{"id":"https://openalex.org/W7083699032","doi":"https://doi.org/10.1007/s12243-025-01118-9","title":"A versatile XAI-based framework for efficient and explainable intrusion detection systems","display_name":"A versatile XAI-based framework for efficient and explainable intrusion detection systems","publication_year":2025,"publication_date":"2025-09-29","ids":{"openalex":"https://openalex.org/W7083699032","doi":"https://doi.org/10.1007/s12243-025-01118-9"},"language":"en","primary_location":{"id":"doi:10.1007/s12243-025-01118-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12243-025-01118-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12243-025-01118-9.pdf","source":{"id":"https://openalex.org/S164884734","display_name":"Annals of Telecommunications","issn_l":"0003-4347","issn":["0003-4347","1958-9395"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["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":"Annals of Telecommunications","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/s12243-025-01118-9.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Beny Nugraha","orcid":null},"institutions":[{"id":"https://openalex.org/I2610724","display_name":"Chemnitz University of Technology","ror":"https://ror.org/00a208s56","country_code":"DE","type":"education","lineage":["https://openalex.org/I2610724"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Beny Nugraha","raw_affiliation_strings":["Chair of Communication Networks, Technische Universit\u00e4t Chemnitz, Chemnitz, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chair of Communication Networks, Technische Universit\u00e4t Chemnitz, Chemnitz, Germany","institution_ids":["https://openalex.org/I2610724"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Abhishek Venkatesh Jnanashree","orcid":null},"institutions":[{"id":"https://openalex.org/I2610724","display_name":"Chemnitz University of Technology","ror":"https://ror.org/00a208s56","country_code":"DE","type":"education","lineage":["https://openalex.org/I2610724"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Abhishek Venkatesh Jnanashree","raw_affiliation_strings":["Chair of Communication Networks, Technische Universit\u00e4t Chemnitz, Chemnitz, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chair of Communication Networks, Technische Universit\u00e4t Chemnitz, Chemnitz, Germany","institution_ids":["https://openalex.org/I2610724"]}]},{"author_position":"last","author":{"id":null,"display_name":"Thomas Bauschert","orcid":null},"institutions":[{"id":"https://openalex.org/I2610724","display_name":"Chemnitz University of Technology","ror":"https://ror.org/00a208s56","country_code":"DE","type":"education","lineage":["https://openalex.org/I2610724"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas Bauschert","raw_affiliation_strings":["Chair of Communication Networks, Technische Universit\u00e4t Chemnitz, Chemnitz, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chair of Communication Networks, Technische Universit\u00e4t Chemnitz, Chemnitz, Germany","institution_ids":["https://openalex.org/I2610724"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2610724"],"apc_list":{"value":2790,"currency":"USD","value_usd":2790},"apc_paid":{"value":2790,"currency":"USD","value_usd":2790},"fwci":12.0688,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.98453428,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"80","issue":"11-12","first_page":"1095","last_page":"1120"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.73089998960495,"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"}},"topics":[{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.73089998960495,"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"}},{"id":"https://openalex.org/T13067","display_name":"Geological Modeling and Analysis","score":0.026900000870227814,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14204","display_name":"Railway Systems and Materials Science","score":0.012199999764561653,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.7864000201225281},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.7275000214576721},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5934000015258789},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5166000127792358},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.45649999380111694},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.4440999925136566},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4083999991416931},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.3686000108718872}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7864000201225281},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7595000267028809},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.7275000214576721},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6019999980926514},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5934000015258789},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5773000121116638},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5166000127792358},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.45649999380111694},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.4440999925136566},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4083999991416931},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3752000033855438},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3686000108718872},{"id":"https://openalex.org/C137524506","wikidata":"https://www.wikidata.org/wiki/Q2247688","display_name":"Anomaly-based intrusion detection