{"id":"https://openalex.org/W7225346644","doi":"https://doi.org/10.1007/s44163-026-02677-z","title":"Leakage aware gated non local fusion network for calibrated IIoT SCADA cyberattack detection supporting cyber risk management and operational resilience","display_name":"Leakage aware gated non local fusion network for calibrated IIoT SCADA cyberattack detection supporting cyber risk management and operational resilience","publication_year":2026,"publication_date":"2026-11-05","ids":{"openalex":"https://openalex.org/W7225346644","doi":"https://doi.org/10.1007/s44163-026-02677-z"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-026-02677-z","doi":"https://doi.org/10.1007/s44163-026-02677-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-02677-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-026-02677-z.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1","oarl"],"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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s44163-026-02677-z.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119276453","display_name":"Zulkernain Doha","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I311071055","display_name":"Grand Canyon University","ror":"https://ror.org/014kv8184","country_code":"US","type":"education","lineage":["https://openalex.org/I311071055"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zulkernain Doha","raw_affiliation_strings":["Faculty of Business and Technology, Grand Canyon University, Phoenix, AZ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Business and Technology, Grand Canyon University, Phoenix, AZ, USA","institution_ids":["https://openalex.org/I311071055"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160753533","display_name":"Ariful Alam Mojumder","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I128365640","display_name":"Regis University","ror":"https://ror.org/043ae9h44","country_code":"US","type":"education","lineage":["https://openalex.org/I128365640"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ariful Alam Mojumder","raw_affiliation_strings":["MBA in Management Science, Project Leadership and Management, Regis University, Denver, CO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MBA in Management Science, Project Leadership and Management, Regis University, Denver, CO, USA","institution_ids":["https://openalex.org/I128365640"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107707668","display_name":"Kaosar Hossain","orcid":"https://orcid.org/0009-0002-2530-1726","observed_orcids":["https://orcid.org/0009-0002-2530-1726"]},"institutions":[{"id":"https://openalex.org/I4405267770","display_name":"International American University","ror":"https://ror.org/0493eqn45","country_code":"US","type":"education","lineage":["https://openalex.org/I4405267770"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaosar Hossain","raw_affiliation_strings":["International American University, Los Angeles, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"International American University, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I4405267770"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160916828","display_name":"Md Sayem Ahammed","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I165075387","display_name":"Trine University","ror":"https://ror.org/038e0dv78","country_code":"US","type":"education","lineage":["https://openalex.org/I165075387"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Md Sayem Ahammed","raw_affiliation_strings":["Master of Science in Business Analytics, Trine University, Angola, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Master of Science in Business Analytics, Trine University, Angola, IN, USA","institution_ids":["https://openalex.org/I165075387"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135788427","display_name":"Mohammad Sazzad Hossain","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I165075387","display_name":"Trine University","ror":"https://ror.org/038e0dv78","country_code":"US","type":"education","lineage":["https://openalex.org/I165075387"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammad Sazzad Hossain","raw_affiliation_strings":["Master of Science in Business Analytics, College of Graduate and Professional Studies, Trine University, Angola, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Master of Science in Business Analytics, College of Graduate and Professional Studies, Trine University, Angola, IN, USA","institution_ids":["https://openalex.org/I165075387"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135752726","display_name":"Maria Kabtia","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I165075387","display_name":"Trine University","ror":"https://ror.org/038e0dv78","country_code":"US","type":"education","lineage":["https://openalex.org/I165075387"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maria Kabtia","raw_affiliation_strings":["Master of Science in Business Analytics, College of Graduate and Professional Studies, Trine