{"id":"https://openalex.org/W7133212965","doi":"https://doi.org/10.1109/jiot.2026.3669246","title":"Transformer-Driven Multicenter Manifold Modeling Deep SVDD for Anomaly Detection in IIoT Networks","display_name":"Transformer-Driven Multicenter Manifold Modeling Deep SVDD for Anomaly Detection in IIoT Networks","publication_year":2026,"publication_date":"2026-03-02","ids":{"openalex":"https://openalex.org/W7133212965","doi":"https://doi.org/10.1109/jiot.2026.3669246"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2026.3669246","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3669246","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/A5056908856","display_name":"Weijian Zhong","orcid":"https://orcid.org/0000-0002-7886-2466"},"institutions":[{"id":"https://openalex.org/I111950717","display_name":"Macau University of Science and Technology","ror":"https://ror.org/03jqs2n27","country_code":"MO","type":"education","lineage":["https://openalex.org/I111950717","https://openalex.org/I4391767947"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Weijian Zhong","raw_affiliation_strings":["School of Computer Science and Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, China","institution_ids":["https://openalex.org/I111950717"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100605483","display_name":"Dagang Li","orcid":"https://orcid.org/0000-0002-8134-0538"},"institutions":[{"id":"https://openalex.org/I111950717","display_name":"Macau University of Science and Technology","ror":"https://ror.org/03jqs2n27","country_code":"MO","type":"education","lineage":["https://openalex.org/I111950717","https://openalex.org/I4391767947"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Dagang Li","raw_affiliation_strings":["School of Computer Science and Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, China"],"raw_orcid":"https://orcid.org/0000-0002-8134-0538","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, China","institution_ids":["https://openalex.org/I111950717"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102313539","display_name":"Yuntao Zou","orcid":null},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]},{"id":"https://openalex.org/I6469544","display_name":"City University of Macau","ror":"https://ror.org/04gpd4q15","country_code":"MO","type":"education","lineage":["https://openalex.org/I6469544"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Yuntao Zou","raw_affiliation_strings":["Advanced Interdisciplinary Research Center, City University of Macau, Macau, China"],"raw_orcid":"https://orcid.org/0000-0002-8492-7684","affiliations":[{"raw_affiliation_string":"Advanced Interdisciplinary Research Center, City University of Macau, Macau, China","institution_ids":["https://openalex.org/I6469544","https://openalex.org/I204512498"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127833763","display_name":"Tongjun Guan","orcid":null},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tongjun Guan","raw_affiliation_strings":["Future Front Interdisciplinary Research Institute, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Future Front Interdisciplinary Research Institute, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121541460","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-1717-5785"},"institutions":[{"id":"https://openalex.org/I49835588","display_name":"Macao Polytechnic University","ror":"https://ror.org/02sf5td35","country_code":"MO","type":"education","lineage":["https://openalex.org/I49835588"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["Faculty of Applied Sciences, Macao Polytechnic University, Macau, SAR, China"],"raw_orcid":"https://orcid.org/0000-0002-1717-5785","affiliations":[{"raw_affiliation_string":"Faculty of Applied Sciences, Macao Polytechnic University, Macau, SAR, China","institution_ids":["https://openalex.org/I49835588"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":12.882,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.9742052,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":"13","issue":"10","first_page":"20071","last_page":"20084"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.17829999327659607,"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":0.17829999327659607,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.16670000553131104,"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":0.032099999487400055,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7559000253677368},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4848000109195709},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46369999647140503},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.38089999556541443},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.3675000071525574},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36629998683929443},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.36559998989105225},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.35100001096725464}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