{"id":"https://openalex.org/W4402056503","doi":"https://doi.org/10.1145/3691338","title":"Deep Learning for Time Series Anomaly Detection: A Survey","display_name":"Deep Learning for Time Series Anomaly Detection: A Survey","publication_year":2024,"publication_date":"2024-08-30","ids":{"openalex":"https://openalex.org/W4402056503","doi":"https://doi.org/10.1145/3691338"},"language":"en","primary_location":{"id":"doi:10.1145/3691338","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3691338","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3691338","source":{"id":"https://openalex.org/S157921468","display_name":"ACM Computing Surveys","issn_l":"0360-0300","issn":["0360-0300","1557-7341"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Computing Surveys","raw_type":"journal-article"},"type":"review","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3691338","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014539095","display_name":"Zahra Zamanzadeh Darban","orcid":"https://orcid.org/0000-0003-2073-8072"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Zahra Zamanzadeh Darban","raw_affiliation_strings":["Faculty of IT, Monash University, Clayton, Australia"],"raw_orcid":"https://orcid.org/0000-0003-2073-8072","affiliations":[{"raw_affiliation_string":"Faculty of IT, Monash University, Clayton, Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058054791","display_name":"Geoffrey I. Webb","orcid":"https://orcid.org/0000-0001-9963-5169"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Geoffrey I. Webb","raw_affiliation_strings":["Faculty of IT, Monash University, Clayton, Australia"],"raw_orcid":"https://orcid.org/0000-0001-9963-5169","affiliations":[{"raw_affiliation_string":"Faculty of IT, Monash University, Clayton, Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008056593","display_name":"Shirui Pan","orcid":"https://orcid.org/0000-0003-0794-527X"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shirui Pan","raw_affiliation_strings":["School of Information and Communication Technology, Griffith University, Gold Coast, Australia"],"raw_orcid":"https://orcid.org/0000-0003-0794-527X","affiliations":[{"raw_affiliation_string":"School of Information and Communication Technology, Griffith University, Gold Coast, Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028089542","display_name":"Char\u0173 C. Aggarwal","orcid":"https://orcid.org/0000-0003-2579-7581"},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Charu Aggarwal","raw_affiliation_strings":["IBM T. J. Watson Research Center, Yorktown Heights, United States"],"raw_orcid":"https://orcid.org/0000-0003-2579-7581","affiliations":[{"raw_affiliation_string":"IBM T. J. Watson Research Center, Yorktown Heights, United States","institution_ids":["https://openalex.org/I4210114115"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019440770","display_name":"Mahsa Salehi","orcid":"https://orcid.org/0000-0002-2991-1612"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Mahsa Salehi","raw_affiliation_strings":["Faculty of IT, Monash University, Clayton, Australia"],"raw_orcid":"https://orcid.org/0000-0002-2991-1612","affiliations":[{"raw_affiliation_string":"Faculty of IT, Monash University, Clayton, Australia","institution_ids":["https://openalex.org/I56590836"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5014539095"],"corresponding_institution_ids":["https://openalex.org/I56590836"],"apc_list":null,"apc_paid":null,"fwci":118.0756,"has_fulltext":true,"cited_by_count":383,"citation_normalized_percentile":{"value":0.99979245,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"57","issue":"1","first_page":"1","last_page":"42"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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":1.0,"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":0.9993000030517578,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9991999864578247,"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":0.8690460324287415},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7369770407676697},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6798185706138611},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5721714496612549},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5635879039764404},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4487718641757965},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44473764300346375},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3919329047203064},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.37791547179222107}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8690460324287415},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7369770407676697},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6798185706138611},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5721714496612549},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5635879039764404},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4487718641757965},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44473764300346375},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3919329047203064},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.37791547179222107},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3691338","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3691338","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3691338","source":{"id":"https://openalex.org/S157921468","display_name":"ACM