{"id":"https://openalex.org/W7163984311","doi":"https://doi.org/10.1145/3748522.3779783","title":"DyCAD: Dynamic Collaborative Online Anomaly Detection for Multivariate Time Series using Adaptive Clustering","display_name":"DyCAD: Dynamic Collaborative Online Anomaly Detection for Multivariate Time Series using Adaptive Clustering","publication_year":2026,"publication_date":"2026-03-23","ids":{"openalex":"https://openalex.org/W7163984311","doi":"https://doi.org/10.1145/3748522.3779783"},"language":null,"primary_location":{"id":"doi:10.1145/3748522.3779783","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748522.3779783","pdf_url":null,"source":null,"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":"Proceedings of the 41st ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3748522.3779783","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058290511","display_name":"Ming\u2010Chang Lee","orcid":"https://orcid.org/0000-0003-2484-4366"},"institutions":[{"id":"https://openalex.org/I204778367","display_name":"Norwegian University of Science and Technology","ror":"https://ror.org/05xg72x27","country_code":"NO","type":"education","lineage":["https://openalex.org/I204778367"]}],"countries":["NO"],"is_corresponding":true,"raw_author_name":"Ming-Chang Lee","raw_affiliation_strings":["Department of Information Security and Communication Technology, Norwegian University of Science and Technology, Gj\u00f8vik, Oppland, Norway"],"raw_orcid":"https://orcid.org/0000-0003-2484-4366","affiliations":[{"raw_affiliation_string":"Department of Information Security and Communication Technology, Norwegian University of Science and Technology, Gj\u00f8vik, Oppland, Norway","institution_ids":["https://openalex.org/I204778367"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103166673","display_name":"Jia\u2010Chun Lin","orcid":"https://orcid.org/0000-0003-3374-8536"},"institutions":[{"id":"https://openalex.org/I204778367","display_name":"Norwegian University of Science and Technology","ror":"https://ror.org/05xg72x27","country_code":"NO","type":"education","lineage":["https://openalex.org/I204778367"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Jia-Chun Lin","raw_affiliation_strings":["Department of Information Security and Communication Technology, Norwegian University of Science and Technology, Gj\u00f8vik, Oppland, Norway"],"raw_orcid":"https://orcid.org/0000-0003-3374-8536","affiliations":[{"raw_affiliation_string":"Department of Information Security and Communication Technology, Norwegian University of Science and Technology, Gj\u00f8vik, Oppland, Norway","institution_ids":["https://openalex.org/I204778367"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5138217702","display_name":"Sokratis Katsikas","orcid":"https://orcid.org/0000-0003-2966-9683"},"institutions":[{"id":"https://openalex.org/I204778367","display_name":"Norwegian University of Science and Technology","ror":"https://ror.org/05xg72x27","country_code":"NO","type":"education","lineage":["https://openalex.org/I204778367"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Sokratis Katsikas","raw_affiliation_strings":["Department of Information Security and Communication Technology, Norwegian University of Science and Technology, Gj\u00f8vik, Oppland, Norway"],"raw_orcid":"https://orcid.org/0000-0003-2966-9683","affiliations":[{"raw_affiliation_string":"Department of Information Security and Communication Technology, Norwegian University of Science and Technology, Gj\u00f8vik, Oppland, Norway","institution_ids":["https://openalex.org/I204778367"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5058290511"],"corresponding_institution_ids":["https://openalex.org/I204778367"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.96110806,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"561","last_page":"568"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9836999773979187,"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":0.9836999773979187,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.00860000029206276,"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"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.0010999999940395355,"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/anomaly-detection","display_name":"Anomaly