{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T17:36:02Z","timestamp":1780421762094,"version":"3.54.1"},"reference-count":85,"publisher":"Springer Science and Business Media LLC","issue":"18","license":[{"start":{"date-parts":[[2023,6,19]],"date-time":"2023-06-19T00:00:00Z","timestamp":1687132800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,6,19]],"date-time":"2023-06-19T00:00:00Z","timestamp":1687132800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"published-print":{"date-parts":[[2023,12]]},"DOI":"10.1007\/s11227-023-05444-4","type":"journal-article","created":{"date-parts":[[2023,6,19]],"date-time":"2023-06-19T12:02:06Z","timestamp":1687176126000},"page":"21265-21309","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["Improved discrete salp swarm algorithm using exploration and exploitation techniques for feature selection in intrusion detection systems"],"prefix":"10.1007","volume":"79","author":[{"given":"Malek","family":"Barhoush","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bilal H.","family":"Abed-alguni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nour Elhuda A.","family":"Al-qudah","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,6,19]]},"reference":[{"key":"5444_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2019.107094","author":"MZ Gunduz","year":"2020","unstructured":"Gunduz MZ, Das R (2020) Cyber-security on smart grid: threats and potential solutions. Comput Netw. https:\/\/doi.org\/10.1016\/j.comnet.2019.107094","journal-title":"Comput Netw"},{"key":"5444_CR2","doi-asserted-by":"publisher","first-page":"10","DOI":"10.3837\/tiis.2018.10.024","volume":"12","author":"S Maza","year":"2018","unstructured":"Maza S, Touahria M (2018) Feature selection algorithms in intrusion detection system: a survey. KSII Trans Internet Inf Syst 12:10. https:\/\/doi.org\/10.3837\/tiis.2018.10.024","journal-title":"KSII Trans Internet Inf Syst"},{"key":"5444_CR3","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.neucom.2017.11.077","volume":"300","author":"J Cai","year":"2018","unstructured":"Cai J, Luo J, Wang S, Yang S (2018) Feature selection in machine learning: a new perspective. Neurocomputing 300:70\u201379. https:\/\/doi.org\/10.1016\/j.neucom.2017.11.077","journal-title":"Neurocomputing"},{"key":"5444_CR4","doi-asserted-by":"publisher","DOI":"10.1145\/3102304.3102325","author":"M Mafarja","year":"2017","unstructured":"Mafarja M, Eleyan D, Abdullah S, Mirjalili S (2017) S-shaped vs V-shaped transfer functions for ant lion optimization algorithm in feature selection problem. ACM Int Conf Proc Ser. https:\/\/doi.org\/10.1145\/3102304.3102325","journal-title":"ACM Int Conf Proc Ser"},{"key":"5444_CR5","doi-asserted-by":"crossref","unstructured":"Asghari Varzaneh Z, Hosseini S, Javidi MM (2023) A novel binary horse herd optimization algorithm for feature selection problem. Multimed. Tools Appl 1\u201335","DOI":"10.1007\/s11042-023-15023-7"},{"key":"5444_CR6","doi-asserted-by":"crossref","unstructured":"Qu L, He W, Li J, Zhang H, Yang C, Xie B (2023) Explicit and size-adaptive PSO-based feature selection for classification. Swarm Evol Comput, p. 101249","DOI":"10.1016\/j.swevo.2023.101249"},{"key":"5444_CR7","doi-asserted-by":"publisher","first-page":"140936","DOI":"10.1109\/ACCESS.2020.3013617","volume":"8","author":"Y Gao","year":"2020","unstructured":"Gao Y, Zhou Y, Luo Q (2020) An efficient binary equilibrium optimizer algorithm for feature selection. IEEE Access 8:140936\u2013140963. https:\/\/doi.org\/10.1109\/ACCESS.2020.3013617","journal-title":"IEEE Access"},{"key":"5444_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.119612","volume":"218","author":"AM Vommi","year":"2023","unstructured":"Vommi AM, Battula TK (2023) A hybrid filter-wrapper feature selection using Fuzzy KNN based on Bonferroni mean for medical datasets