{"id":"https://openalex.org/W3111298796","doi":"https://doi.org/10.1109/smc42975.2020.9283078","title":"Anomaly Detection in Distributed Systems via Variational Autoencoders","display_name":"Anomaly Detection in Distributed Systems via Variational Autoencoders","publication_year":2020,"publication_date":"2020-10-11","ids":{"openalex":"https://openalex.org/W3111298796","doi":"https://doi.org/10.1109/smc42975.2020.9283078","mag":"3111298796"},"language":"en","primary_location":{"id":"doi:10.1109/smc42975.2020.9283078","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc42975.2020.9283078","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101693366","display_name":"Yun Qian","orcid":"https://orcid.org/0000-0003-3158-9412"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Qian","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111118231","display_name":"Shi Ying","orcid":"https://orcid.org/0000-0002-0471-0021"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shi Ying","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065258230","display_name":"Bingming Wang","orcid":"https://orcid.org/0000-0002-8723-0970"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingming Wang","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2822","last_page":"2829"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":1.0,"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/T12127","display_name":"Software System Performance and Reliability","score":1.0,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9986000061035156,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9980999827384949,"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":0.8376667499542236},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7264282703399658},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.6728653311729431},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.586403489112854},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5478318929672241},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5280987620353699},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4816704988479614},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43595778942108154},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43000173568725586},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.18593564629554749}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8376667499542236},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7264282703399658},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.6728653311729431},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.586403489112854},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5478318929672241},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5280987620353699},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4816704988479614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43595778942108154},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43000173568725586},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18593564629554749},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"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},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc42975.2020.9283078","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc42975.2020.9283078","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.6299999952316284,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1540258466","https://openalex.org/W1959608418","https://openalex.org/W2003990204","https://openalex.org/W2039157918","https://openalex.org/W2094924503","https://openalex.org/W2096017373","https://openalex.org/W2102632804","https://openalex.org/W2105454049","https://openalex.org/W2141041105","https://openalex.org/W2162744351","https://openalex.org/W2247317079","https://openalex.org/W2293379877","https://openalex.org/W2326344342","https://openalex.org/W2337344967","https://openalex.org/W2401686019","https://openalex.org/W2467604901","https://openalex.org/W2552475543","https://openalex.org/W2560021099","https://openalex.org/W2585367509","https://openalex.org/W2767094836","https://openalex.org/W2883560233","https://openalex.org/W2898998129","https://openalex.org/W2901773810","https://openalex.org/W2910068345","https://openalex.org/W2947815220","https://openalex.org/W2955071495","https://openalex.org/W2964121744","https://openalex.org/W2964304846","https://openalex.org/W2995458562","https://openalex.org/W3014309328","https://openalex.org/W3153872861","https://openalex.org/W4243639384","https://openalex.org/W4288335160","https://openalex.org/W6631190155","https://openalex.org/W6632550495","https://openalex.org/W6640963894","https://openalex.org/W6674213323","https://openalex.org/W6720208624","https://openalex.org/W6758101687","https://openalex.org/W6763324549","https://openalex.org/W6765462445","https://openalex.org/W6775524090","https://openalex.org/W7016021835"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W3210364259","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W2143820878","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4300558037","https://openalex.org/W4377864969"],"abstract_inverted_index":{"Distributed":[0],"systems":[1],"have":[2,32],"been":[3],"widely":[4],"used":[5],"in":[6,29],"the":[7,13,21,57,60,83,89,101,113,116],"information":[8],"technology":[9],"industry.":[10],"However,":[11],"with":[12,147],"increasing":[14],"scale":[15],"and":[16,23,44,59,95,119,150],"complexity":[17],"of":[18,25,62,91],"distributed":[19,64,136],"systems,":[20],"efficiency":[22],"accuracy":[24,149],"manual":[26],"anomaly":[27,47,74,108],"detection":[28,48,75,103],"system":[30,52],"logs":[31],"decreased.":[33],"Therefore,":[34],"there":[35],"is":[36],"a":[37,41],"great":[38],"demand":[39],"for":[40],"highly":[42],"accurate":[43],"efficient":[45],"automatic":[46,73],"method":[49,76],"based":[50,77],"on":[51,78,130],"log":[53,93,131],"analysis":[54],"to":[55],"ensure":[56],"reliability":[58],"stability":[61],"large-scale":[63],"systems.":[65,137],"In":[66,82,100],"this":[67],"paper,":[68],"we":[69],"propose":[70],"VeLog,":[71],"an":[72,107],"variational":[79],"autoencoders":[80],"(VAEs).":[81],"offline":[84],"training":[85],"phase,":[86,104],"VeLog":[87,105,129,143],"learns":[88],"patterns":[90],"normal":[92,98,125],"sequences":[94],"then":[96],"generates":[97],"intervals.":[99,126],"online":[102],"detects":[106],"by":[109],"automatically":[110],"evaluating":[111],"whether":[112],"distance":[114],"between":[115],"input":[117],"vector":[118,122],"its":[120],"estimated":[121],"matches":[123],"these":[124],"We":[127],"evaluate":[128],"datasets":[132],"collected":[133],"from":[134],"representative":[135],"The":[138],"experimental":[139],"results":[140],"demonstrate":[141],"that":[142],"can":[144],"detect":[145],"anomalies":[146],"high":[148],"good":[151],"efficiency.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}