u00e9","family":"Rold\u00e1n-G\u00f3mez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,3,3]]},"reference":[{"key":"5098_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/00207543.2020.1798035","volume":"201","author":"D Ivanov","year":"2020","unstructured":"Ivanov D, Tang C, Dolgui A, Battini D, Das A (2020) Researchers\u2019 perspectives on industry 4.0: multi-disciplinary analysis and opportunities for operations management. Int J Product Res 201:1\u201324. https:\/\/doi.org\/10.1080\/00207543.2020.1798035","journal-title":"Int J Product Res"},{"key":"5098_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jii.2021.100257","volume":"26","author":"PKR Maddikunta","year":"2022","unstructured":"Maddikunta PKR, Pham Q-V, Deepa N, Dev K, Gadekallu TR, Ruby R, Liyanage M (2022) Industry 5.0: A survey on enabling technologies and potential applications. J Indust Inform Integrat 26:100257. https:\/\/doi.org\/10.1016\/j.jii.2021.100257","journal-title":"J Indust Inform Integrat"},{"key":"5098_CR3","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1016\/j.jmsy.2021.10.006","volume":"61","author":"X Xu","year":"2021","unstructured":"Xu X, Lu Y, Vogel-Heuser B, Wang L (2021) Industry 4.0 and industry 5.0-inception, conception and perception. J Manufact Syst 61:530\u2013535. https:\/\/doi.org\/10.1016\/j.jmsy.2021.10.006","journal-title":"J Manufact Syst"},{"key":"5098_CR4","doi-asserted-by":"publisher","first-page":"197017","DOI":"10.1109\/ACCESS.2020.3034136","volume":"8","author":"A Filali","year":"2020","unstructured":"Filali A, Abouaomar A, Cherkaoui S, Kobbane A, Guizani M (2020) Multi-access edge computing: A survey. IEEE Access 8:197017\u2013197046","journal-title":"IEEE Access"},{"issue":"11","key":"5098_CR5","doi-asserted-by":"publisher","first-page":"3901","DOI":"10.3390\/s21113901","volume":"21","author":"LL Dhirani","year":"2021","unstructured":"Dhirani LL, Armstrong E, Newe T (2021) Industrial iot, cyber threats, and standards landscape: Evaluation and roadmap. Sensors 21(11):3901","journal-title":"Sensors"},{"key":"5098_CR6","doi-asserted-by":"publisher","first-page":"107485","DOI":"10.1016\/j.ress.2021.107485","volume":"209","author":"M Iaiani","year":"2021","unstructured":"Iaiani M, Tugnoli A, Bonvicini S, Cozzani V (2021) Analysis of cybersecurity-related incidents in the process industry. Reliab Eng Syst Safety 209:107485. https:\/\/doi.org\/10.1016\/j.ress.2021.107485","journal-title":"Reliab Eng Syst Safety"},{"issue":"8","key":"5098_CR7","doi-asserted-by":"publisher","first-page":"6437","DOI":"10.1109\/JIOT.2021.3049173","volume":"8","author":"M Shen","year":"2021","unstructured":"Shen M, Liu A, Huang G, Xiong NN, Lu H (2021) Attdc: an active and traceable trust data collection scheme for industrial security in smart cities. IEEE Int Things J 8(8):6437\u20136453. https:\/\/doi.org\/10.1109\/JIOT.2021.3049173","journal-title":"IEEE Int Things J"},{"key":"5098_CR8","doi-asserted-by":"crossref","unstructured":"Chander B, Pal S, De D, Buyya R (2022). In: De D, Buyya R, Pal S (eds) Artificial intelligence-based internet of things for industry 5.0. Springer, Cham, pp 3\u201345","DOI":"10.1007\/978-3-030-87059-1_1"},{"key":"5098_CR9","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.comcom.2019.08.024","volume":"148","author":"C Fiandrino","year":"2019","unstructured":"Fiandrino C, Pizarro A, Mateo P, Andr\u00e9s Ramiro C, Ludant N, Widmer J (2019) Openleon: an end-to-end emulation platform from the edge data center to the mobile user. Comput Commun 