{"id":"https://openalex.org/W4327768027","doi":"https://doi.org/10.1109/ccnc51644.2023.10060584","title":"A Deep Learning Approach for Real-Time Application-Level Anomaly Detection in IoT Data Streaming","display_name":"A Deep Learning Approach for Real-Time Application-Level Anomaly Detection in IoT Data Streaming","publication_year":2023,"publication_date":"2023-01-08","ids":{"openalex":"https://openalex.org/W4327768027","doi":"https://doi.org/10.1109/ccnc51644.2023.10060584"},"language":"en","primary_location":{"id":"doi:10.1109/ccnc51644.2023.10060584","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ccnc51644.2023.10060584","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 20th Consumer Communications & Networking Conference (CCNC)","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/A5008119392","display_name":"Mahsa Raeiszadeh","orcid":"https://orcid.org/0009-0005-9729-4475"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Mahsa Raeiszadeh","raw_affiliation_strings":["CIISE, Concordia University,Montréal,QC,Canada"],"affiliations":[{"raw_affiliation_string":"CIISE, Concordia University,Montréal,QC,Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080097569","display_name":"Ahsan Saleem","orcid":"https://orcid.org/0000-0003-1710-3578"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ahsan Saleem","raw_affiliation_strings":["CIISE, Concordia University,Montréal,QC,Canada"],"affiliations":[{"raw_affiliation_string":"CIISE, Concordia University,Montréal,QC,Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023434379","display_name":"Amin Ebrahimzadeh","orcid":"https://orcid.org/0000-0002-1741-677X"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Amin Ebrahimzadeh","raw_affiliation_strings":["CIISE, Concordia University,Montréal,QC,Canada"],"affiliations":[{"raw_affiliation_string":"CIISE, Concordia University,Montréal,QC,Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041878389","display_name":"Roch Glitho","orcid":"https://orcid.org/0000-0002-7699-0296"},"institutions":[{"id":"https://openalex.org/I869660684","display_name":"University of the Western Cape","ror":"https://ror.org/00h2vm590","country_code":"ZA","type":"education","lineage":["https://openalex.org/I869660684"]},{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA","ZA"],"is_corresponding":false,"raw_author_name":"Roch H. Glitho","raw_affiliation_strings":["CIISE, Concordia University,Montréal,QC,Canada","Computer Science Programme, University of Western Cape, Capetown, South Africa"],"affiliations":[{"raw_affiliation_string":"CIISE, Concordia University,Montréal,QC,Canada","institution_ids":["https://openalex.org/I60158472"]},{"raw_affiliation_string":"Computer Science Programme, University of Western Cape, Capetown, South Africa","institution_ids":["https://openalex.org/I869660684"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067617101","display_name":"Johan Eker","orcid":"https://orcid.org/0000-0003-0181-3970"},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Johan Eker","raw_affiliation_strings":["Ericsson Research,Sweden","Ericsson Research, Sweden"],"affiliations":[{"raw_affiliation_string":"Ericsson Research,Sweden","institution_ids":["https://openalex.org/I1306339040"]},{"raw_affiliation_string":"Ericsson Research, Sweden","institution_ids":["https://openalex.org/I1306339040"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034800224","display_name":"Raquel A. F. Mini","orcid":"https://orcid.org/0000-0001-7575-7348"},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Raquel A. F. Mini","raw_affiliation_strings":["Ericsson Research,Sweden","Ericsson Research, Sweden"],"affiliations":[{"raw_affiliation_string":"Ericsson Research,Sweden","institution_ids":["https://openalex.org/I1306339040"]},{"raw_affiliation_string":"Ericsson Research, Sweden","institution_ids":["https://openalex.org/I1306339040"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5008119392"],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":0.6949,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.74379056,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"9","issue":null,"first_page":"449","last_page":"454"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9991000294685364,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9973999857902527,"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":0.7932542562484741},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7900891900062561},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6125898957252502},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6068388819694519},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.535658061504364},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5012743473052979},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48755019903182983},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.4766329526901245},{"id":"https://openalex.org/keywords/concept-drift","display_name":"Concept