classification: a COVID-19 case study. Expert Syst Appl 218:119612","journal-title":"Expert Syst Appl"},{"key":"5444_CR9","doi-asserted-by":"crossref","unstructured":"Neha N, Raman MRG, Somu N, Senthilnathan R, Sriram VSS (2019) An improved feedforward neural network using salp swarm optimization technique for the design of intrusion detection system for computer network. Comput Intell Pattern Recognit","DOI":"10.1007\/978-981-13-9042-5_74"},{"key":"5444_CR10","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-021-03697-5","author":"S Gavel","year":"2021","unstructured":"Gavel S, Raghuvanshi AS, Tiwari S (2021) Distributed intrusion detection scheme using dual-axis dimensionality reduction for Internet of things (IoT). J Supercomput. https:\/\/doi.org\/10.1007\/s11227-021-03697-5","journal-title":"J Supercomput"},{"key":"5444_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.advengsoft.2017.07.002","author":"S Mirjalili","year":"2017","unstructured":"Mirjalili S, Gandomi AH, Mirjalili SZ, Saremi S, Faris H, Mirjalili SM (2017) Salp Swarm algorithm: a bio-inspired optimizer for engineering design problems. Adv Eng Softw. https:\/\/doi.org\/10.1016\/j.advengsoft.2017.07.002","journal-title":"Adv Eng Softw"},{"key":"5444_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2019.113122","volume":"145","author":"M Tubishat","year":"2019","unstructured":"Tubishat M, Idris N, Shuib L, Abushariah M, Mirjalili S (2019) Improved Salp Swarm algorithm based on opposition based learning and novel local search algorithm for feature selection. Expert Syst Appl 145:113122. https:\/\/doi.org\/10.1016\/j.eswa.2019.113122","journal-title":"Expert Syst Appl"},{"key":"5444_CR13","doi-asserted-by":"publisher","unstructured":"Zhou X, Wu Z, Wang H (2012) Elite opposition-based differential evolution for solving large-scale optimization problems and its implementation on GPU https:\/\/doi.org\/10.1109\/PDCAT.2012.70.","DOI":"10.1109\/PDCAT.2012.70"},{"key":"5444_CR14","doi-asserted-by":"crossref","unstructured":"Zhang J, Zhang G, Kong M, Zhang T (2023) Adaptive infinite impulse response system identification using an enhanced golden jackal optimization. J Supercomput pp. 1\u201326","DOI":"10.21203\/rs.3.rs-1941783\/v1"},{"key":"5444_CR15","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/S0305-0548(97)00031-2","volume":"24","author":"N Mladenovi\u0107","year":"1997","unstructured":"Mladenovi\u0107 N, Hansen P (1997) Variable neighborhood search. Comput Oper Res 24:11. https:\/\/doi.org\/10.1016\/S0305-0548(97)00031-2","journal-title":"Comput Oper Res"},{"key":"5444_CR16","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1007\/s11227-021-04050-6","volume":"78","author":"F Alkhateeb","year":"2022","unstructured":"Alkhateeb F, Abed-alguni BH, Al-rousan MH (2022) Discrete hybrid cuckoo search and simulated annealing algorithm for solving the job shop scheduling problem. J Supercomput 78:4. https:\/\/doi.org\/10.1007\/s11227-021-04050-6","journal-title":"J Supercomput"},{"key":"5444_CR17","doi-asserted-by":"publisher","unstructured":"Yang XS (2012) Flower pollination algorithm for global optimization. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7445 LNCS, doi: https:\/\/doi.org\/10.1007\/978-3-642-32894-7_27","DOI":"10.1007\/978-3-642-32894-7_27"},{"key":"5444_CR18","unstructured":"Ibrahim HT, Mazher WJ, U\u00e7an ON, Bayat O (2017) Feature selection using salp swarm algorithm for real biomedical datasets"},{"key":"5444_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2019.113122","author":"M Tubishat","year":"2020","unstructured":"Tubishat M, Idris N, Shuib L, Abushariah MAM, Mirjalili S (2020) Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection. Expert Syst Appl. https:\/\/doi.org\/10.1016\/j.eswa.2019.113122","journal-title":"Expert Syst