University, Angola, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Master of Science in Business Analytics, College of Graduate and Professional Studies, Trine University, Angola, IN, USA","institution_ids":["https://openalex.org/I165075387"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133277519","display_name":"Samia Akter","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I165075387","display_name":"Trine University","ror":"https://ror.org/038e0dv78","country_code":"US","type":"education","lineage":["https://openalex.org/I165075387"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samia Akter","raw_affiliation_strings":["Master of Science in Business Analytics, College of Graduate and Professional Studies, Trine University, Angola, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Master of Science in Business Analytics, College of Graduate and Professional Studies, Trine University, Angola, IN, USA","institution_ids":["https://openalex.org/I165075387"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137877222","display_name":"Md Shahiduzzaman","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I165075387","display_name":"Trine University","ror":"https://ror.org/038e0dv78","country_code":"US","type":"education","lineage":["https://openalex.org/I165075387"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Md Shahiduzzaman","raw_affiliation_strings":["Master of Science in Business Analytics, College of Graduate and Professional Studies, Phoenix Education Center, Trine University, Tempe, AZ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Master of Science in Business Analytics, College of Graduate and Professional Studies, Phoenix Education Center, Trine University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I165075387"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5150744910","display_name":"Dinar Ibn Raihan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I78137547","display_name":"Ibb University","ror":"https://ror.org/00fhcxc56","country_code":"YE","type":"education","lineage":["https://openalex.org/I78137547"]}],"countries":["YE"],"is_corresponding":true,"raw_author_name":"Dinar Ibn Raihan","raw_affiliation_strings":["Department of Computer Science and Engineering, Ibb University, Ibb, Yemen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Ibb University, Ibb, Yemen","institution_ids":["https://openalex.org/I78137547"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5150744910"],"corresponding_institution_ids":["https://openalex.org/I78137547"],"apc_list":{"value":1590,"currency":"USD","value_usd":1590},"apc_paid":{"value":1590,"currency":"USD","value_usd":1590},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6","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":0.9940999746322632,"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":0.9940999746322632,"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/T10917","display_name":"Smart Grid Security and Resilience","score":0.002099999925121665,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"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":0.0006000000284984708,"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/industrial-internet-of-things-security","display_name":"Industrial Internet of Things security","score":0.8640000224113464},{"id":"https://openalex.org/keywords/intrusion-detection","display_name":"intrusion detection","score":0.9070000052452087},{"id":"https://openalex.org/keywords/temperature-scaling","display_name":"temperature scaling","score":0.765999972820282},{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.6240000128746033},{"id":"https://openalex.org/keywords/focal-loss","display_name":"focal loss","score":0.6159999966621399},{"id":"https://openalex.org/keywords/cybersecurity-risk-management","display_name":"cyber risk management","score":0.6579999923706055},{"id":"https://openalex.org/keywords/operational-resilience","display_name":"operational resilience","score":0.9860000014305115},{"id":"https://openalex.org/keywords/confidence-calibration","display_name":"confidence calibration","score":0.593999981880188},{"id":"https://openalex.org/keywords/attack-classification","display_name":"attack classification","score":0.32600000500679016}],"concepts":[{"id":"https://openalex.org/C113863187","wikidata":"https://www.wikidata.org/wiki/Q17498","display_name":"SCADA","level":2,"score":0.7071999907493591},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6866999864578247},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6110000014305115},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.5605999827384949},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.44190001487731934},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.43380001187324524},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.38960000872612},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.3693000078201294},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.36329999566078186},{"id":"https://openalex.org/C48105269","wikidata":"https://www.wikidata.org/wiki/Q1141160","display_name":"Header","level":2,"score":0.35740000009536743},{"id":"https://openalex.org/C32896092","wikidata":"https://www.wikidata.org/wiki/Q189447","display_name":"Risk