{"id":"https://openalex.org/W7140948419","doi":"https://doi.org/10.1145/3788096","title":"Janus: A Dual-Mask Attention Transformer for Log-based Anomaly Detection in Cellular Networks","display_name":"Janus: A Dual-Mask Attention Transformer for Log-based Anomaly Detection in Cellular Networks","publication_year":2026,"publication_date":"2026-03-26","ids":{"openalex":"https://openalex.org/W7140948419","doi":"https://doi.org/10.1145/3788096"},"language":"en","primary_location":{"id":"doi:10.1145/3788096","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3788096","pdf_url":null,"source":{"id":"https://openalex.org/S4210193547","display_name":"Proceedings of the ACM on Measurement and Analysis of Computing Systems","issn_l":"2476-1249","issn":["2476-1249"],"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":"Proceedings of the ACM on Measurement and Analysis of Computing Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3788096","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103233339","display_name":"Umakant P. Kulkarni","orcid":"https://orcid.org/0000-0002-9452-4504"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Umakant Kulkarni","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0000-0002-9452-4504","affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014376333","display_name":"Sonia Fahmy","orcid":"https://orcid.org/0000-0003-2870-7166"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sonia Fahmy","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0000-0003-2870-7166","affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":18.0209,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.98836536,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"10","issue":"1","first_page":"1","last_page":"36"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.8977000117301941,"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":0.8977000117301941,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.011900000274181366,"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/T10260","display_name":"Software Engineering Research","score":0.010400000028312206,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/discriminative-model","display_name":"Discriminative model","score":0.6647999882698059},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.5968000292778015},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5602999925613403},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4641000032424927},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.42080000042915344},{"id":"https://openalex.org/keywords/grammar","display_name":"Grammar","score":0.4196999967098236},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41260001063346863},{"id":"https://openalex.org/keywords/janus","display_name":"Janus","score":0.3684000074863434}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7829999923706055},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6647999882698059},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.5968000292778015},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5602999925613403},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5034999847412109},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4641000032424927},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.42080000042915344},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4198000133037567},{"id":"https://openalex.org/C26022165","wikidata":"https://www.wikidata.org/wiki/Q8091","display_name":"Grammar","level":2,"score":0.4196999967098236},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4171000123023987},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41260001063346863},{"id":"https://openalex.org/C2779290492","wikidata":"https://www.wikidata.org/wiki/Q6155940","display_name":"Janus","level":2,"score":0.3684000074863434},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.33410000801086426},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.31679999828338623},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.30169999599456787},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C199521495","wikidata":"https://www.wikidata.org/wiki/Q181487","display_name":"Audit","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.2572999894618988}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3788096","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3788096","pdf_url":null,"source":{"id":"https://openalex.org/S4210193547","display_name":"Proceedings of the ACM on Measurement and Analysis of Computing Systems","issn_l":"2476-1249","issn":["2476-1249"],"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":"Proceedings of the ACM on Measurement and Analysis of Computing Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3788096","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3788096","pdf_url":null,"source":{"id":"https://openalex.org/S4210193547","display_name":"Proceedings of the ACM on Measurement and Analysis of Computing Systems","issn_l":"2476-1249","issn":["2476-1249"],"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":"Proceedings of the ACM on Measurement and Analysis of Computing Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6754885911941528,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2136420282","https://openalex.org/W2141409867","https://openalex.org/W2153919695","https://openalex.org/W2170880743","https://openalex.org/W3199174176","https://openalex.org/W4205965165","https://openalex.org/W4294672412","https://openalex.org/W4327503230","https://openalex.org/W4328028653","https://openalex.org/W4380590077","https://openalex.org/W4387212529","https://openalex.org/W4405014254"],"related_works":[],"abstract_inverted_index":{"Modern":[0],"cellular":[1],"networks,":[2],"such":[3],"as":[4,26],"5G,":[5],"generate":[6],"complex":[7],"operational":[8],"logs":[9,25],"that":[10,144],"challenge":[11],"traditional":[12],"anomaly":[13,58],"detection":[14,59],"techniques.":[15],"Existing":[16],"deep":[17],"learning":[18,117],"approaches,":[19],"including":[20],"standard":[21],"transformer":[22],"models,":[23],"treat":[24],"monolithic":[27],"text":[28],"streams":[29],"and":[30,39,96,128,161],"lack":[31],"the":[32,85,103],"specialization":[33],"to":[34,125,130],"reason":[35],"about":[36],"procedural":[37],"correctness":[38],"semantic":[40,112],"integrity,":[41],"a":[42,56,62,71,93,110,153,158,166],"key":[43],"requirement":[44],"for":[45],"telecommunications":[46],"software.":[47],"We":[48],"tackle":[49],"this":[50],"problem":[51],"in":[52],"our":[53],"system":[54,60],"Janus,":[55],"log-based":[57],"featuring":[61],"novel":[63],"Single-Pass":[64],"Dual-Mask":[65],"(SPDM)":[66],"attention":[67,77],"mechanism.":[68],"Janus":[69,121,145],"introduces":[70],"domain-specific":[72],"inductive":[73],"bias":[74],"by":[75],"partitioning":[76],"heads":[78,83,98],"into":[79],"two":[80],"groups.":[81],"Global":[82],"learn":[84],"valid":[86],"temporal":[87],"grammar":[88],"of":[89,105],"5G":[90,140],"procedures":[91],"using":[92,109],"causal":[94],"mask,":[95],"local":[97],"perform":[99],"fine-grained":[100],"audits":[101],"on":[102,151],"consistency":[104],"critical":[106],"data":[107],"fields":[108],"tag-based":[111],"mask.":[113],"A":[114],"multi-stage":[115],"curriculum":[116],"framework":[118],"progressively":[119],"adapts":[120],"from":[122],"domain":[123],"pre-training":[124],"discriminative":[126],"fine-tuning":[127],"learns":[129],"detect":[131],"complex,":[132],"real-world":[133],"software":[134],"failures.":[135],"Experimental":[136],"evaluation":[137],"with":[138],"several":[139],"log":[141],"datasets":[142],"demonstrates":[143],"consistently":[146],"outperforms":[147],"prior":[148],"systems,":[149],"achieving":[150],"average":[152],"3\u00d7":[154],"performance":[155],"improvement":[156],"over":[157,165],"DNN-based":[159],"baseline":[160],"an":[162],"80%":[163],"gain":[164],"transformer-based":[167],"system.":[168]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-27T00:00:00"}
