{"id":"https://openalex.org/W7160692692","doi":"https://doi.org/10.1155/int/9925751","title":"Large\u2010Scale Benchmarking of Intrusion Detection Datasets With GPU\u2010Accelerated Data Pipelines, Complexity Analysis, and Model Evaluation","display_name":"Large\u2010Scale Benchmarking of Intrusion Detection Datasets With GPU\u2010Accelerated Data Pipelines, Complexity Analysis, and Model Evaluation","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7160692692","doi":"https://doi.org/10.1155/int/9925751"},"language":"en","primary_location":{"id":"doi:10.1155/int/9925751","is_oa":true,"landing_page_url":"https://doi.org/10.1155/int/9925751","pdf_url":null,"source":{"id":"https://openalex.org/S57950554","display_name":"International Journal of Intelligent Systems","issn_l":"0884-8173","issn":["0884-8173","1098-111X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1155/int/9925751","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082486081","display_name":"Marcelo V C Arag\u00e3o","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marcelo V. C. Arag\u00e3o","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-8999-8169","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135783014","display_name":"Felipe A. P. de Figueiredo","orcid":"https://orcid.org/0000-0002-2167-7286"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Felipe A. P. de Figueiredo","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-2167-7286","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133822250","display_name":"Samuel B. Mafra","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Samuel B. Mafra","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-5238-1795","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2500,"currency":"USD","value_usd":2500},"apc_paid":{"value":2500,"currency":"USD","value_usd":2500},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.57581084,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2026","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9075000286102295,"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":0.9075000286102295,"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":0.028200000524520874,"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/T10734","display_name":"Information and Cyber Security","score":0.006800000090152025,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/benchmarking","display_name":"Benchmarking","score":0.8429999947547913},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.6902999877929688},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5885000228881836},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.5246000289916992},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4244999885559082},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.387800008058548},{"id":"https://openalex.org/keywords/graphics","display_name":"Graphics","score":0.37070000171661377},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.35580000281333923}],"concepts":[{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.8429999947547913},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8122000098228455},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.6902999877929688},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5885000228881836},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5774000287055969},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5713000297546387},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5246000289916992},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4377000033855438},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4244999885559082},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.387800008058548},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.37070000171661377},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.35580000281333923},{"id":"https://openalex.org/C197640229","wikidata":"https://www.wikidata.org/wiki/Q2534066","display_name":"Predictability","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.329800009727478},{"id":"https://openalex.org/C2779851693","wikidata":"https://www.wikidata.org/wiki/Q183484","display_name":"Graphics processing unit","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.2888000011444092},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.2833999991416931},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.2667999863624573},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1155/int/9925751","is_oa":true,"landing_page_url":"https://doi.org/10.1155/int/9925751","pdf_url":null,"source":{"id":"https://openalex.org/S57950554","display_name":"International