Appl"},{"issue":"4","key":"5444_CR20","doi-asserted-by":"publisher","first-page":"1639","DOI":"10.1007\/s10845-021-01899-5","volume":"34","author":"Y Sun","year":"2023","unstructured":"Sun Y, Pan J-S, Hu P, Chu S-C (2023) Enhanced equilibrium optimizer algorithm applied in job shop scheduling problem. J Intell Manuf 34(4):1639\u20131665","journal-title":"J Intell Manuf"},{"key":"5444_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.105190","volume":"191","author":"A Faramarzi","year":"2020","unstructured":"Faramarzi A, Heidarinejad M, Stephens B, Mirjalili S (2020) Equilibrium optimizer: a novel optimization algorithm. Knowl-Based Syst 191:105190","journal-title":"Knowl-Based Syst"},{"key":"5444_CR22","doi-asserted-by":"publisher","DOI":"10.3390\/computation9060068","author":"ZM Elgamal","year":"2021","unstructured":"Elgamal ZM, Yasin NM, Sabri AQM, Sihwail R, Tubishat M, Jarrah H (2021) Improved equilibrium optimization algorithm using elite opposition-based learning and new local search strategy for feature selection in medical datasets. Computation. https:\/\/doi.org\/10.3390\/computation9060068","journal-title":"Computation"},{"key":"5444_CR23","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1016\/j.future.2019.02.028","volume":"97","author":"AA Heidari","year":"2019","unstructured":"Heidari AA, Mirjalili S, Faris H, Aljarah I, Mafarja M, Chen H (2019) Harris hawks optimization: algorithm and applications. Futur Gener Comput Syst 97:849\u2013872","journal-title":"Futur Gener Comput Syst"},{"key":"5444_CR24","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3006473","author":"R Sihwail","year":"2020","unstructured":"Sihwail R, Omar K, Ariffin KAZ, Tubishat M (2020) Improved Harris Hawks optimization using elite opposition-based learning and novel search mechanism for feature selection. IEEE Access. https:\/\/doi.org\/10.1109\/ACCESS.2020.3006473","journal-title":"IEEE Access"},{"key":"5444_CR25","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.knosys.2015.12.022","volume":"96","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S (2016) SCA: a sine cosine algorithm for solving optimization problems. Knowl-based Syst 96:120\u2013133","journal-title":"Knowl-based Syst"},{"key":"5444_CR26","doi-asserted-by":"crossref","unstructured":"Abed-Alguni BH, Alawad NA, Al-Betar MA, Paul D (2022) Opposition-based sine cosine optimizer utilizing refraction learning and variable neighborhood search for feature selection. Appl Intell pp. 1\u201337","DOI":"10.1007\/s10489-022-04201-z"},{"key":"5444_CR27","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","volume":"69","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46\u201361","journal-title":"Adv Eng Softw"},{"key":"5444_CR28","first-page":"3","volume":"4","author":"BH Abed-alguni","year":"2018","unstructured":"Abed-alguni BH, Barhoush M (2018) Distributed grey wolf optimizer for numerical optimization problems. Jordanian J Comput Inf Technol 4:3","journal-title":"Jordanian J Comput Inf Technol"},{"key":"5444_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107113","volume":"102","author":"BH Abed-alguni","year":"2021","unstructured":"Abed-alguni BH, Alawad NA (2021) Distributed grey wolf optimizer for scheduling of workflow applications in cloud environments. Appl Soft Comput 102:107113","journal-title":"Appl Soft Comput"},{"issue":"02","key":"5444_CR30","doi-asserted-by":"publisher","first-page":"1750012","DOI":"10.1142\/S1469026817500122","volume":"16","author":"S Zhang","year":"2017","unstructured":"Zhang S, Luo Q, Zhou Y (2017) Hybrid grey wolf optimizer using elite opposition-based learning strategy and simplex method. Int J Comput Intell Appl 16(02):1750012","journal-title":"Int J Comput Intell Appl"},{"key":"5444_CR31","doi-asserted-by":"crossref","unstructured":"Yildiz BS, Pholdee N, Bureerat S, Yildiz AR, Sait SM (2021) Enhanced grasshopper optimization