{"id":"https://openalex.org/W7128509090","doi":"https://doi.org/10.1109/jiot.2026.3663198","title":"CADiS: Causality-Driven Transformer for Anomaly Detection and Root Cause Diagnosis in Industrial Internet of Things","display_name":"CADiS: Causality-Driven Transformer for Anomaly Detection and Root Cause Diagnosis in Industrial Internet of Things","publication_year":2026,"publication_date":"2026-02-10","ids":{"openalex":"https://openalex.org/W7128509090","doi":"https://doi.org/10.1109/jiot.2026.3663198"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2026.3663198","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3663198","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125586948","display_name":"Zuanyang Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zuanyang Zeng","raw_affiliation_strings":["Fujian Provincial Key Laboratory of Network Security and Cryptology, College of Computer and Cyber Security, Fujian Normal University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0009-0007-4712-9169","affiliations":[{"raw_affiliation_string":"Fujian Provincial Key Laboratory of Network Security and Cryptology, College of Computer and Cyber Security, Fujian Normal University, Fuzhou, China","institution_ids":["https://openalex.org/I111753288"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125521487","display_name":"Xiaoding Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoding Wang","raw_affiliation_strings":["Fujian Provincial Key Laboratory of Network Security and Cryptology, College of Computer and Cyber Security, Fujian Normal University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-0494-3538","affiliations":[{"raw_affiliation_string":"Fujian Provincial Key Laboratory of Network Security and Cryptology, College of Computer and Cyber Security, Fujian Normal University, Fuzhou, China","institution_ids":["https://openalex.org/I111753288"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125580969","display_name":"Li Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Xu","raw_affiliation_strings":["Fujian Provincial Key Laboratory of Network Security and Cryptology, College of Computer and Cyber Security, Fujian Normal University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-8972-3373","affiliations":[{"raw_affiliation_string":"Fujian Provincial Key Laboratory of Network Security and Cryptology, College of Computer and Cyber Security, Fujian Normal University, Fuzhou, China","institution_ids":["https://openalex.org/I111753288"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125523103","display_name":"Xiucai Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xiucai Ye","raw_affiliation_strings":["Department of Computer Science, University of Tsukuba, Tsukuba, Japan"],"raw_orcid":"https://orcid.org/0000-0002-5547-3919","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Tsukuba, Tsukuba, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125514009","display_name":"Jia Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I23923803","display_name":"University of Exeter","ror":"https://ror.org/03yghzc09","country_code":"GB","type":"education","lineage":["https://openalex.org/I23923803"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jia Hu","raw_affiliation_strings":["Department of Computer Science, University of Exeter, Exeter, U.K"],"raw_orcid":"https://orcid.org/0000-0001-5406-8420","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Exeter, Exeter, U.K","institution_ids":["https://openalex.org/I23923803"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035131570","display_name":"Farooque Hassan Kumbhar","orcid":"https://orcid.org/0000-0002-8442-3072"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Farooque Hassan Kumbhar","raw_affiliation_strings":["Augmented Cognition Meta-Communications ERC Research Center, Korea University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-8442-3072","affiliations":[{"raw_affiliation_string":"Augmented Cognition Meta-Communications ERC Research Center, Korea University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064768354","display_name":"Kapal Dev","orcid":"https://orcid.org/0000-0003-1262-8594"},"institutions":[{"id":"https://openalex.org/I4210100923","display_name":"Munster Technological University","ror":"https://ror.org/013xpqh61","country_code":"IE","type":"facility","lineage":["https://openalex.org/I4210100923"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Kapal Dev","raw_affiliation_strings":["Department of Computer Science, ADAPT Centre, Munster Technological University, Cork, Ireland"],"raw_orcid":"https://orcid.org/0000-0003-1262-8594","affiliations":[{"raw_affiliation_string":"Department of Computer Science, ADAPT Centre, Munster Technological University, Cork, Ireland","institution_ids":["https://openalex.org/I4210100923"]}]}],"institutions":[],"countries_distinct_count":5,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14120539,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"10","first_page":"20047","last_page":"20060"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.5996999740600586,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.5996999740600586,"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/T12127","display_name":"Software System Performance and Reliability","score":0.24740000069141388,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.04650000110268593,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.8274999856948853},{"id":"https://openalex.org/keywords/root-cause","display_name":"Root