{"id":"https://openalex.org/W4390032896","doi":"https://doi.org/10.1007/s00521-023-09309-y","title":"Optimizing anomaly-based attack detection using classification machine learning","display_name":"Optimizing anomaly-based attack detection using classification machine learning","publication_year":2023,"publication_date":"2023-12-20","ids":{"openalex":"https://openalex.org/W4390032896","doi":"https://doi.org/10.1007/s00521-023-09309-y"},"language":"en","primary_location":{"id":"doi:10.1007/s00521-023-09309-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00521-023-09309-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00521-023-09309-y.pdf","source":{"id":"https://openalex.org/S147897268","display_name":"Neural Computing and Applications","issn_l":"0941-0643","issn":["0941-0643","1433-3058"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computing and Applications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s00521-023-09309-y.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093546215","display_name":"Hany Abdelghany Gouda","orcid":"https://orcid.org/0009-0005-0548-749X"},"institutions":[{"id":"https://openalex.org/I84058292","display_name":"Helwan University","ror":"https://ror.org/00h55v928","country_code":"EG","type":"education","lineage":["https://openalex.org/I84058292"]}],"countries":["EG"],"is_corresponding":true,"raw_author_name":"Hany Abdelghany Gouda","raw_affiliation_strings":["Information Systems Department, Faculty of Commerce and Business Administration, Helwan University, Cairo, Egypt"],"raw_orcid":"https://orcid.org/0009-0005-0548-749X","affiliations":[{"raw_affiliation_string":"Information Systems Department, Faculty of Commerce and Business Administration, Helwan University, Cairo, Egypt","institution_ids":["https://openalex.org/I84058292"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Mohamed Abdelslam Ahmed","orcid":"https://orcid.org/0000-0001-5545-0621"},"institutions":[{"id":"https://openalex.org/I84058292","display_name":"Helwan University","ror":"https://ror.org/00h55v928","country_code":"EG","type":"education","lineage":["https://openalex.org/I84058292"]}],"countries":["EG"],"is_corresponding":true,"raw_author_name":"Mohamed Abdelslam Ahmed","raw_affiliation_strings":["Information Systems Department, Faculty of Commerce and Business Administration, Helwan University, Cairo, Egypt"],"raw_orcid":"https://orcid.org/0000-0001-5545-0621","affiliations":[{"raw_affiliation_string":"Information Systems Department, Faculty of Commerce and Business Administration, Helwan University, Cairo, Egypt","institution_ids":["https://openalex.org/I84058292"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034587442","display_name":"Mohamed Roushdy","orcid":"https://orcid.org/0000-0002-9655-3229"},"institutions":[{"id":"https://openalex.org/I186217134","display_name":"Future University in Egypt","ror":"https://ror.org/03s8c2x09","country_code":"EG","type":"education","lineage":["https://openalex.org/I186217134"]}],"countries":["EG"],"is_corresponding":true,"raw_author_name":"Mohamed Ismail Roushdy","raw_affiliation_strings":["Computer Science Department, Faculty of Computers and Information Technology, Future University in Egypt, Cairo, Egypt"],"raw_orcid":"https://orcid.org/0000-0002-9655-3229","affiliations":[{"raw_affiliation_string":"Computer Science Department, Faculty of Computers and Information Technology, Future University in Egypt, Cairo, Egypt","institution_ids":["https://openalex.org/I186217134"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5034587442","https://openalex.org/A5093546215"],"corresponding_institution_ids":["https://openalex.org/I186217134","https://openalex.org/I84058292"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":2.696,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.90215976,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"36","issue":"6","first_page":"3239","last_page":"3257"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7998145818710327},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6717971563339233},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.652959406375885},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6095441579818726},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6078320741653442},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.5362581014633179},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.5249091386795044},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5174503922462463},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5154033899307251},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.46530681848526},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.43497946858406067},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40921229124069214}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7998145818710327},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6717971563339233},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.652959406375885},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6095441579818726},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6078320741653442},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.5362581014633179},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.5249091386795044},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5174503922462463},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5154033899307251},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.46530681848526},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.43497946858406067},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40921229124069214}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s00521-023-09309-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00521-023-09309-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00521-023-09309-y.pdf","source":{"id":"https://openalex.org/S147897268","display_name":"Neural