Computing Surveys","issn_l":"0360-0300","issn":["0360-0300","1557-7341"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Computing Surveys","raw_type":"journal-article"},{"id":"pmh:oai:monash.edu:publications/a03ccb99-7ee5-4ce0-8fcf-9926ea0a4656","is_oa":true,"landing_page_url":"https://research.monash.edu/en/publications/a03ccb99-7ee5-4ce0-8fcf-9926ea0a4656","pdf_url":"https://researchmgt.monash.edu/ws/files/632804834/623912556-oa.pdf","source":{"id":"https://openalex.org/S4306402625","display_name":"Monash University Research Portal (Monash University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I56590836","host_organization_name":"Monash University","host_organization_lineage":["https://openalex.org/I56590836"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Zamanzadeh Darban, Z, Webb, G I, Pan, S, Aggarwal, C C & Salehi, M 2024, 'Deep Learning for Time Series Anomaly Detection : A Survey', ACM Computing Surveys, vol. 57, no. 1, 15. https://doi.org/10.1145/3691338","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:research-repository.griffith.edu.au:10072/433061","is_oa":true,"landing_page_url":"https://hdl.handle.net/10072/433061","pdf_url":null,"source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal article"}],"best_oa_location":{"id":"doi:10.1145/3691338","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3691338","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3691338","source":{"id":"https://openalex.org/S157921468","display_name":"ACM Computing Surveys","issn_l":"0360-0300","issn":["0360-0300","1557-7341"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Computing Surveys","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4402056503.pdf","grobid_xml":"https://content.openalex.org/works/W4402056503.grobid-xml"},"referenced_works_count":188,"referenced_works":["https://openalex.org/W1634533623","https://openalex.org/W1745334888","https://openalex.org/W1915489093","https://openalex.org/W1924770834","https://openalex.org/W1970088130","https://openalex.org/W1970978220","https://openalex.org/W1978239142","https://openalex.org/W1987004515","https://openalex.org/W2012906088","https://openalex.org/W2013746897","https://openalex.org/W2025768430","https://openalex.org/W2046868034","https://openalex.org/W2049058890","https://openalex.org/W2054217036","https://openalex.org/W2064675550","https://openalex.org/W2073703998","https://openalex.org/W2081028405","https://openalex.org/W2095409369","https://openalex.org/W2099940443","https://openalex.org/W2100495367","https://openalex.org/W2116341502","https://openalex.org/W2117296910","https://openalex.org/W2122538988","https://openalex.org/W2122646361","https://openalex.org/W2127979711","https://openalex.org/W2146103513","https://openalex.org/W2159505618","https://openalex.org/W2162800060","https://openalex.org/W2168386304","https://openalex.org/W2171604933","https://openalex.org/W2186910770","https://openalex.org/W2217007515","https://openalex.org/W2286533962","https://openalex.org/W2287948962","https://openalex.org/W2399941526","https://openalex.org/W2407991977","https://openalex.org/W2474046725","https://openalex.org/W2524141621","https://openalex.org/W2535642622","https://openalex.org/W2583164363","https://openalex.org/W2584408238","https://openalex.org/W2584499795","https://openalex.org/W2604247107","https://openalex.org/W2608911009","https://openalex.org/W2611984554","https://openalex.org/W2617259906","https://openalex.org/W2620661538","https://openalex.org/W2741951152","https://openalex.org/W2743617586","https://openalex.org/W2750814024","https://openalex.org/W2751802138","https://openalex.org/W2753802340","https://openalex.org/W2762410434","https://openalex.org/W2766761849","https://openalex.org/W2780476542","https://openalex.org/W2783741806","https://openalex.org/W2783751309","https://openalex.org/W2785362611","https://openalex.org/W2786827964","https://openalex.org/W2789828921","https://openalex.org/W2792764867","https://openalex.org/W2794417179","https://openalex.org/W2797405679","https://openalex.org/W2804483946","https://openalex.org/W2884570277","https://openalex.org/W2887731362","https://openalex.org/W2888245863","https://openalex.org/W2895543640","https://openalex.org/W2896333468","https://openalex.org/W2901072570","https://openalex.org/W2901312569","https://openalex.org/W2906498146","https://openalex.org/W2906714766","https://openalex.org/W2910068345","https://openalex.org/W2911200746","https://openalex.org/W2918465401","https://openalex.org/W2944302975","https://openalex.org/W2944981198","https://openalex.org/W2946530240","https://openalex.org/W2947464817","https://openalex.org/W2948517885","https://openalex.org/W2949848919","https://openalex.org/W2950361482","https://openalex.org/W2950860789","https://openalex.org/W2953352227","https://openalex.org/W2954960318","https://openalex.org/W2962736999","https://openalex.org/W2963026732","https://openalex.org/W2963166639","https://openalex.org/W2963248736","https://openalex.org/W2963532813","https://openalex.org/W2963608065","https://openalex.org/W2964199361","https://openalex.org/W2965433388","https://openalex.org/W2965981069","https://openalex.org/W2966587068","https://openalex.org/W2973055534","