algorithm using elite opposition-based learning for solving real-world engineering problems. Eng Comput pp. 1\u201313","DOI":"10.1007\/s00366-021-01368-w"},{"issue":"1","key":"5444_CR32","first-page":"56","volume":"3","author":"BH Abed-alguni","year":"2017","unstructured":"Abed-alguni BH (2017) Bat Q-learning algorithm. Jordanian J Comput Inf Technol 3(1):56\u201377","journal-title":"Jordanian J Comput Inf Technol"},{"key":"5444_CR33","doi-asserted-by":"crossref","unstructured":"Haruna Z, Mu\u2019azu MB, Abubilal KA, Tijani SA (2017) Development of a modified bat algorithm using elite opposition\u2014Based learning. In: 2017 IEEE 3rd International Conference on Electro-Technology for National Development (NIGERCON), 2017, pp. 144\u2013151","DOI":"10.1109\/NIGERCON.2017.8281888"},{"key":"5444_CR34","doi-asserted-by":"crossref","unstructured":"Paiva FAP, Silva CRM, Leite IVO, Marcone MHF, Costa JAF (2017) Modified bat algorithm with cauchy mutation and elite opposition-based learning. In :2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI), pp. 1\u20136","DOI":"10.1109\/LA-CCI.2017.8285715"},{"issue":"11","key":"5444_CR35","doi-asserted-by":"publisher","first-page":"1564","DOI":"10.1080\/0305215X.2014.982634","volume":"47","author":"P Guo","year":"2015","unstructured":"Guo P, Cheng W, Wang Y (2015) Parallel machine scheduling with step-deteriorating jobs and setup times by a hybrid discrete cuckoo search algorithm. Eng Optim 47(11):1564\u20131585","journal-title":"Eng Optim"},{"key":"5444_CR36","doi-asserted-by":"crossref","unstructured":"Luo Q, Zhou Y, Xie J, Ma M, Li L (2014) Discrete bat algorithm for optimal problem of permutation flow shop scheduling. Sci World J","DOI":"10.1155\/2014\/630280"},{"key":"5444_CR37","doi-asserted-by":"crossref","unstructured":"Alawad NA, Abed-alguni BH (2021) Discrete Jaya with refraction learning and three mutation methods for the permutation flow shop scheduling problem. J Supercomput pp. 1\u201322","DOI":"10.1007\/s11227-021-03998-9"},{"issue":"7","key":"5444_CR38","doi-asserted-by":"publisher","first-page":"3293","DOI":"10.1007\/s00500-021-06665-6","volume":"26","author":"BH Abed-alguni","year":"2022","unstructured":"Abed-alguni BH, Paul D (2022) Island-based Cuckoo Search with elite opposition-based learning and multiple mutation methods for solving optimization problems. Soft Comput 26(7):3293\u20133312","journal-title":"Soft Comput"},{"key":"5444_CR39","unstructured":"Alkhateeb F, Abed-Alguni BH (2017) A hybrid cuckoo search and simulated annealing algorithm"},{"key":"5444_CR40","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1016\/j.knosys.2018.01.017","volume":"145","author":"AL Aro Bolaji","year":"2018","unstructured":"Aro Bolaji AL, Bamigbola AF, Shola PB (2018) Late acceptance hill climbing algorithm for solving patient admission scheduling problem. Knowl-Based Syst 145:197\u2013206. https:\/\/doi.org\/10.1016\/j.knosys.2018.01.017","journal-title":"Knowl-Based Syst"},{"issue":"2","key":"5444_CR41","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1016\/j.jksuci.2018.05.003","volume":"32","author":"BH Abed-alguni","year":"2020","unstructured":"Abed-alguni BH, Alkhateeb F (2020) Intelligent hybrid cuckoo search and \u03b2-hill climbing algorithm. J King Saud Univ Comput Inf Sci 32(2):159\u2013173. https:\/\/doi.org\/10.1016\/j.jksuci.2018.05.003","journal-title":"J King Saud Univ Comput Inf Sci"},{"issue":"12","key":"5444_CR42","doi-asserted-by":"publisher","first-page":"6771","DOI":"10.1007\/s13369-017-2873-8","volume":"43","author":"BH Abed-alguni","year":"2018","unstructured":"Abed-alguni BH (2018) Action-selection method for reinforcement learning based on cuckoo search algorithm. Arab J Sci Eng 43(12):6771\u20136785","journal-title":"Arab J Sci Eng"},{"key":"5444_CR43","doi-asserted-by":"publisher","DOI":"10.1515\/jisys-2018-0331","author":"BH