detection","score":0.8468999862670898},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6180999875068665},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5648000240325928},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5515000224113464},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.5271999835968018},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5199000239372253},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.49000000953674316}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8468999862670898},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.753600001335144},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6973999738693237},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6180999875068665},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5648000240325928},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5515000224113464},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.5271999835968018},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5199000239372253},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.49000000953674316},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.44749999046325684},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.42660000920295715},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3758000135421753},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3359000086784363},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2881999909877777},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2874000072479248},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2833999991416931},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3748522.3779783","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748522.3779783","pdf_url":null,"source":null,"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":"Proceedings of the 41st ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3748522.3779783","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748522.3779783","pdf_url":null,"source":null,"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":"Proceedings of the 41st ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1987971958","https://openalex.org/W2122646361","https://openalex.org/W2407991977","https://openalex.org/W2786827964","https://openalex.org/W3003089943","https://openalex.org/W3004207920","https://openalex.org/W3081497074","https://openalex.org/W3091751937","https://openalex.org/W3155567600","https://openalex.org/W3159054899","https://openalex.org/W3169450514","https://openalex.org/W4318486034","https://openalex.org/W4366808736","https://openalex.org/W4376870121","https://openalex.org/W4384077378","https://openalex.org/W4408062202"],"related_works":[],"abstract_inverted_index":{"A":[0],"multivariate":[1,111,171],"time":[2,69,83,112,172],"series":[3,70],"refers":[4],"to":[5,32,57,117,130,133,193,229],"a":[6,103,145,166,204],"set":[7],"of":[8,53],"multiple":[9,158],"variables":[10,81,182,232],"whose":[11],"data":[12,24],"points":[13,19],"are":[14],"recorded":[15],"simultaneously":[16],"at":[17],"successive":[18],"in":[20,46,68,75,197],"time.":[21,199],"Monitoring":[22],"such":[23],"and":[25,37,61,84,152,188,221],"detecting":[26],"anomalies":[27,54,196],"has":[28],"become":[29],"increasingly":[30],"important":[31],"ensure":[33],"proper":[34],"system":[35],"operation":[36],"maintain":[38],"high":[39,218],"service":[40],"quality.":[41],"This":[42],"is":[43,115,142],"especially":[44],"critical":[45],"cyber-physical":[47],"systems,":[48],"where":[49],"the":[50,77,86,153,170,190,231,235],"timely":[51],"detection":[52,67,87,108,219],"enables":[55],"personnel":[56],"take":[58],"prompt":[59],"countermeasures":[60],"minimize":[62],"potential":[63],"damage.":[64],"However,":[65],"anomaly":[66,107,160,177],"presents":[71],"several":[72],"challenges,":[73,99],"particularly":[74],"capturing":[76],"dynamic":[78,104],"correlation":[79],"among":[80],"over":[82],"adapting":[85],"model":[88,126],"without":[89,121],"extensive":[90,122],"human":[91],"intervention":[92],"or":[93,124],"computational":[94],"resources.":[95],"To":[96],"address":[97],"these":[98],"we":[100],"propose":[101],"DyCAD,":[102],"collaborative":[105],"online":[106],"approach":[109],"for":[110,164,234],"series.":[113],"DyCAD":[114,141,179,202,215],"designed":[116],"be":[118],"easily":[119],"deployable":[120],"configuration":[123],"offline":[125],"training,":[127],"allowing":[128],"it":[129],"automatically":[131],"adapt":[132],"different":[134],"environments.":[135],"Unlike":[136],"many":[137],"deep":[138],"learning-based":[139],"solutions,":[140],"built":[143],"on":[144,184],"divide-and-conquer":[146],"strategy,":[147],"parallel":[148,176],"processing,":[149],"adaptive":[150],"clustering,":[151],"majority":[154,191],"rule.":[155],"It":[156],"employs":[157],"lightweight":[159],"detectors,":[161],"each":[162],"responsible":[163,233],"monitoring":[165],"separate":[167],"variable":[168],"within":[169],"series,":[173],"thereby":[174],"enabling":[175],"detection.":[178],"dynamically":[180],"clusters":[181],"based":[183],"their":[185],"recent":[186],"correlations":[187],"applies":[189],"rule":[192],"collaboratively":[194],"detect":[195],"real":[198],"We":[200],"evaluate":[201],"using":[203],"publicly":[205],"available":[206],"multisensor":[207],"water":[208],"pump":[209],"dataset.":[210],"Experimental":[211],"results":[212],"demonstrate":[213],"that":[214],"achieves":[216],"both":[217],"accuracy":[220],"real-time":[222],"performance,":[223],"while":[224],"also":[225],"providing":[226],"useful":[227],"information":[228],"identify":[230],"detected":[236],"anomalies.":[237]},"counts_by_year":[],"updated_date":"2026-06-10T14:10:52.464848","created_date":"2026-06-10T00:00:00"}