8177000284194946},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7559000253677368},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5509999990463257},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5134999752044678},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4848000109195709},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46369999647140503},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.38089999556541443},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3675000071525574},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36629998683929443},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.36559998989105225},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.35100001096725464},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34779998660087585},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C13540734","wikidata":"https://www.wikidata.org/wiki/Q5318996","display_name":"Dynamic network analysis","level":2,"score":0.31610000133514404},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.2992999851703644},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29490000009536743},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.28999999165534973},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.2892000079154968},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.25850000977516174}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2026.3669246","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3669246","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":[],"awards":[{"id":"https://openalex.org/G4739566124","display_name":null,"funder_award_id":"2023BIB017","funder_id":"https://openalex.org/F4320336596","funder_display_name":"Key Research and Development Program of Sichuan Province"},{"id":"https://openalex.org/G7658171565","display_name":null,"funder_award_id":"2022B03","funder_id":"https://openalex.org/F4320330424","funder_display_name":"Key Laboratory of Intelligent Multimedia Technology"}],"funders":[{"id":"https://openalex.org/F4320330424","display_name":"Key Laboratory of Intelligent Multimedia Technology","ror":null},{"id":"https://openalex.org/F4320336596","display_name":"Key Research and Development Program of Sichuan Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Anomaly":[0],"detection":[1,45],"in":[2,179],"Industrial":[3],"Internet":[4],"of":[5,151],"Things":[6],"(IIoT)":[7],"systems":[8],"is":[9,122,136],"crucial":[10],"for":[11,48,66,190],"ensuring":[12],"operational":[13],"safety":[14],"and":[15,28,132,159,171,181,187],"product":[16],"quality.":[17],"However,":[18],"challenges":[19],"such":[20],"as":[21],"heterogeneous":[22],"sensor":[23,102],"data,":[24],"dynamic":[25,49],"network":[26],"structures,":[27],"complex":[29],"spatio-temporal":[30,106],"dependencies":[31,100],"hinder":[32],"existing":[33],"methods.":[34],"To":[35,109],"address":[36],"these":[37,155],"issues,":[38],"we":[39,71],"propose":[40],"a":[41,91,118],"novel":[42],"Transformer-based":[43],"anomaly":[44,161],"framework":[46,53],"designed":[47],"IIoT":[50,167,191],"networks.":[51],"Our":[52],"integrates":[54],"self-supervised":[55,119],"graph":[56,74],"contrastive":[57,120],"learning":[58],"with":[59,94],"multi-center":[60],"Support":[61],"Vector":[62],"Data":[63],"Description":[64],"(SVDD)":[65],"the":[67,111,149],"first":[68],"time.":[69],"Specifically,":[70],"construct":[72],"temporal":[73,95],"snapshots":[75],"from":[76],"normal":[77,145],"time":[78],"windows.":[79],"Graph":[80],"Attention":[81],"Networks":[82],"(GAT)":[83],"are":[84,128],"used":[85],"to":[86,140,154],"extract":[87],"structural":[88],"features,":[89],"while":[90],"lightweight":[92],"Transformer":[93],"window":[96],"attention":[97],"captures":[98],"long-range":[99],"among":[101],"sequences,":[103],"producing":[104],"robust":[105],"node":[107,126],"representations.":[108],"improve":[110],"model\u2019s":[112],"generalization":[113],"without":[114],"requiring":[115],"labeled":[116],"anomalies,":[117],"loss":[121],"introduced.":[123],"The":[124],"resulting":[125],"embeddings":[127],"clustered":[129],"via":[130],"k-Medoids,":[131],"an":[133],"SVDD":[134],"sub-model":[135],"trained":[137],"per":[138],"cluster":[139],"define":[141],"multiple":[142],"hyperspheres":[143],"representing":[144],"behavior.":[146],"During":[147],"inference,":[148],"proximity":[150],"test":[152],"representations":[153],"hyper-spheres":[156],"enables":[157],"accurate":[158],"interpretable":[160],"detection.":[162],"Extensive":[163],"experiments":[164],"on":[165],"real-world":[166],"datasets,":[168],"including":[169],"SWaT":[170],"WADI,":[172],"show":[173],"our":[174],"method":[175],"outperforms":[176],"state-of-the-art":[177],"baselines":[178],"AUC":[180],"F1":[182],"score,":[183],"demonstrating":[184],"its":[185],"effectiveness":[186],"practical":[188],"value":[189],"security":[192],"applications.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-04T07:58:01.006859","created_date":"2026-03-03T00:00:00"}