cause","score":0.7907000184059143},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6531999707221985},{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.6176999807357788},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5853999853134155},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.508899986743927},{"id":"https://openalex.org/keywords/causal-analysis","display_name":"Causal analysis","score":0.48260000348091125},{"id":"https://openalex.org/keywords/root-cause-analysis","display_name":"Root cause analysis","score":0.46369999647140503}],"concepts":[{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.8274999856948853},{"id":"https://openalex.org/C84945661","wikidata":"https://www.wikidata.org/wiki/Q7366567","display_name":"Root cause","level":2,"score":0.7907000184059143},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7879999876022339},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6531999707221985},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.6176999807357788},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5853999853134155},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5594000220298767},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.508899986743927},{"id":"https://openalex.org/C2987525970","wikidata":"https://www.wikidata.org/wiki/Q96374569","display_name":"Causal analysis","level":2,"score":0.48260000348091125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4675999879837036},{"id":"https://openalex.org/C130963320","wikidata":"https://www.wikidata.org/wiki/Q1401207","display_name":"Root cause analysis","level":2,"score":0.46369999647140503},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.4221999943256378},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.3562000095844269},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.3458999991416931},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.3409999907016754},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3400999903678894},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.3346000015735626},{"id":"https://openalex.org/C14396502","wikidata":"https://www.wikidata.org/wiki/Q280951","display_name":"Common cause and special cause","level":2,"score":0.32829999923706055},{"id":"https://openalex.org/C171078966","wikidata":"https://www.wikidata.org/wiki/Q111029","display_name":"Root (linguistics)","level":2,"score":0.31679999828338623},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.31369999051094055},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.2847999930381775},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26829999685287476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2026.3663198","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3663198","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6706802845001221,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G3051878211","display_name":null,"funder_award_id":"62471139","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"CADiS,":[3],"a":[4,69,81,90,100,106,119],"causality-driven":[5],"anomaly":[6],"detection":[7],"framework,":[8],"to":[9,85,108],"address":[10],"the":[11,47,65,111,126,134,137,142,169],"challenges":[12],"of":[13,21,50,113,128,136,173,179,187,193],"root":[14,152],"cause":[15,153],"identification":[16],"in":[17,38],"high-dimensional":[18],"Industrial":[19],"Internet":[20],"Things":[22],"(IIoT)":[23],"multivariate":[24],"time":[25,97],"series.":[26],"The":[27,183],"essential":[28],"difference":[29],"between":[30],"CADiS":[31,163],"and":[32,71,150,175,189,201],"existing":[33],"correlation-driven":[34],"deep":[35],"models":[36],"lies":[37],"its":[39,199],"core":[40],"innovation:":[41],"it":[42,79],"fundamentally":[43],"redefines":[44],"anomalies":[45],"as":[46,99],"structural":[48],"decay":[49],"an":[51,103],"underlying":[52],"causal":[53,73,114,129,139,144],"mechanism,":[54],"rather":[55],"than":[56],"merely":[57],"capturing":[58],"symptomatic":[59],"deviations":[60],"or":[61],"spurious":[62],"correlations.":[63],"Specifically,":[64],"framework":[66],"first":[67],"learns":[68],"directed":[70],"lag-aware":[72],"prior":[74],"from":[75],"normal":[76],"data,":[77],"compiling":[78],"into":[80],"structured":[82],"attention":[83],"mask":[84],"constrain":[86],"information":[87],"flow.":[88],"Then,":[89],"Causal-Phase":[91],"Decomposition":[92],"(CPD)":[93],"technique":[94],"treats":[95],"each":[96],"window":[98],"micro-experiment,":[101],"comparing":[102],"ante-phase":[104],"with":[105],"post-phase":[107],"explicitly":[109],"capture":[110],"dynamics":[112],"attenuation.":[115],"Inference":[116],"relies":[117],"on":[118,157,181,195],"unified":[120],"Causal-Change":[121],"Score":[122],"(CCS),":[123],"which":[124],"quantifies":[125],"degradation":[127],"association":[130],"strength,":[131],"directly":[132],"revealing":[133],"breakdown":[135],"system\u2019s":[138],"logic.":[140],"Furthermore,":[141],"decomposed":[143],"change":[145],"matrix":[146],"allows":[147],"for":[148],"fine-grained":[149],"auditable":[151],"diagnosis.":[154],"Extensive":[155],"experiments":[156],"real-world":[158],"industrial":[159],"datasets":[160],"demonstrate":[161],"that":[162],"significantly":[164],"outperforms":[165],"strong":[166],"baselines,":[167],"achieving":[168],"<italic":[170,176,184,190],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[171,177,185,191],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">V<sub>ROC</sub></i>":[172,192],"89.93%":[174],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">V<sub>PR</sub></i>":[178],"76.93%":[180],"SWaT;":[182],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">A<sub>PR</sub></i>":[186],"18.04%":[188],"78.38%":[194],"SMD,":[196],"thereby":[197],"validating":[198],"robustness":[200],"diagnostic":[202],"precision.":[203]},"counts_by_year":[],"updated_date":"2026-05-09T06:09:20.037420","created_date":"2026-02-11T00:00:00"}
