{"id":"https://openalex.org/W7124153366","doi":"https://doi.org/10.1109/icpads67057.2025.11323005","title":"HPCLOG: A Transformer-Based Log Anomaly Detection Framework for Distributed Systems","display_name":"HPCLOG: A Transformer-Based Log Anomaly Detection Framework for Distributed Systems","publication_year":2025,"publication_date":"2025-12-14","ids":{"openalex":"https://openalex.org/W7124153366","doi":"https://doi.org/10.1109/icpads67057.2025.11323005"},"language":null,"primary_location":{"id":"doi:10.1109/icpads67057.2025.11323005","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpads67057.2025.11323005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 31th International Conference on Parallel and Distributed Systems (ICPADS)","raw_type":"proceedings-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/A5123031288","display_name":"Qinxuan Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I24571045","display_name":"University of North Dakota","ror":"https://ror.org/04a5szx83","country_code":"US","type":"education","lineage":["https://openalex.org/I24571045"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Qinxuan Shi","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, University of North Dakota,Grand Forks,USA"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, University of North Dakota,Grand Forks,USA","institution_ids":["https://openalex.org/I24571045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123041258","display_name":"Zhanglong Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I24571045","display_name":"University of North Dakota","ror":"https://ror.org/04a5szx83","country_code":"US","type":"education","lineage":["https://openalex.org/I24571045"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhanglong Yang","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, University of North Dakota,Grand Forks,USA"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, University of North Dakota,Grand Forks,USA","institution_ids":["https://openalex.org/I24571045"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5122338366","display_name":"Sicong Shao","orcid":null},"institutions":[{"id":"https://openalex.org/I24571045","display_name":"University of North Dakota","ror":"https://ror.org/04a5szx83","country_code":"US","type":"education","lineage":["https://openalex.org/I24571045"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sicong Shao","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, University of North Dakota,Grand Forks,USA"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, University of North Dakota,Grand Forks,USA","institution_ids":["https://openalex.org/I24571045"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5123031288"],"corresponding_institution_ids":["https://openalex.org/I24571045"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.72860834,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9965000152587891,"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":0.9965000152587891,"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":0.0006000000284984708,"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":0.00039999998989515007,"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":0.7730000019073486},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6132000088691711},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5401999950408936},{"id":"https://openalex.org/keywords/distributed-database","display_name":"Distributed database","score":0.45249998569488525},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4458000063896179},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.4361000061035156},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.382099986076355}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7730000019073486},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7146000266075134},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6132000088691711},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5952000021934509},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5401999950408936},{"id":"https://openalex.org/C70061542","wikidata":"https://www.wikidata.org/wiki/Q989016","display_name":"Distributed database","level":2,"score":0.45249998569488525},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4458000063896179},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.4361000061035156},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.382099986076355},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.37770000100135803},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.36320000886917114},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3400000035762787},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.3353999853134155},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32409998774528503},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3215999901294708},{"id":"https://openalex.org/C3739613","wikidata":"https://www.wikidata.org/wiki/Q679003","display_name":"Distributed Computing Environment","level":2,"score":0.29409998655319214},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2896000146865845}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpads67057.2025.11323005","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpads67057.2025.11323005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 31th International Conference on Parallel and Distributed Systems (ICPADS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2039157918","https://openalex.org/W2094924503","https://openalex.org/W2767094836","https://openalex.org/W2895810692","https://openalex.org/W2963390429","https://openalex.org/W3007213231","https://openalex.org/W3043486047","https://openalex.org/W3134843924","https://openalex.org/W3183619936","https://openalex.org/W3199174176","https://openalex.org/W4210481850","https://openalex.org/W4282943716","https://openalex.org/W4319924564","https://openalex.org/W4319993380","https://openalex.org/W4392843850","https://openalex.org/W4405362546"],"related_works":[],"abstract_inverted_index":{"Distributed":[0],"systems,":[1,27],"prevalent":[2],"in":[3,57],"safety-critical":[4],"domains,":[5],"produce":[6],"vast":[7],"logs":[8],"containing":[9],"essential":[10],"runtime":[11],"data.":[12],"Log":[13],"Anomaly":[14,93],"Detection":[15],"(LAD)":[16],"is":[17,80],"vital":[18],"for":[19,76,120],"maintaining":[20],"the":[21,53,92],"security":[22],"and":[23,36,123,160],"reliability":[24],"of":[25,150],"these":[26,62],"yet":[28],"traditional":[29],"methods":[30],"falter":[31],"amid":[32],"growing":[33],"data":[34],"complexity":[35],"scale.":[37],"While":[38],"modern":[39],"deep":[40],"learning":[41],"approaches":[42],"such":[43],"as":[44],"LSTM":[45],"excel":[46],"at":[47],"pattern":[48],"recognition,":[49],"they":[50],"inadequately":[51],"model":[52,89,112],"long-term":[54],"dependencies":[55],"found":[56],"log":[58,121],"sequences.":[59],"To":[60],"address":[61],"challenges,":[63],"we":[64],"introduce":[65],"HPCLog":[66,79,107,141],"(High-throughput":[67],"Processing":[68],"Collection":[69],"Log),":[70],"a":[71,84,117],"transformerbased":[72],"LAD":[73],"framework":[74],"tailored":[75],"distributed":[77],"systems.":[78],"built":[81],"upon":[82],"EM-AT,":[83],"novel":[85],"unsupervised":[86],"anomaly":[87,128],"detection":[88,129],"that":[90,125,140],"extends":[91],"Transformer.":[94],"By":[95],"integrating":[96],"an":[97],"Expectation-Maximization":[98],"(EM)":[99],"algorithm,":[100],"EM-AT":[101,111],"enables":[102,126],"fully":[103],"automated":[104],"threshold":[105],"determination.":[106],"seamlessly":[108],"integrates":[109],"this":[110],"with":[113,130],"Apache":[114],"Kafka,":[115],"creating":[116],"highthroughput":[118],"pipeline":[119],"collection":[122],"processing":[124],"accurate":[127],"low":[131],"latency.":[132],"Experimental":[133],"results":[134],"on":[135,158,162],"two":[136],"public":[137],"datasets":[138],"demonstrate":[139],"surpasses":[142],"leading":[143],"methods,":[144],"achieving":[145],"<tex":[146,151],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[147,152],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$F_{1}$</tex>":[148],"-scores":[149],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathbf{9":[153],"8.":[154],"9":[155],"0":[156],"\\%}$</tex>":[157],"HDFS":[159],"99.61%":[161],"OpenStack.":[163]},"counts_by_year":[],"updated_date":"2026-02-23T20:09:44.859080","created_date":"2026-01-15T00:00:00"}