Journal of Intelligent Systems","issn_l":"0884-8173","issn":["0884-8173","1098-111X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1155/int/9925751","is_oa":true,"landing_page_url":"https://doi.org/10.1155/int/9925751","pdf_url":null,"source":{"id":"https://openalex.org/S57950554","display_name":"International Journal of Intelligent Systems","issn_l":"0884-8173","issn":["0884-8173","1098-111X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1277437854","display_name":null,"funder_award_id":"APQ-04523-23","funder_id":"https://openalex.org/F4320322980","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de Minas Gerais"},{"id":"https://openalex.org/G1427545861","display_name":"Center of Science for Development in Digital Agriculture - CCD-AD/SemeAr","funder_award_id":"22/09319-9","funder_id":"https://openalex.org/F4320320997","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo"},{"id":"https://openalex.org/G1480674285","display_name":null,"funder_award_id":"306199/2025-4","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"},{"id":"https://openalex.org/G1516301096","display_name":null,"funder_award_id":"APQ-03162-24","funder_id":"https://openalex.org/F4320322980","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de Minas Gerais"},{"id":"https://openalex.org/G1725971247","display_name":null,"funder_award_id":"311470/2021-1","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"},{"id":"https://openalex.org/G2515778752","display_name":null,"funder_award_id":"1245.010604/2020-14","funder_id":"https://openalex.org/F4320317482","funder_display_name":"Rede Nacional de Ensino e Pesquisa"},{"id":"https://openalex.org/G4266494009","display_name":null,"funder_award_id":"PPE-00124-23","funder_id":"https://openalex.org/F4320322980","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de Minas Gerais"},{"id":"https://openalex.org/G5182016929","display_name":null,"funder_award_id":"052/2023","funder_id":"https://openalex.org/F4320324388","funder_display_name":"Minist\u00e9rio da Ci\u00eancia e Tecnologia"},{"id":"https://openalex.org/G5393701633","display_name":"SAMURAI: smart 5G core and multiran integration","funder_award_id":"20/05127-2","funder_id":"https://openalex.org/F4320320997","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo"},{"id":"https://openalex.org/G6927355157","display_name":null,"funder_award_id":"APQ-01558-24","funder_id":"https://openalex.org/F4320322980","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de Minas Gerais"},{"id":"https://openalex.org/G7997372242","display_name":null,"funder_award_id":"APQ-05305-23","funder_id":"https://openalex.org/F4320322980","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de Minas Gerais"},{"id":"https://openalex.org/G8076259984","display_name":null,"funder_award_id":"1060/2, 01.25.0883.00","funder_id":"https://openalex.org/F4320322904","funder_display_name":"Financiadora de Estudos e Projetos"},{"id":"https://openalex.org/G8732967406","display_name":null,"funder_award_id":"RED-00194-23","funder_id":"https://openalex.org/F4320322980","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de Minas Gerais"}],"funders":[{"id":"https://openalex.org/F4320317482","display_name":"Rede Nacional de Ensino e Pesquisa","ror":"https://ror.org/04hztxs45"},{"id":"https://openalex.org/F4320320997","display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","ror":"https://ror.org/02ddkpn78"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"},{"id":"https://openalex.org/F4320322904","display_name":"Financiadora de Estudos e Projetos","ror":"https://ror.org/030w99567"},{"id":"https://openalex.org/F4320322980","display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de Minas Gerais","ror":"https://ror.org/00nc55f03"},{"id":"https://openalex.org/F4320324388","display_name":"Minist\u00e9rio da Ci\u00eancia e