drift","score":0.43799978494644165},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.430412232875824},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4248518943786621},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4096236526966095},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4056106209754944},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37509310245513916},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.23009717464447021},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.1324804425239563}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7932542562484741},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7900891900062561},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6125898957252502},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6068388819694519},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.535658061504364},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5012743473052979},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48755019903182983},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.4766329526901245},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.43799978494644165},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.430412232875824},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4248518943786621},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4096236526966095},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4056106209754944},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37509310245513916},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.23009717464447021},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.1324804425239563},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ccnc51644.2023.10060584","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ccnc51644.2023.10060584","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 20th Consumer Communications & Networking Conference (CCNC)","raw_type":"proceedings-article"},{"id":"pmh:oai:lup.lub.lu.se:20f3fe78-bbb9-4c45-a19c-c587809e40d2","is_oa":false,"landing_page_url":"https://lup.lub.lu.se/record/20f3fe78-bbb9-4c45-a19c-c587809e40d2","pdf_url":null,"source":{"id":"https://openalex.org/S4306400536","display_name":"Lund University Publications (Lund University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I187531555","host_organization_name":"Lund University","host_organization_lineage":["https://openalex.org/I187531555"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5899999737739563,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W60686164","https://openalex.org/W1522301498","https://openalex.org/W2026453187","https://openalex.org/W2093606067","https://openalex.org/W2127543052","https://openalex.org/W2144200194","https://openalex.org/W2181523240","https://openalex.org/W2191950414","https://openalex.org/W2296719434","https://openalex.org/W2336788611","https://openalex.org/W2555676925","https://openalex.org/W2620661538","https://openalex.org/W2804841412","https://openalex.org/W2906498146","https://openalex.org/W2987793235","https://openalex.org/W3009220316","https://openalex.org/W3086419524","https://openalex.org/W3102937575","https://openalex.org/W3187356014","https://openalex.org/W4253461361","https://openalex.org/W6703470281","https://openalex.org/W6756753118"],"related_works":["https://openalex.org/W2990081132","https://openalex.org/W4296984035","https://openalex.org/W3127121676","https://openalex.org/W3108206468","https://openalex.org/W3091433184","https://openalex.org/W2902096670","https://openalex.org/W2931947761","https://openalex.org/W3108897387","https://openalex.org/W4200247875","https://openalex.org/W4387250752"],"abstract_inverted_index":{"The":[0],"growth":[1],"of":[2,8,18,25,41,103,135],"streaming":[3],"data":[4,26,75],"originating":[5],"from":[6],"Internet":[7],"Things":[9],"(IoT)-based":[10],"Industry":[11],"4.0":[12],"opens":[13],"doors":[14],"to":[15,29,45,59,120,126],"real-time":[16,39],"analytics":[17],"time-sensitive":[19,36],"services.":[20],"However,":[21],"this":[22],"ever-increasing":[23],"amount":[24],"inevitably":[27],"leads":[28],"anomalies,":[30],"resulting":[31],"in":[32,52,63,107,133],"considerable":[33],"risks":[34],"for":[35],"applications.":[37],"Thus,":[38],"detection":[40,131],"anomalies":[42,62],"is":[43,58],"critical":[44],"prevent":[46],"impending":[47],"failures":[48],"and":[49,138],"resolve":[50],"them":[51],"time.":[53,109],"Given":[54],"that":[55,114],"the":[56,100,115,127,144],"problem":[57],"detect":[60],"application-level":[61],"real":[64,108],"time,":[65],"we":[66],"develop":[67],"a":[68,78,90,104,121],"deep":[69],"learning-based":[70],"technique,":[71],"which":[72,98],"integrates":[73],"time-series":[74],"inference":[76],"with":[77],"Long-Short":[79],"Term":[80],"Memory":[81],"(LSTM)-based":[82],"prediction":[83],"model.":[84],"Our":[85,110],"proposed":[86,116],"method":[87,117],"relies":[88],"on":[89],"novel":[91],"metric":[92],"called":[93],"Sequence":[94],"Inconsistency":[95],"Distance":[96],"(SID),":[97],"determines":[99],"abnormality":[101],"likelihood":[102],"target":[105],"record":[106],"trace-driven":[111],"evaluations":[112],"indicate":[113],"achieves":[118],"up":[119],"92.6%":[122],"performance":[123],"gain":[124],"compared":[125],"current":[128],"state-of-the-art":[129],"anomaly":[130],"methods":[132],"terms":[134],"true":[136],"positive":[137,140],"false":[139],"rate":[141],"while":[142],"meeting":[143],"essential":[145],"efficiency":[146],"requirements.":[147]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}