Abed-Alguni","year":"2020","unstructured":"Abed-Alguni BH, Paul DJ (2020) Hybridizing the cuckoo search algorithm with different mutation operators for numerical optimization problems. J Syst Intell. https:\/\/doi.org\/10.1515\/jisys-2018-0331","journal-title":"J Syst Intell"},{"issue":"15","key":"5444_CR44","doi-asserted-by":"publisher","first-page":"10167","DOI":"10.1007\/s00500-021-05939-3","volume":"25","author":"BH Abed-alguni","year":"2021","unstructured":"Abed-alguni BH, Alawad NA, Barhoush M, Hammad R (2021) Exploratory cuckoo search for solving single-objective optimization problems. Soft Comput 25(15):10167\u201310180","journal-title":"Soft Comput"},{"key":"5444_CR45","doi-asserted-by":"publisher","first-page":"125076","DOI":"10.1109\/ACCESS.2020.3007291","volume":"8","author":"Q Al-Tashi","year":"2020","unstructured":"Al-Tashi Q, Abdulkadir SJ, Rais HM, Mirjalili S, Alhussian H (2020) Approaches to multi-objective feature selection: a systematic literature review. IEEE Access 8:125076\u2013125096","journal-title":"IEEE Access"},{"issue":"3","key":"5444_CR46","doi-asserted-by":"publisher","first-page":"3157","DOI":"10.1007\/s11227-022-04763-2","volume":"79","author":"S Xie","year":"2023","unstructured":"Xie S, Zhang Y, Lv D, Chen X, Lu J, Liu J (2023) A new improved maximal relevance and minimal redundancy method based on feature subset. J Supercomput 79(3):3157\u20133180","journal-title":"J Supercomput"},{"key":"5444_CR47","doi-asserted-by":"crossref","unstructured":"Abed-Alguni BH, Paul D, Hammad R (2022) Improved Salp swarm algorithm for solving single-objective continuous optimization problems. Appl Intell pp. 1\u201320","DOI":"10.1007\/s10489-022-03269-x"},{"key":"5444_CR48","doi-asserted-by":"publisher","unstructured":"Tizhoosh HR (2005) Opposition-based learning: A new scheme for machine intelligence. Proc-Int Conf Comput Intell Model Control Autom CIMCA 2005 Int Conf Intell Agents Web Technol Internet 1:695\u2013701 https:\/\/doi.org\/10.1109\/cimca.2005.1631345.","DOI":"10.1109\/cimca.2005.1631345"},{"key":"5444_CR49","doi-asserted-by":"publisher","DOI":"10.1016\/j.jksuci.2018.06.003","author":"AE Hegazy","year":"2020","unstructured":"Hegazy AE, Makhlouf MA, El-Tawel GS (2020) Improved salp swarm algorithm for feature selection. J King Saud Univ-Comput Inf Sci. https:\/\/doi.org\/10.1016\/j.jksuci.2018.06.003","journal-title":"J King Saud Univ-Comput Inf Sci"},{"key":"5444_CR50","doi-asserted-by":"publisher","unstructured":"Sharafaldin I, Lashkari AH, Ghorbani AA (2018) Toward generating a new intrusion detection dataset and intrusion traffic characterization. In: ICISSP 2018-Proceedings of the 4th International Conference on Information Systems Security and Privacy, 2018, 2018-Janua, doi: https:\/\/doi.org\/10.5220\/0006639801080116","DOI":"10.5220\/0006639801080116"},{"key":"5444_CR51","unstructured":"Panigrahi R, Borah, S (2018) A detailed analysis of CICIDS2017 dataset for designing Intrusion Detection Systems. Int J Eng Technol 7(3):24"},{"key":"5444_CR52","doi-asserted-by":"publisher","unstructured":"Tavallaee M, Bagheri E, Lu W, Ghorbani AA (2009) A detailed analysis of the KDD CUP 99 data set https:\/\/doi.org\/10.1109\/CISDA.2009.5356528","DOI":"10.1109\/CISDA.2009.5356528"},{"key":"5444_CR53","doi-asserted-by":"crossref","unstructured":"MontazeriShatoori M, Davidson L, Kaur G, Lashkari AH (2020) Detection of doh tunnels using time-series classification of encrypted traffic. In: 2020 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC\/PiCom\/CBDCom\/CyberSciTech), 2020, pp. 63\u201370","DOI":"10.1109\/DASC-PICom-CBDCom-CyberSciTech49142.2020.00026"},{"issue":"2","key":"5444_CR54","first-page":"46","volume":"8","author":"YM Banadaki","year":"2020","unstructured":"Banadaki YM (2020) Detecting malicious dns over https traffic in domain name