148:17\u201326. https:\/\/doi.org\/10.1016\/j.comcom.2019.08.024","journal-title":"Comput Commun"},{"key":"5098_CR10","doi-asserted-by":"publisher","unstructured":"Auliva RS, Sheu R-K, Liang D, Wang W-J (2018) Iiot testbed: A dds-based emulation tool for industrial iot applications. In: 2018 International Conference on System Science and Engeering (ICSSE), pp. 1\u20134. https:\/\/doi.org\/10.1109\/ICSSE.2018.8520091","DOI":"10.1109\/ICSSE.2018.8520091"},{"issue":"10","key":"5098_CR11","doi-asserted-by":"publisher","first-page":"6822","DOI":"10.1002\/cpe.6822","volume":"34","author":"G Luo","year":"2022","unstructured":"Luo G, Chen Z, Mohammed BO (2022) A systematic literature review of intrusion detection systems in the cloud-based IoT environments. Concurr Computat Pract Exp 34(10):6822. https:\/\/doi.org\/10.1002\/cpe.6822","journal-title":"Concurr Computat Pract Exp"},{"key":"5098_CR12","unstructured":"Moysis S, Zacharias G, Demetris T, George P, Marios\u00a0D D (2020) Fogify: A fog computing emulation framework. In: Proceedings of the 5th ACM\/IEEE Symposium on Edge Computing. SEC \u201920. Association for Computing Machinery. New York, NY, USA"},{"key":"5098_CR13","doi-asserted-by":"publisher","unstructured":"Coutinho A, Greve F, Prazeres C, Cardoso J (2018) Fogbed: A rapid-prototyping emulation environment for fog computing. In: 2018 IEEE International Conference on Communications (ICC), pp. 1\u20137. https:\/\/doi.org\/10.1109\/ICC.2018.8423003","DOI":"10.1109\/ICC.2018.8423003"},{"issue":"22","key":"5098_CR14","doi-asserted-by":"publisher","first-page":"16231","DOI":"10.1109\/JIOT.2021.3095308","volume":"8","author":"TK Rodrigues","year":"2021","unstructured":"Rodrigues TK, Liu J, Kato N (2021) Application of cybertwin for offloading in mobile multiaccess edge computing for 6g networks. IEEE Int Things J 8(22):16231\u201316242. https:\/\/doi.org\/10.1109\/JIOT.2021.3095308","journal-title":"IEEE Int Things J"},{"key":"5098_CR15","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1016\/j.isprsjprs.2020.06.004","volume":"166","author":"J Liu","year":"2020","unstructured":"Liu J, Li Q, Cao R, Tang W, Qiu G (2020) Mininet: an extremely lightweight convolutional neural network for real-time unsupervised monocular depth estimation. ISPRS J Photog Remote Sens 166:255\u2013267","journal-title":"ISPRS J Photog Remote Sens"},{"issue":"1","key":"5098_CR16","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1109\/JPROC.2014.2371999","volume":"103","author":"D Kreutz","year":"2014","unstructured":"Kreutz D, Ramos FM, Verissimo PE, Rothenberg CE, Azodolmolky S, Uhlig S (2014) Software-defined networking: a comprehensive survey. Proceed IEEE 103(1):14\u201376","journal-title":"Proceed IEEE"},{"key":"5098_CR17","doi-asserted-by":"publisher","first-page":"116974","DOI":"10.1109\/ACCESS.2020.3001277","volume":"8","author":"Q-V Pham","year":"2020","unstructured":"Pham Q-V, Fang F, Ha VN, Piran MJ, Le M, Le LB, Hwang W-J, Ding Z (2020) A survey of multi-access edge computing in 5g and beyond: fundamentals, technology integration, and state-of-the-art. IEEE Access 8:116974\u2013117017","journal-title":"IEEE Access"},{"key":"5098_CR18","unstructured":"Liyanage M, Porambage P, Ding AY (2018) Five driving forces of multi-access edge computing. arXiv preprint arXiv:1810.00827"},{"key":"5098_CR19","doi-asserted-by":"crossref","first-page":"381","DOI":"10.21275\/ART20203995","volume":"9","author":"B Mahesh","year":"2020","unstructured":"Mahesh B (2020) Machine learning algorithms-a review. Int J Sci Res (IJSR) 9:381\u2013386","journal-title":"Int J Sci Res (IJSR)"},{"key":"5098_CR20","doi-asserted-by":"publisher","first-page":"113251","DOI":"10.1016\/j.eswa.2020.113251","volume":"149","author":"J Rold\u00e1n","year":"2020","unstructured":"Rold\u00e1n J, Boubeta-Puig J, Luis Mart\u00ednez J, Ortiz G (2020) Integrating complex event processing and machine learning: An intelligent architecture for detecting iot security attacks. Expert Syst Appl 149:113251. https:\/\/doi.org\/10.1016\/j.eswa.2020.113251","journal-title":"Expert Syst Appl"},{"key":"5098_CR21","doi-asserted-by":"publisher","unstructured":"Suthishni DNP, Kumar KSS (2022) A Review on Machine Learning based Security Approaches in Intrusion Detection System. In: 2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), pp. 341\u2013348. https:\/\/doi.org\/10.23919\/INDIACom54597.2022.9763261","DOI":"10.23919\/INDIACom54597.2022.9763261"},{"key":"5098_CR22","doi-asserted-by":"crossref","unstructured":"Mohammed M, Khan MB, Bashier EBM (2016) Machine learning: algorithms and applications. CRC Press","DOI":"10.1201\/9781315371658"},{"key":"5098_CR23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1475-925X-5-51","volume":"5","author":"F Azuaje","year":"2006","unstructured":"Azuaje F, Witten IEF (2006) Witten ih, frank e: data mining: practical machine learning tools and techniques. Biomed Eng Online 5:1\u20132","journal-title":"Biomed Eng Online"},{"issue":"3","key":"5098_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s42979-021-00592-x","volume":"2","author":"IH Sarker","year":"2021","unstructured":"Sarker IH (2021) Machine learning: algorithms, real-world applications and research directions. SN Comput Sci 2(3):1\u201321","journal-title":"SN Comput Sci"},{"issue":"3","key":"5098_CR25","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1007\/BF00993309","volume":"16","author":"SL Salzberg","year":"1994","unstructured":"Salzberg SL (1994) C45: programs for machine learning by j ross quinlan. Mach Learn 16(3):235\u2013240. https:\/\/doi.org\/10.1007\/BF00993309","journal-title":"Mach Learn"},{"key":"5098_CR26","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V et al (2011) Scikit-learn: machine learning in python. J Mach Learn Res 12:2825\u20132830","journal-title":"J Mach Learn Res"},{"key":"5098_CR27","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010950718922","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L (2001) Random forests. Mach Learn 45:5\u201332. https:\/\/doi.org\/10.1023\/A:1010950718922","journal-title":"Mach Learn"},{"key":"5098_CR28","unstructured":"John GH, Langley P (1995) Estimating continuous distributions in bayesian classifiers. In: Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence. UAI\u201995, pp. 338\u2013345. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA"},{"key":"5098_CR29","unstructured":"Ruder S (2016) An overview of gradient descent optimization algorithms. arXiv preprint arXiv:1609.04747"},{"key":"5098_CR30","doi-asserted-by":"publisher","first-page":"102983","DOI":"10.1016\/j.jnca.2021.102983","volume":"178","author":"M Mohammadi","year":"2021","unstructured":"Mohammadi M, Rashid TA, Karim SHT, Aldalwie AHM, Tho QT, Bidaki M, Rahmani AM, Hosseinzadeh M (2021) A comprehensive survey and taxonomy of the svm-based intrusion detection systems. J Net Comput Appl 178:102983. https:\/\/doi.org\/10.1016\/j.jnca.2021.102983","journal-title":"J Net Comput Appl"},{"issue":"03","key":"5098_CR31","doi-asserted-by":"publisher","first-page":"186","DOI":"10.36548\/jscp.2020.3.007","volume":"2","author":"S Smys","year":"2020","unstructured":"Smys S, Chen JIZ, Shakya S (2020) Survey on neural network architectures with deep learning. J Soft Comput Parad (JSCP) 2(03):186\u2013194","journal-title":"J Soft Comput Parad (JSCP)"},{"key":"5098_CR32","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1016\/j.inffus.2021.11.011","volume":"81","author":"R Shwartz-Ziv","year":"2022","unstructured":"Shwartz-Ziv R, Armon A (2022) Tabular data: deep learning is not all you need. Inform Fus 81:84\u201390. https:\/\/doi.org\/10.1016\/j.inffus.2021.11.011","journal-title":"Inform Fus"},{"key":"5098_CR33","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1007\/978-981-19-3391-2_2","volume-title":"Computational Intelligence and data analytics","author":"M Roveri","year":"2023","unstructured":"Roveri M (2023) Is tiny deep learning the new deep learning? Computational Intelligence and data analytics. Springer, London, pp 23\u201339"},{"key":"5098_CR34","doi-asserted-by":"publisher","first-page":"201071","DOI":"10.1109\/ACCESS.2020.3035849","volume":"8","author":"B Mishra","year":"2020","unstructured":"Mishra B, Kertesz A (2020) The use of mqtt in m2m and iot systems: a survey. IEEE Access 8:201071\u2013201086","journal-title":"IEEE Access"},{"issue":"11","key":"5098_CR35","doi-asserted-by":"publisher","first-page":"4879","DOI":"10.3390\/app11114879","volume":"11","author":"D Silva","year":"2021","unstructured":"Silva D, Carvalho LI, Soares J, Sofia RC (2021) A performance analysis of internet of things networking protocols: evaluating mqtt, coap, opc ua. Appl Sci 11(11):4879","journal-title":"Appl Sci"},{"issue":"2","key":"5098_CR36","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/j.ijcip.2013.05.001","volume":"6","author":"N Goldenberg","year":"2013","unstructured":"Goldenberg N, Wool A (2013) Accurate modeling of modbus\/tcp for intrusion detection in scada systems. Int J Crit Infrast Protect 6(2):63\u201375. https:\/\/doi.org\/10.1016\/j.ijcip.2013.05.001","journal-title":"Int J Crit Infrast Protect"},{"key":"5098_CR37","doi-asserted-by":"publisher","first-page":"100470","DOI":"10.1016\/j.ijcip.2021.100470","volume":"35","author":"H Hui","year":"2021","unstructured":"Hui H, McLaughlin K, Sezer S (2021) Vulnerability analysis of s7 plcs: manipulating the security mechanism. Int J Crit Infrast Protect 35:100470. https:\/\/doi.org\/10.1016\/j.ijcip.2021.100470","journal-title":"Int J Crit Infrast Protect"},{"key":"5098_CR38","doi-asserted-by":"crossref","unstructured":"Lederer S, M\u00fcller C, Timmerer C (2012) Dynamic adaptive streaming over http dataset. In: Proceedings of the 3rd Multimedia Systems Conference, pp. 89\u201394","DOI":"10.1145\/2155555.2155570"},{"issue":"8","key":"5098_CR39","first-page":"1322","volume":"2","author":"C Mary","year":"2015","unstructured":"Mary C (2015) Shellshock attack on linux systems-bash. Int Res J Eng Technol 2(8):1322\u20131325","journal-title":"Int Res J Eng Technol"},{"issue":"4","key":"5098_CR40","doi-asserted-by":"publisher","first-page":"2057","DOI":"10.1007\/s11277-020-07139-y","volume":"112","author":"A Abdollahi","year":"2020","unstructured":"Abdollahi A, Fathi M (2020) An intrusion detection system on ping of death attacks in iot networks. Wirel Person Commun 112(4):2057\u20132070","journal-title":"Wirel Person Commun"},{"key":"5098_CR41","doi-asserted-by":"crossref","unstructured":"Thomas DR, Clayton R, Beresford AR (2017) 1000 days of udp amplification ddos attacks. In: 2017 APWG Symposium on Electronic Crime Research (eCrime), pp. 79\u201384. IEEE","DOI":"10.1109\/ECRIME.2017.7945057"},{"key":"5098_CR42","doi-asserted-by":"publisher","unstructured":"Peuster