management","level":2,"score":0.3555000126361847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3528999984264374},{"id":"https://openalex.org/C20136886","wikidata":"https://www.wikidata.org/wiki/Q749647","display_name":"Interoperability","level":2,"score":0.35089999437332153},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.34779998660087585},{"id":"https://openalex.org/C145804949","wikidata":"https://www.wikidata.org/wiki/Q478123","display_name":"Situation awareness","level":2,"score":0.34369999170303345},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3431999981403351},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.33489999175071716},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.32739999890327454},{"id":"https://openalex.org/C193519340","wikidata":"https://www.wikidata.org/wiki/Q891179","display_name":"Data loss","level":2,"score":0.32010000944137573},{"id":"https://openalex.org/C92446256","wikidata":"https://www.wikidata.org/wiki/Q3306762","display_name":"Data validation","level":2,"score":0.31790000200271606},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C147494362","wikidata":"https://www.wikidata.org/wiki/Q2078905","display_name":"Troubleshooting","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C129763632","wikidata":"https://www.wikidata.org/wiki/Q1454667","display_name":"Network management","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.28029999136924744},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.2754000127315521},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.2687000036239624},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.26739999651908875},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.26010000705718994},{"id":"https://openalex.org/C62555980","wikidata":"https://www.wikidata.org/wiki/Q1460420","display_name":"Emergency management","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.25049999356269836},{"id":"https://openalex.org/C40071531","wikidata":"https://www.wikidata.org/wiki/Q2513962","display_name":"Industrial control system","level":3,"score":0.2502000033855438}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-026-02677-z","doi":"https://doi.org/10.1007/s44163-026-02677-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-02677-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-026-02677-z.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1","oarl"],"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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ff88a5a1016d4c808f9b06693ee80c8e","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/ff88a5a1016d4c808f9b06693ee80c8e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Artificial Intelligence, Vol 6, Iss 1 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-026-02677-z","doi":"https://doi.org/10.1007/s44163-026-02677-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-02677-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-026-02677-z.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1","oarl"],"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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4943999946117401,"id":"https://metadata.un.org/sdg/9"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225346644.pdf","grobid_xml":"https://content.openalex.org/works/W7225346644.grobid-xml"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W2810443361","https://openalex.org/W2894066856","https://openalex.org/W2902264868","https://openalex.org/W3006520740","https://openalex.org/W3155995009","https://openalex.org/W3157915803","https://openalex.org/W4386881452","https://openalex.org/W4389639285","https://openalex.org/W4391733508","https://openalex.org/W4391971011","https://openalex.org/W4393420577","https://openalex.org/W4394938966","https://openalex.org/W4400850302","https://openalex.org/W4403295017","https://openalex.org/W4407432954","https://openalex.org/W4408410698","https://openalex.org/W4408670415","https://openalex.org/W4408793049","https://openalex.org/W4409052567","https://openalex.org/W4409153671","https://openalex.org/W4410640280","https://openalex.org/W4410934984","https://openalex.org/W4411487280","https://openalex.org/W4411580992","https://openalex.org/W4414157027","https://openalex.org/W4414524233","https://openalex.org/W7110452706","https://openalex.org/W7119523666","https://openalex.org/W7124437936","https://openalex.org/W7124922659","https://openalex.org/W7128200862","https://openalex.org/W7128427596","https://openalex.org/W7128677769","https://openalex.org/W7128710263","https://openalex.org/W7128784124","https://openalex.org/W7129583614","https://openalex.org/W7130363991","https://openalex.org/W7130850309","https://openalex.org/W7134201277","https://openalex.org/W7139945670","https://openalex.org/W7139948689","https://openalex.org/W7139978384","https://openalex.org/W7140090504","https