{"id":"https://openalex.org/W7225834229","doi":"https://doi.org/10.20944/preprints202611.1052.v1","title":"TRUST-IDS: Shift-Aware, Adversarially Robust and Explainable Network Intrusion Detection via Multi-Objective Evolutionary Configuration","display_name":"TRUST-IDS: Shift-Aware, Adversarially Robust and Explainable Network Intrusion Detection via Multi-Objective Evolutionary Configuration","publication_year":2026,"publication_date":"2026-11-10","ids":{"openalex":"https://openalex.org/W7225834229","doi":"https://doi.org/10.20944/preprints202611.1052.v1"},"language":"en","primary_location":{"id":"doi:10.20944/preprints202611.1052.v1","doi":"https://doi.org/10.20944/preprints202611.1052.v1","is_oa":true,"landing_page_url":"https://doi.org/10.20944/preprints202611.1052.v1","pdf_url":null,"source":{"id":"https://openalex.org/S6309402219","display_name":"Preprints.org","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.20944/preprints202611.1052.v1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044963180","display_name":"Jamal Sami Zraqou","orcid":"https://orcid.org/0000-0001-9060-7188","observed_orcids":["https://orcid.org/0000-0001-9060-7188"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jamal Zraqou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135673765","display_name":"Ayman J. Alnsour","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ayman J. Alnsour","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"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":0.9911999702453613,"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":0.9911999702453613,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.00430000014603138,"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/T12391","display_name":"Artificial Immune Systems Applications","score":0.001500000013038516,"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":[],"concepts":[{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.7405999898910522},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6599000096321106},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6597999930381775},{"id":"https://openalex.org/C2781251061","wikidata":"https://www.wikidata.org/wiki/Q5416089","display_name":"Evasion (ethics)","level":3,"score":0.61080002784729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5411999821662903},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5394999980926514},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.5274999737739563},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47760000824928284},{"id":"https://openalex.org/C158251709","wikidata":"https://www.wikidata.org/wiki/Q354025","display_name":"Intrusion","level":2,"score":0.476500004529953},{"id":"https://openalex.org/C2778924833","wikidata":"https://www.wikidata.org/wiki/Q7064603","display_name":"Novelty detection","level":3,"score":0.45080000162124634},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4368000030517578},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.34040001034736633},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.3292999863624573},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32170000672340393},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.3154999911785126},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.31049999594688416},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C137524506","wikidata":"https://www.wikidata.org/wiki/Q2247688","display_name":"Anomaly-based intrusion detection system","level":3,"score":0.2800000011920929},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2515999972820282},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.20944/preprints202611.1052.v1","doi":"https://doi.org/10.20944/preprints202611.1052.v1","is_oa":true,"landing_page_url":"https://doi.org/10.20944/preprints202611.1052.v1","pdf_url":null,"source":{"id":"https://openalex.org/S6309402219","display_name":"Preprints.org","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.20944/preprints202611.1052.v1","doi":"https://doi.org/10.20944/preprints202611.1052.v1","is_oa":true,"landing_page_url":"https://doi.org/10.20944/preprints202611.1052.v1","pdf_url":null,"source":{"id":"https://openalex.org/S6309402219","display_name":"Preprints.org","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Machine-learning":[0],"intrusion":[1],"detectors":[2],"that":[3,69],"score":[4],"highly":[5],"on":[6,89,93],"benchmarks":[7],"often":[8],"degrade":[9],"in":[10],"deployment,":[11],"where":[12],"they":[13],"meet":[14],"unseen":[15,107],"attack":[16,72,108,120],"families,":[17],"evasive":[18],"adversaries":[19],"and":[20,53,58,61,91,97,112,162],"analysts":[21],"who":[22],"need":[23],"stable":[24],"explanations.":[25],"We":[26],"present":[27],"TRUST-IDS,":[28],"which":[29],"fuses":[30],"a":[31,40,66,74,117,131,158],"LightGBM":[32,166],"branch":[33],"hardened":[34],"by":[35],"constraint-aware":[36],"adversarial":[37],"augmentation":[38,49],"with":[39,146,157],"quantile-calibrated":[41],"k-nearest-neighbour":[42],"novelty":[43],"branch.":[44],"NSGA-II":[45],"configures":[46],"its":[47],"hyper-parameters,":[48],"strength,":[50],"fusion":[51],"weight":[52],"threshold":[54],"to":[55,62],"maximise":[56],"macro-F1":[57],"robust":[59],"detection":[60,115],"minimise":[63],"complexity,":[64],"using":[65],"validation":[67],"split":[68],"withholds":[70],"entire":[71],"families;":[73],"knee-point":[75],"rule":[76],"selects":[77],"the":[78,100,128,149,152],"deployed":[79],"configuration.":[80],"On":[81,135],"NSL-KDD":[82],"(five":[83],"seeds),":[84],"TRUST-IDS":[85],"reached":[86],"91.90%":[87],"accuracy":[88,155],"KDDTest+":[90],"86.11%":[92],"KDDTest-21,":[94],"versus":[95],"79.64%":[96],"61.30%":[98],"for":[99],"best":[101,153],"baseline.":[102],"It":[103],"detected":[104],"88.19%":[105],"of":[106,130],"types":[109],"(baseline":[110,125],"45.65%)":[111],"retained":[113],"89.0%":[114],"under":[116],"black-box":[118],"evasion":[119],"at":[121,127,167],"\u03b5":[122],"=":[123],"0.05":[124],"60.7%),":[126],"cost":[129],"12.59%":[132],"false-positive":[133],"rate.":[134],"UNSW-NB15,":[136],"shift-aware":[137],"selection":[138],"over-fired":[139],"because":[140],"benign":[141],"test":[142],"traffic":[143],"had":[144],"drifted;":[145],"conventional":[147],"selection,":[148],"architecture":[150],"matched":[151],"baseline":[154],"(87.45%)":[156],"six-fold":[159],"smaller":[160],"booster":[161],"improved":[163],"robustness":[164],"over":[165],"every":[168],"budget.":[169],"A":[170],"label-free":[171],"novelty-quantile":[172],"diagnostic":[173],"distinguishes":[174],"these":[175],"two":[176],"regimes.":[177]},"counts_by_year":[],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2026-11-12T00:00:00"}