system","level":3,"score":0.358599990606308},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.35679998993873596},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3522999882698059},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3434000015258789},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.3294000029563904},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32359999418258667},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.322299987077713},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.29679998755455017},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s12243-025-01118-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12243-025-01118-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12243-025-01118-9.pdf","source":{"id":"https://openalex.org/S164884734","display_name":"Annals of Telecommunications","issn_l":"0003-4347","issn":["0003-4347","1958-9395"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["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":"Annals of Telecommunications","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s12243-025-01118-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12243-025-01118-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12243-025-01118-9.pdf","source":{"id":"https://openalex.org/S164884734","display_name":"Annals of Telecommunications","issn_l":"0003-4347","issn":["0003-4347","1958-9395"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["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":"Annals of Telecommunications","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320311034","display_name":"Technische Universit\u00e4t Chemnitz","ror":"https://ror.org/00a208s56"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7083699032.pdf","grobid_xml":"https://content.openalex.org/works/W7083699032.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W2282821441","https://openalex.org/W2295598076","https://openalex.org/W2353267094","https://openalex.org/W2528491735","https://openalex.org/W2981731882","https://openalex.org/W2982682021","https://openalex.org/W3109369928","https://openalex.org/W3114887082","https://openalex.org/W3121453273","https://openalex.org/W3200314112","https://openalex.org/W3216835679","https://openalex.org/W4285058242","https://openalex.org/W4285248859","https://openalex.org/W4295854586","https://openalex.org/W4313116287","https://openalex.org/W4379382625","https://openalex.org/W4381281419","https://openalex.org/W4381615611","https://openalex.org/W4382281941","https://openalex.org/W4384517581","https://openalex.org/W4388933390","https://openalex.org/W4390548160","https://openalex.org/W4390692351","https://openalex.org/W4393159983","https://openalex.org/W4394795122","https://openalex.org/W4400489863","https://openalex.org/W4401247017","https://openalex.org/W4401359544","https://openalex.org/W4406892568","https://openalex.org/W4411111458","https://openalex.org/W4411205861"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Artificial":[1],"intelligence":[2],"(AI)-based":[3],"intrusion":[4],"detection":[5,214],"systems":[6],"(IDSs)":[7],"markedly":[8],"advance":[9],"network":[10],"security":[11],"by":[12,97],"leveraging":[13],"machine":[14],"learning":[15,19],"(ML)":[16],"and":[17,40,58,99,151,175,216],"deep":[18],"(DL)":[20],"models":[21],"for":[22,121],"accurate,":[23],"adaptive":[24],"threat":[25],"detection.":[26],"Their":[27],"main":[28],"drawback,":[29],"however,":[30],"is":[31,140],"an":[32,49,81,187,205],"inherent":[33],"\u201cblack-box\u201d":[34],"character":[35],"that":[36,54,129,212],"impedes":[37],"trust,":[38],"traceability,":[39],"regulatory":[41],"compliance.":[42],"To":[43,136],"overcome":[44],"this":[45,139],"limitation,":[46],"we":[47],"propose":[48],"efficient":[50],"explainable-AI":[51],"(XAI)":[52],"framework":[53,143],"enhances":[55],"both":[56],"robustness":[57],"interpretability.":[59],"The":[60],"two-stage":[61],"process":[62],"first":[63,142],"couples":[64],"a":[65,88,107,118,125],"statistical":[66],"selector":[67],"(ANOVA)":[68],"with":[69],"global":[70],"SHAP":[71,98],"scores":[72],"to":[73,144,202],"retain":[74],"only":[75],"the":[76,102,115,141,182],"ten":[77],"most":[78],"informative":[79],"features,":[80],"approximately":[82],"70%":[83],"dimensionality":[84],"reduction,":[85],"then":[86],"retrains":[87],"lightweight":[89],"XGBoost":[90],"detector":[91],"whose":[92],"decisions":[93],"are":[94],"explained":[95],"locally":[96],"LIME.":[100],"Cross-validating":[101],"two":[103],"explanation":[104,122,198],"modalities":[105],"adds":[106],"reliability":[108],"check":[109],"absent":[110],"from":[111,200],"earlier":[112],"hybrids,":[113],"while":[114,195],"inclusion":[116],"of":[117,190],"time-efficiency":[119],"evaluation":[120],"generation":[123],"provides":[124],"new":[126],"performance":[127],"dimension":[128],"prior":[130],"XAI-IDS":[131],"studies":[132],"have":[133],"not":[134],"addressed.":[135],"our":[137],"knowledge,":[138],"jointly":[145],"apply":[146],"dual-stage":[147],"statistical\u2013model-based":[148],"feature":[149],"selection":[150],"SHAP\u2013LIME":[152],"cross-validation":[153],"in":[154,224],"IDS,":[155],"enabling":[156],"near-real-time":[157,218],"explainability":[158],"without":[159],"sacrificing":[160],"accuracy.":[161],"Comprehensive":[162],"experiments":[163],"on":[164],"three":[165],"representative":[166],"traces,":[167],"CIC-DDoS2019":[168],"(legacy":[169],"IP":[170],"DDoS),":[171],"CICIoT2023":[172],"(IoT":[173],"malware),":[174],"5":[176],"G":[177],"PFCP":[178],"(control-plane":[179],"attacks),":[180],"confirm":[181],"framework\u2019s":[183],"versatility:":[184],"it":[185],"sustains":[186],"F1":[188],"Score":[189],"at":[191],"least":[192],"99":[193],"%":[194,207],"accelerating":[196],"LIME":[197],"time":[199],"36":[201],"4.9":[203],"s,":[204],"87":[206],"speed-up.":[208],"These":[209],"results":[210],"demonstrate":[211],"high":[213],"accuracy":[215],"transparent,":[217],"interpretability":[219],"can":[220],"be":[221],"achieved":[222],"simultaneously":[223],"modern":[225],"IDS":[226],"deployments.":[227]},"counts_by_year":[{"year":2026,"cited_by_count":11}],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-10T00:00:00"}