Computing and Applications","issn_l":"0941-0643","issn":["0941-0643","1433-3058"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computing and Applications","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s00521-023-09309-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00521-023-09309-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00521-023-09309-y.pdf","source":{"id":"https://openalex.org/S147897268","display_name":"Neural Computing and Applications","issn_l":"0941-0643","issn":["0941-0643","1433-3058"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computing and Applications","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322165","display_name":"Helwan University","ror":"https://ror.org/00h55v928"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390032896.pdf","grobid_xml":"https://content.openalex.org/works/W4390032896.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W2150847526","https://openalex.org/W2592949994","https://openalex.org/W2618772563","https://openalex.org/W2678934292","https://openalex.org/W2958285686","https://openalex.org/W2973032842","https://openalex.org/W2986887798","https://openalex.org/W3000225415","https://openalex.org/W3037489623","https://openalex.org/W3042921284","https://openalex.org/W3089549039","https://openalex.org/W3089977857","https://openalex.org/W3091285855","https://openalex.org/W3126814579","https://openalex.org/W3137588659","https://openalex.org/W3153990350","https://openalex.org/W3155739706","https://openalex.org/W3168873038","https://openalex.org/W3185512663","https://openalex.org/W3211805421","https://openalex.org/W3216768217","https://openalex.org/W4212788843","https://openalex.org/W4308302001"],"related_works":["https://openalex.org/W2989490741","https://openalex.org/W3092506759","https://openalex.org/W2367545121","https://openalex.org/W4248881655","https://openalex.org/W2482165163","https://openalex.org/W3010890513","https://openalex.org/W120741642","https://openalex.org/W138569904","https://openalex.org/W2390914021","https://openalex.org/W2389417819"],"abstract_inverted_index":{"Abstract":[0],"One":[1],"of":[2,6,26,78,82,94,103,115,152,185,212],"the":[3,21,24,46,76,107,134,150,153,183],"significant":[4],"aspects":[5],"our":[7],"digital":[8],"world":[9],"is":[10,18,37,45],"that":[11],"data":[12,32,213],"are":[13,68],"literally":[14],"everywhere,":[15],"and":[16,33,43,59,88,120,136,142,177,214,218,232],"it":[17,35,220],"increasing.":[19],"On":[20],"other":[22],"hand,":[23],"number":[25],"cyberattacks":[27],"aiming":[28],"to":[29,191,203,207],"seize":[30],"this":[31,44,62],"use":[34],"illegally":[36],"increasing":[38],"at":[39],"an":[40],"exponential":[41],"rate,":[42],"challenge.":[47],"Therefore,":[48],"intrusion":[49],"detection":[50,159,223],"systems":[51],"(IDS)":[52],"have":[53],"attracted":[54],"considerable":[55],"interest":[56],"from":[57],"researchers":[58],"industries.":[60],"In":[61,181],"regard,":[63],"machine":[64],"learning":[65],"(ML)":[66],"techniques":[67],"playing":[69],"a":[70,146,193],"pivotal":[71],"role":[72],"as":[73],"they":[74],"put":[75],"responsibility":[77],"analyzing":[79],"enormous":[80,210],"amounts":[81,211],"data,":[83,135],"finding":[84],"patterns,":[85],"classifying":[86],"intrusions,":[87],"solving":[89],"issues":[90],"on":[91],"computers":[92],"instead":[93],"humans.":[95],"This":[96],"paper":[97],"implements":[98],"two":[99,113],"separate":[100],"classification":[101],"layers":[102],"ML-based":[104],"algorithms":[105,141,155,188],"with":[106],"recently":[108],"published":[109],"NF-UQ-NIDS-v2":[110],"dataset,":[111],"preprocessing":[112],"volumes":[114],"sample":[116],"records":[117],"(100":[118],"k":[119],"10":[121],"million),":[122],"utilizing":[123],"MinMaxScaler,":[124],"LabelEncoder,":[125],"selecting":[126],"superlative":[127],"features":[128],"by":[129],"recursive":[130],"feature":[131],"elimination,":[132],"normalizing":[133],"optimizing":[137],"hyper-parameters":[138],"for":[139,162,228,234],"classical":[140,154],"neural":[143,186,236],"networks.":[144,237],"With":[145],"small":[147],"dataset":[148],"volume,":[149],"results":[151],"layer":[156,184],"show":[157],"high":[158,222],"accuracy":[160],"rates":[161],"support":[163],"vector":[164],"(98.26%),":[165],"decision":[166],"tree":[167],"(98.78%),":[168],"random":[169],"forest":[170],"(99.07%),":[171],"K-nearest":[172],"neighbors":[173],"(98.16%),":[174],"CatBoost":[175],"(99.04%),":[176],"gradient":[178],"boosting":[179],"(98.80%).":[180],"addition,":[182],"network":[187],"has":[189],"proven":[190],"be":[192],"very":[194],"powerful":[195],"technology":[196],"when":[197],"using":[198],"deep":[199],"learning,":[200],"particularly":[201],"due":[202],"its":[204],"unique":[205],"ability":[206],"effectively":[208],"handle":[209],"detect":[215],"hidden":[216],"correlations":[217],"patterns;":[219],"showed":[221],"results,":[224],"which":[225],"were":[226],"(98.87%)":[227],"long":[229],"short-term":[230],"memory":[231],"(98.56%)":[233],"convolutional":[235]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":4}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}