system using machine learning classifiers. J Comput Sci Appl 8(2):46\u201355","journal-title":"J Comput Sci Appl"},{"issue":"3","key":"5444_CR55","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1109\/MPRV.2018.03367731","volume":"17","author":"Y Meidan","year":"2018","unstructured":"Meidan Y et al (2018) N-BaIoT: network-based detection of IoT Botnet attacks using deep autoencoders. IEEE Pervasive Comput 17(3):12\u201322","journal-title":"IEEE Pervasive Comput"},{"key":"5444_CR56","first-page":"65","volume":"2","author":"MT Jafar","year":"2021","unstructured":"Jafar MT, Al-Fawa\u2019reh M, Al-Hrahsheh Z, Jafar ST (2021) Analysis and investigation of malicious DNS queries using CIRA-CIC-DoHBrw-2020 dataset. Manchester J Artif Intell Appl Sci 2:65\u201370","journal-title":"Manchester J Artif Intell Appl Sci"},{"key":"5444_CR57","doi-asserted-by":"crossref","unstructured":"Sharafaldin I, Lashkari AH, Hakak S, Ghorbani AA (2019) Developing realistic distributed denial of service (DDoS) attack dataset and taxonomy. 2019 Int Carnahan Conf Secur Technol pp. 1\u20138","DOI":"10.1109\/CCST.2019.8888419"},{"key":"5444_CR58","doi-asserted-by":"publisher","unstructured":"Moustafa N, Slay J (2015) UNSW-NB15: a comprehensive data set for network intrusion detection systems (UNSW-NB15 network data set). https:\/\/doi.org\/10.1109\/MilCIS.2015.7348942","DOI":"10.1109\/MilCIS.2015.7348942"},{"key":"5444_CR59","unstructured":"Zoghi Z, Serpen G (2021) Unsw-nb15 computer security dataset: analysis through visualization. arXiv Prepr. arXiv2101.05067"},{"key":"5444_CR60","first-page":"2018","volume":"1","author":"CL Tan","year":"2018","unstructured":"Tan CL (2018) Phishing dataset for machine learning: feature evaluation. Mendeley Data 1:2018","journal-title":"Mendeley Data"},{"key":"5444_CR61","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2019.113103","author":"N Neggaz","year":"2020","unstructured":"Neggaz N, Ewees AA, Elaziz MA, Mafarja M (2020) Boosting salp swarm algorithm by sine cosine algorithm and disrupt operator for feature selection. Expert Syst Appl. https:\/\/doi.org\/10.1016\/j.eswa.2019.113103","journal-title":"Expert Syst Appl"},{"key":"5444_CR62","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-016-2385-6","author":"S Gu","year":"2018","unstructured":"Gu S, Cheng R, Jin Y (2018) Feature selection for high-dimensional classification using a competitive swarm optimizer. Soft Comput. https:\/\/doi.org\/10.1007\/s00500-016-2385-6","journal-title":"Soft Comput"},{"key":"5444_CR63","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953","author":"NV Chawla","year":"2002","unstructured":"Chawla NV, Bowyer KW, Hall LO, Kegelmeyer WP (2002) SMOTE: synthetic minority over-sampling technique. J Artif Intell Res. https:\/\/doi.org\/10.1613\/jair.953","journal-title":"J Artif Intell Res"},{"key":"5444_CR64","doi-asserted-by":"publisher","DOI":"10.1007\/s12065-021-00565-2","author":"J Miao","year":"2021","unstructured":"Miao J, Zhu W (2021) Precision\u2013recall curve (PRC) classification trees. Evol Intell. https:\/\/doi.org\/10.1007\/s12065-021-00565-2","journal-title":"Evol Intell"},{"issue":"1","key":"5444_CR65","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1214\/aoms\/1177731944","volume":"11","author":"M Friedman","year":"1940","unstructured":"Friedman M (1940) A comparison of alternative tests of significance for the problem of $m$ rankings. Ann Math Stat 11(1):86\u201392. https:\/\/doi.org\/10.1214\/aoms\/1177731944","journal-title":"Ann Math Stat"},{"key":"5444_CR66","doi-asserted-by":"publisher","first-page":"128687","DOI":"10.1109\/ACCESS.2021.3112169","volume":"9","author":"GS Thejas","year":"2021","unstructured":"Thejas GS, Garg R, Iyengar SS, Sunitha NR, Badrinath P, Chennupati S (2021) Metric and accuracy ranked feature inclusion: hybrids of filter and wrapper