M, Karl H, van Rossem S (2016) Medicine: Rapid prototyping of production-ready network services in multi-pop environments. In: 2016 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), pp. 148\u2013153. https:\/\/doi.org\/10.1109\/NFV-SDN.2016.7919490","DOI":"10.1109\/NFV-SDN.2016.7919490"},{"key":"5098_CR43","unstructured":"Kaur K, Singh J, Ghumman NS (2014) Mininet as software defined networking testing platform. In: International Conference on Communication, Computing & Systems (ICCCS), pp. 139\u201342"},{"key":"5098_CR44","doi-asserted-by":"crossref","unstructured":"Grygorash O, Zhou Y, Jorgensen Z (2006) Minimum spanning tree based clustering algorithms. In: 2006 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI\u201906), pp. 73\u201381. IEEE","DOI":"10.1109\/ICTAI.2006.83"},{"key":"5098_CR45","doi-asserted-by":"crossref","unstructured":"Asadollahi S, Goswami B, Sameer M (2018) Ryu controller\u2019s scalability experiment on software defined networks. In: 2018 IEEE International Conference on Current Trends in Advanced Computing (ICCTAC), pp. 1\u20135. IEEE","DOI":"10.1109\/ICCTAC.2018.8370397"},{"key":"5098_CR46","doi-asserted-by":"publisher","unstructured":"Gomez-Miguelez I, Garcia-Saavedra A, Sutton P, Serrano P, Cano C, Leith D (2016) srslte: an open-source platform for lte evolution and experimentation, pp. 25\u201332. https:\/\/doi.org\/10.1145\/2980159.2980163","DOI":"10.1145\/2980159.2980163"},{"issue":"1","key":"5098_CR47","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/s10994-006-6226-1","volume":"63","author":"P Geurts","year":"2006","unstructured":"Geurts P, Ernst D, Wehenkel L (2006) Extremely randomized trees. Mach learn 63(1):3\u201342","journal-title":"Mach learn"},{"issue":"1","key":"5098_CR48","doi-asserted-by":"publisher","first-page":"38","DOI":"10.2214\/AJR.18.20224","volume":"212","author":"GS Handelman","year":"2019","unstructured":"Handelman GS, Kok HK, Chandra RV, Razavi AH, Huang S, Brooks M, Lee MJ, Asadi H (2019) Peering into the black box of artificial intelligence: evaluation metrics of machine learning methods. Am J Roentgenol 212(1):38\u201343","journal-title":"Am J Roentgenol"},{"key":"5098_CR49","doi-asserted-by":"publisher","first-page":"680","DOI":"10.1016\/j.future.2016.11.009","volume":"78","author":"R Roman","year":"2018","unstructured":"Roman R, Lopez J, Mambo M (2018) Mobile edge computing, fog et al.: a survey and analysis of security threats and challenges. Future Generat Comput Syst 78:680\u2013698. https:\/\/doi.org\/10.1016\/j.future.2016.11.009","journal-title":"Future Generat Comput Syst"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05098-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-023-05098-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05098-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,15]],"date-time":"2024-10-15T18:02:41Z","timestamp":1729015361000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-023-05098-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,3]]},"references-count":49,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2023,7]]}},"alternative-id":["5098"],"URL":"https:\/\/doi.org\/10.1007\/s11227-023-05098-2","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"value":"0920-8542","type":"print"},{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,3]]},"assertion":[{"value":"3 February 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 March 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Not applicable","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}