https://openalex.org/W2979625610","https://openalex.org/W2989259119","https://openalex.org/W2999926897","https://openalex.org/W2999963732","https://openalex.org/W3003626942","https://openalex.org/W3009808474","https://openalex.org/W3010542492","https://openalex.org/W3011806746","https://openalex.org/W3014106621","https://openalex.org/W3015316773","https://openalex.org/W3017266184","https://openalex.org/W3027507763","https://openalex.org/W3035630868","https://openalex.org/W3038889727","https://openalex.org/W3040099731","https://openalex.org/W3040266635","https://openalex.org/W3048036752","https://openalex.org/W3080273007","https://openalex.org/W3080875990","https://openalex.org/W3081497074","https://openalex.org/W3093074257","https://openalex.org/W3095970110","https://openalex.org/W3098957257","https://openalex.org/W3099971460","https://openalex.org/W3105816646","https://openalex.org/W3105931142","https://openalex.org/W3106312933","https://openalex.org/W3106543020","https://openalex.org/W3111370974","https://openalex.org/W3120331202","https://openalex.org/W3128634608","https://openalex.org/W3135550350","https://openalex.org/W3135644052","https://openalex.org/W3138821899","https://openalex.org/W3152030785","https://openalex.org/W3155567600","https://openalex.org/W3166888304","https://openalex.org/W3169450514","https://openalex.org/W3170937175","https://openalex.org/W3170981104","https://openalex.org/W3176085787","https://openalex.org/W3185481507","https://openalex.org/W3190748826","https://openalex.org/W3198059351","https://openalex.org/W3198381997","https://openalex.org/W3199148273","https://openalex.org/W3199473923","https://openalex.org/W3213388407","https://openalex.org/W3215290057","https://openalex.org/W3217451197","https://openalex.org/W3217545443","https://openalex.org/W4206118545","https://openalex.org/W4206503836","https://openalex.org/W4206706211","https://openalex.org/W4210263262","https://openalex.org/W4214900325","https://openalex.org/W4223531197","https://openalex.org/W4225512856","https://openalex.org/W4225539031","https://openalex.org/W4240592325","https://openalex.org/W4241492760","https://openalex.org/W4243017487","https://openalex.org/W4249224151","https://openalex.org/W4283207721","https://openalex.org/W4283696437","https://openalex.org/W4285109203","https://openalex.org/W4290943650","https://openalex.org/W4290948310","https://openalex.org/W4293718132","https://openalex.org/W4297733535","https://openalex.org/W4297814361","https://openalex.org/W4299412574","https://openalex.org/W4300506038","https://openalex.org/W4306317270","https://openalex.org/W4311415873","https://openalex.org/W4320013936","https://openalex.org/W4365393071","https://openalex.org/W4385245566","https://openalex.org/W4385562572","https://openalex.org/W4393480503","https://openalex.org/W4393566251","https://openalex.org/W4393705400","https://openalex.org/W4396757586","https://openalex.org/W4398462993","https://openalex.org/W4402056503","https://openalex.org/W6685488477","https://openalex.org/W6739901393","https://openalex.org/W6743485176","https://openalex.org/W6745537798","https://openalex.org/W6746775625","https://openalex.org/W6758101687"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4377864969","https://openalex.org/W2972971679"],"abstract_inverted_index":{"Time":[0],"series":[1,58,87,132,158],"anomaly":[2,88,96,108,128,153],"detection":[3,97,109,129,154],"is":[4,44],"important":[5],"for":[6,69,85],"a":[7,76,92],"wide":[8],"range":[9],"of":[10,26,46,54,81,126],"research":[11,146],"fields":[12],"and":[13,22,40,43,52,78,99,116,147],"applications,":[14],"including":[15],"financial":[16],"markets,":[17],"economics,":[18],"earth":[19],"sciences,":[20],"manufacturing,":[21],"healthcare.":[23],"The":[24,49],"presence":[25],"anomalies":[27],"can":[28],"indicate":[29],"novel":[30],"or":[31],"unexpected":[32],"events,":[33],"such":[34],"as":[35],"production":[36],"faults,":[37],"system":[38],"defects,":[39],"heart":[41],"palpitations,":[42],"therefore":[45],"particular":[47],"interest.":[48],"large":[50],"size":[51],"complexity":[53],"patterns":[55],"in":[56,111,130,137,145],"time":[57,86,131,157],"data":[59],"have":[60],"led":[61],"researchers":[62],"to":[63,156],"develop":[64],"specialised":[65],"deep":[66,83,100,127,152],"learning":[67,84,101],"models":[68,155],"detecting":[70],"anomalous":[71],"patterns.":[72],"This":[73],"survey":[74],"provides":[75,91],"structured":[77],"comprehensive":[79],"overview":[80],"state-of-the-art":[82],"detection.":[89],"It":[90],"taxonomy":[93],"based":[94],"on":[95],"strategies":[98],"models.":[102],"Aside":[103],"from":[104],"describing":[105],"the":[106],"basic":[107],"techniques":[110],"each":[112],"category,":[113],"their":[114],"advantages":[115],"limitations":[117],"are":[118],"also":[119],"discussed.":[120],"Furthermore,":[121],"this":[122],"study":[123],"includes":[124],"examples":[125],"across":[133],"various":[134],"application":[135],"domains":[136],"recent":[138],"years.":[139],"Finally,":[140],"it":[141],"summarises":[142],"open":[143],"issues":[144],"challenges":[148],"faced":[149],"while":[150],"adopting":[151],"data.":[159]},"counts_by_year":[{"year":2026,"cited_by_count":98},{"year":2025,"cited_by_count":257},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-03T09:05:47.796612","created_date":"2025-10-10T00:00:00"}