://openalex.org/W7155353800","https://openalex.org/W7163192639","https://openalex.org/W7163213613","https://openalex.org/W7163690758","https://openalex.org/W7164818363","https://openalex.org/W7166088314"],"related_works":["https://openalex.org/W7128427596","https://openalex.org/W7159561540","https://openalex.org/W7163881826","https://openalex.org/W7166873127","https://openalex.org/W7222650247","https://openalex.org/W7128784124","https://openalex.org/W4394872552","https://openalex.org/W7214171979","https://openalex.org/W7210278444","https://openalex.org/W7213653955"],"abstract_inverted_index":{"Industrial":[0],"Internet":[1],"of":[2,23,91],"Things":[3],"(IIoT)":[4],"and":[5,20,39,58,82,126,138,146,157,163,190,207,218,231,244,250,282,299],"SCADA":[6],"systems":[7],"are":[8,33,132],"increasingly":[9],"exposed":[10],"to":[11,35],"cyberattacks":[12],"that":[13,286],"can":[14,46,87],"threaten":[15],"data":[16],"integrity,":[17],"cyber-physical":[18],"availability,":[19],"the":[21,89,97,113,194,261,274],"continuity":[22,309],"industrial":[24,295],"operations.":[25],"Beyond":[26],"their":[27],"immediate":[28],"technical":[29,284],"consequences,":[30],"such":[31],"threats":[32],"relevant":[34],"cyber":[36,296],"risk":[37,297],"management":[38],"operational":[40,300],"resilience":[41,301],"because":[42],"reliable":[43],"security":[44],"monitoring":[45],"provide":[47],"decision-relevant":[48],"information":[49],"for":[50,108],"prioritizing":[51],"potentially":[52],"disruptive":[53],"incidents.":[54],"However,":[55],"many":[56],"machine-learning":[57],"deep-learning":[59],"intrusion":[60,110],"detectors":[61],"process":[62],"tabular":[63],"network-flow":[64],"records":[65,119],"as":[66,267],"flat":[67],"vectors":[68],"or":[69,308],"arbitrary":[70],"feature":[71,155,182],"sequences,":[72],"while":[73],"preprocessing":[74,143],"leakage,":[75],"severe":[76],"class":[77],"imbalance,":[78],"weak":[79],"minority-attack":[80],"detection,":[81],"poorly":[83],"calibrated":[84,199,283],"confidence":[85],"estimates":[86],"limit":[88],"reliability":[90],"reported":[92],"performance.":[93],"This":[94],"study":[95],"proposes":[96],"Gated":[98],"Non-local":[99],"Fusion":[100],"Network":[101],"(GNF),":[102],"a":[103,254,279],"compact":[104],"semantic":[105,154],"tabular-flow":[106],"model":[107],"five-class":[109],"detection":[111,269],"on":[112],"cleaned":[114],"WUSTL-IIoT-2021":[115],"dataset,":[116],"comprising":[117],"1,191,028":[118],"split":[120],"into":[121,153],"60%":[122],"training,":[123],"20%":[124,127],"validation,":[125],"testing.":[128],"The":[129],"evaluated":[130,275],"classes":[131],"Backdoor,":[133],"Command":[134],"Injection,":[135],"DoS,":[136],"Reconnaissance,":[137],"Normal.":[139],"GNF":[140,221,277],"applies":[141],"leakage-aware":[142],"with":[144,203],"split-before-scaling":[145],"train-only":[147],"transformations,":[148],"groups":[149],"raw":[150],"flow":[151,196],"variables":[152],"tokens,":[156],"embeds":[158],"these":[159],"tokens":[160],"before":[161],"local":[162,172],"global":[164],"representation":[165],"learning.":[166],"A":[167,198],"depthwise":[168],"Conv1D":[169],"encoder":[170],"captures":[171],"traffic-feature":[173],"interactions,":[174],"gated":[175],"non-local":[176],"attention":[177],"models":[178],"long-range":[179],"dependencies":[180],"across":[181,270],"groups,":[183],"Transformer":[184],"feed-forward":[185],"refinement":[186],"improves":[187],"token":[188],"representations,":[189],"attention-plus-mean":[191],"pooling":[192],"forms":[193],"final":[195],"embedding.":[197],"classifier":[200],"is":[201],"trained":[202],"class-balanced":[204],"focal":[205],"loss":[206],"refined":[208],"using":[209,239],"temperature":[210,237],"scaling.":[211],"Against":[212],"FT-Transformer,":[213],"SAINT,":[214],"XGBoost,":[215],"TabNet,":[216],"TabTransformer,":[217],"1D-CNN-BiGRU":[219],"baselines,":[220],"achieved":[222],"0.9998":[223,229],"accuracy,":[224],"0.9999":[225],"ROC-AUC,":[226],"0.9399":[227],"macro-F1,":[228],"weighted-F1,":[230],"0.0042":[232],"expected":[233],"calibration":[234],"error":[235],"after":[236],"scaling,":[238],"approximately":[240],"1.4":[241],"M":[242],"parameters":[243],"1318.4":[245],"s":[246],"training":[247],"time.":[248],"Macro-level":[249],"class-wise":[251],"analyses":[252],"provided":[253],"stricter":[255],"assessment":[256],"than":[257],"accuracy":[258],"alone.":[259],"Accordingly,":[260],"results":[262],"should":[263],"not":[264],"be":[265],"interpreted":[266],"uniform":[268],"attack":[271],"categories.":[272],"Within":[273],"benchmark,":[276],"provides":[278],"leakage-aware,":[280],"class-sensitive,":[281],"foundation":[285],"may":[287],"support":[288],"confidence-aware":[289],"alert":[290],"prioritization,":[291],"risk-informed":[292],"cybersecurity":[293],"monitoring,":[294],"management,":[298],"planning":[302],"without":[303],"implying":[304],"experimentally":[305],"demonstrated":[306],"business":[307],"outcomes":[310]},"counts_by_year":[],"updated_date":"2026-11-11T12:16:26.678958","created_date":"2026-11-06T00:00:00"}