feature selection approaches. IEEE Access 9:128687\u2013128701","journal-title":"IEEE Access"},{"key":"5444_CR67","doi-asserted-by":"publisher","unstructured":"Smucker MD, Allan J, Carterette B (2007) A comparison of statistical significance tests for information retrieval evaluation https:\/\/doi.org\/10.1145\/1321440.1321528","DOI":"10.1145\/1321440.1321528"},{"key":"5444_CR68","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-018-1158-6","author":"GI Sayed","year":"2018","unstructured":"Sayed GI, Khoriba G, Haggag MH (2018) A novel chaotic salp swarm algorithm for global optimization and feature selection. Appl Intell. https:\/\/doi.org\/10.1007\/s10489-018-1158-6","journal-title":"Appl Intell"},{"key":"5444_CR69","doi-asserted-by":"publisher","first-page":"12042","DOI":"10.1088\/1742-6596\/1874\/1\/012042","volume":"1874","author":"NS Sulaiman","year":"2021","unstructured":"Sulaiman NS et al (2021) Intrusion detection system techniques\u202f: a review. J Phys Conf Ser 1874:12042. https:\/\/doi.org\/10.1088\/1742-6596\/1874\/1\/012042","journal-title":"J Phys Conf Ser"},{"key":"5444_CR70","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113873","author":"M Tubishat","year":"2021","unstructured":"Tubishat M et al (2021) Dynamic Salp swarm algorithm for feature selection. Expert Syst Appl. https:\/\/doi.org\/10.1016\/j.eswa.2020.113873","journal-title":"Expert Syst Appl"},{"key":"5444_CR71","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.118439","author":"M Alazab","year":"2022","unstructured":"Alazab M, Khurma RA, Awajan A, Camacho D (2022) A new intrusion detection system based on Moth-Flame Optimizer algorithm. Expert Syst Appl. https:\/\/doi.org\/10.1016\/j.eswa.2022.118439","journal-title":"Expert Syst Appl"},{"key":"5444_CR72","doi-asserted-by":"publisher","DOI":"10.3390\/math10060999","author":"A Alzaqebah","year":"2022","unstructured":"Alzaqebah A, Aljarah I, Al-Kadi O, Dama\u0161evi\u010dius R (2022) A modified grey wolf optimization algorithm for an intrusion detection system. Mathematics. https:\/\/doi.org\/10.3390\/math10060999","journal-title":"Mathematics"},{"key":"5444_CR73","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04103-1","author":"QM Alzubi","year":"2020","unstructured":"Alzubi QM, Anbar M, Alqattan ZNM, Al-Betar MA, Abdullah R (2020) Intrusion detection system based on a modified binary grey wolf optimisation. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04103-1","journal-title":"Neural Comput Appl"},{"key":"5444_CR74","doi-asserted-by":"publisher","DOI":"10.3390\/info13070314","author":"Y Zhang","year":"2022","unstructured":"Zhang Y, Zhang H, Zhang B (2022) An effective ensemble automatic feature selection method for network intrusion detection. Inf. https:\/\/doi.org\/10.3390\/info13070314","journal-title":"Inf"},{"key":"5444_CR75","doi-asserted-by":"publisher","DOI":"10.3390\/s23010550","author":"YN Rao","year":"2023","unstructured":"Rao YN, Suresh Babu K (2023) An imbalanced generative adversarial network-based approach for network intrusion detection in an imbalanced dataset. Sensors (Basel). https:\/\/doi.org\/10.3390\/s23010550","journal-title":"Sensors (Basel)"},{"key":"5444_CR76","doi-asserted-by":"publisher","unstructured":"Machoke M, Mbelwa J, Agbinya J, Sam AE (2022) Performance Comparison of Ensemble Learning and Supervised Algorithms in Classifying Multi-label Network Traffic Flow. Eng Technol Appl Sci Res. https:\/\/doi.org\/10.48084\/etasr.4852","DOI":"10.48084\/etasr.4852"},{"key":"5444_CR77","doi-asserted-by":"publisher","unstructured":"Nuiaa RR, Manickam S, Alsaeedi AH, Alomari ES (2022) A new proactive feature selection model based on the enhanced optimization algorithms to detect DRDoS attacks. Int J Electr Comput Eng. https:\/\/doi.org\/10.11591\/ijece.v12i2.pp1869-1880","DOI":"10.11591\/ijece.v12i2.pp1869-1880"},{"key":"5444_CR78","doi-asserted-by":"publisher","unstructured":"Nguyen