Tecnologia","ror":"https://ror.org/050zdnc69"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1988918299","https://openalex.org/W2034069122","https://openalex.org/W2082290707","https://openalex.org/W2118978333","https://openalex.org/W2342249984","https://openalex.org/W2737058386","https://openalex.org/W2770942607","https://openalex.org/W2799758613","https://openalex.org/W2901906577","https://openalex.org/W2924689635","https://openalex.org/W2945664952","https://openalex.org/W2963748489","https://openalex.org/W2973136425","https://openalex.org/W2993383518","https://openalex.org/W3014988774","https://openalex.org/W3032266608","https://openalex.org/W3035965352","https://openalex.org/W3085955590","https://openalex.org/W3126814579","https://openalex.org/W3165574415","https://openalex.org/W3183423075","https://openalex.org/W3196585642","https://openalex.org/W3211805421","https://openalex.org/W3216965265","https://openalex.org/W4210482263","https://openalex.org/W4211187780","https://openalex.org/W4214529720","https://openalex.org/W4220776964","https://openalex.org/W4236137412","https://openalex.org/W4242401062","https://openalex.org/W4253343410","https://openalex.org/W4288074729","https://openalex.org/W4316037971","https://openalex.org/W4320920814","https://openalex.org/W4361292119","https://openalex.org/W4376616081","https://openalex.org/W4382281941","https://openalex.org/W4383196772","https://openalex.org/W4389057640","https://openalex.org/W4390517705","https://openalex.org/W4392151675","https://openalex.org/W4396707597","https://openalex.org/W4400737507","https://openalex.org/W4402035331","https://openalex.org/W4402883814","https://openalex.org/W4403978362","https://openalex.org/W4412471001","https://openalex.org/W4413791227","https://openalex.org/W7151920923"],"related_works":[],"abstract_inverted_index":{"Intrusion":[0],"detection":[1],"systems":[2],"(IDSs)":[3],"are":[4,109],"critical":[5],"for":[6,69,197],"identifying":[7],"malicious":[8],"activity":[9],"in":[10],"computer":[11],"networks;":[12],"however,":[13],"the":[14,44,125,132,149,157,193],"evaluation":[15],"of":[16,47,56,107,138,148,175,192],"machine":[17],"learning":[18],"(ML)\u2013based":[19],"IDS":[20,199],"remains":[21],"inconsistent":[22],"and":[23,65,87],"fragmented.":[24],"Many":[25],"existing":[26],"studies":[27],"rely":[28],"on":[29],"outdated":[30],"datasets,":[31],"neglect":[32],"computational":[33],"complexity,":[34],"or":[35],"use":[36],"limited":[37],"performance":[38],"metrics.":[39],"Additionally,":[40],"few":[41],"works":[42],"leverage":[43],"full":[45,126],"potential":[46],"modern":[48],"graphics":[49],"processing":[50,181],"unit":[51,182],"(GPU)":[52],"acceleration.":[53],"The":[54],"objective":[55],"this":[57],"study":[58],"is":[59],"to":[60,111,124,172],"establish":[61],"a":[62,136,188],"scalable,":[63],"reproducible,":[64],"standardized":[66],"benchmarking":[67],"framework":[68],"intrusion":[70],"detection.":[71],"We":[72],"present":[73],"an":[74],"end\u2010to\u2010end,":[75],"GPU\u2010accelerated":[76,158],"pipeline":[77],"that":[78,103,156],"integrates":[79],"automated":[80],"data":[81],"preprocessing,":[82],"intrinsic":[83],"dataset":[84],"complexity":[85,153],"analysis,":[86],"multiobjective":[88],"hyperparameter":[89],"optimization":[90],"(HPO)":[91],"across":[92],"more":[93],"than":[94],"70":[95],"publicly":[96],"available":[97],"datasets.":[98],"Our":[99],"numerical":[100],"findings":[101],"demonstrate":[102],"stratified":[104],"sampling":[105],"rates":[106],"10%":[108],"sufficient":[110],"maintain":[112],"statistical":[113],"signal":[114],"integrity,":[115],"with":[116,178],"class":[117],"probability":[118],"deviations":[119],"remaining":[120],"below":[121],"0.01":[122,147],"relative":[123],"population.":[127],"Furthermore,":[128],"feature\u2010reduced":[129],"configurations":[130],"decrease":[131],"model":[133],"size":[134],"by":[135,170],"median":[137],"60%":[139],"while":[140],"maintaining":[141],"weighted":[142],"F":[143],"1":[144],"scores":[145],"within":[146],"baseline.":[150],"Finally,":[151],"experimental":[152],"analysis":[154],"reveals":[155],"modeling":[159],"stages":[160],"achieve":[161],"empirical":[162],"time\u2010invariance":[163],"(":[164],"O":[165],"(1)),":[166],"reducing":[167],"training":[168],"latency":[169],"up":[171],"two":[173],"orders":[174],"magnitude":[176],"compared":[177],"traditional":[179],"central":[180],"(CPU)":[183],"workflows.":[184],"These":[185],"contributions":[186],"offer":[187],"rigorous":[189],"quantitative":[190],"view":[191],"performance\u2010efficiency":[194],"trade\u2010offs":[195],"essential":[196],"next\u2010generation":[198],"evaluation.":[200]},"counts_by_year":[],"updated_date":"2026-07-20T07:56:41.581041","created_date":"2026-05-10T00:00:00"}