AT, Park M (2022) Detection of DoH Tunneling using Semi-supervised Learning method. In: International Conference on Information Networking https:\/\/doi.org\/10.1109\/ICOIN53446.2022.9687157","DOI":"10.1109\/ICOIN53446.2022.9687157"},{"key":"5444_CR79","doi-asserted-by":"publisher","DOI":"10.3390\/bdcc6040112","author":"NF Abdulsattar","year":"2022","unstructured":"Abdulsattar NF et al (2022) Botnet detection employing a dilated convolutional autoencoder classifier with the aid of hybrid shark and bear smell optimization algorithm-based feature selection in FANETs. Big Data Cogn Comput. https:\/\/doi.org\/10.3390\/bdcc6040112","journal-title":"Big Data Cogn Comput"},{"key":"5444_CR80","doi-asserted-by":"publisher","DOI":"10.1016\/j.jisa.2022.103405","author":"MA Talukder","year":"2023","unstructured":"Talukder MA et al (2023) A dependable hybrid machine learning model for network intrusion detection. J Secur Appl Inf. https:\/\/doi.org\/10.1016\/j.jisa.2022.103405","journal-title":"J Secur Appl Inf"},{"key":"5444_CR81","doi-asserted-by":"crossref","unstructured":"Imad M, Abul Hassan M, Hussain Bangash S, Naimullah (2022) A comparative analysis of intrusion detection in IoT network using machine learning. Studies in Big Data 111","DOI":"10.1007\/978-3-031-05752-6_10"},{"issue":"3","key":"5444_CR82","doi-asserted-by":"publisher","first-page":"3998","DOI":"10.1007\/s11227-021-04015-9","volume":"78","author":"MJ Goldanloo","year":"2022","unstructured":"Goldanloo MJ, Gharehchopogh FS (2022) A hybrid OBL-based firefly algorithm with symbiotic organisms search algorithm for solving continuous optimization problems. J Supercomput 78(3):3998\u20134031","journal-title":"J Supercomput"},{"issue":"4","key":"5444_CR83","first-page":"319","volume":"11","author":"BH Abed-Alguni","year":"2019","unstructured":"Abed-Alguni BH, Klaib AF, Nahar KMO (2019) Island-based whale optimisation algorithm for continuous optimisation problems. Int J Reason Intell Syst 11(4):319\u2013329","journal-title":"Int J Reason Intell Syst"},{"issue":"4","key":"5444_CR84","doi-asserted-by":"publisher","first-page":"3213","DOI":"10.1007\/s13369-020-05141-x","volume":"46","author":"NA Alawad","year":"2021","unstructured":"Alawad NA, Abed-alguni BH (2021) Discrete island-based cuckoo search with highly disruptive polynomial mutation and opposition-based learning strategy for scheduling of workflow applications in cloud environments. Arab J Sci Eng 46(4):3213\u20133233. https:\/\/doi.org\/10.1007\/s13369-020-05141-x","journal-title":"Arab J Sci Eng"},{"issue":"1","key":"5444_CR85","first-page":"57","volume":"17","author":"BH Abed-alguni","year":"2019","unstructured":"Abed-alguni BH (2019) Island-based cuckoo search with highly disruptive polynomial mutation. Int J Artif Intell 17(1):57\u201382","journal-title":"Int J Artif Intell"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05444-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-023-05444-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05444-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,20]],"date-time":"2023-10-20T21:11:22Z","timestamp":1697836282000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-023-05444-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,19]]},"references-count":85,"journal-issue":{"issue":"18","published-print":{"date-parts":[[2023,12]]}},"alternative-id":["5444"],"URL":"https:\/\/doi.org\/10.1007\/s11227-023-05444-4","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"value":"0920-8542","type":"print"},{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,19]]},"assertion":[{"value":"27 May 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 June 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":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}