{"id":"https://openalex.org/W4313590336","doi":"https://doi.org/10.1186/s42400-022-00134-9","title":"Practical autoencoder based anomaly detection by using vector reconstruction error","display_name":"Practical autoencoder based anomaly detection by using vector reconstruction error","publication_year":2023,"publication_date":"2023-01-04","ids":{"openalex":"https://openalex.org/W4313590336","doi":"https://doi.org/10.1186/s42400-022-00134-9"},"language":"en","primary_location":{"id":"doi:10.1186/s42400-022-00134-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42400-022-00134-9","pdf_url":"https://cybersecurity.springeropen.com/counter/pdf/10.1186/s42400-022-00134-9","source":{"id":"https://openalex.org/S3035238565","display_name":"Cybersecurity","issn_l":"2523-3246","issn":["2523-3246"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybersecurity","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://cybersecurity.springeropen.com/counter/pdf/10.1186/s42400-022-00134-9","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018043866","display_name":"Hasan Torabi","orcid":"https://orcid.org/0000-0001-8157-7853"},"institutions":[{"id":"https://openalex.org/I181744264","display_name":"Kharazmi University","ror":"https://ror.org/05hsgex59","country_code":"IR","type":"education","lineage":["https://openalex.org/I181744264"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Hasan Torabi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran","institution_ids":["https://openalex.org/I181744264"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086084081","display_name":"Seyedeh Leili Mirtaheri","orcid":"https://orcid.org/0000-0002-0744-5876"},"institutions":[{"id":"https://openalex.org/I181744264","display_name":"Kharazmi University","ror":"https://ror.org/05hsgex59","country_code":"IR","type":"education","lineage":["https://openalex.org/I181744264"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Seyedeh Leili Mirtaheri","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran","institution_ids":["https://openalex.org/I181744264"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031964906","display_name":"Sergio Greco","orcid":"https://orcid.org/0000-0003-2966-3484"},"institutions":[{"id":"https://openalex.org/I45204951","display_name":"University of Calabria","ror":"https://ror.org/02rc97e94","country_code":"IT","type":"education","lineage":["https://openalex.org/I45204951"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Sergio Greco","raw_affiliation_strings":["Department of Informatics, Modeling, Electronics and System Engineering, University of Calabria, Arcavacata, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Informatics, Modeling, Electronics and System Engineering, University of Calabria, Arcavacata, Italy","institution_ids":["https://openalex.org/I45204951"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5018043866"],"corresponding_institution_ids":["https://openalex.org/I181744264"],"apc_list":null,"apc_paid":null,"fwci":26.1215,"has_fulltext":true,"cited_by_count":132,"citation_normalized_percentile":{"value":0.99816202,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"6","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","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/T10400","display_name":"Network Security and Intrusion Detection","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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998000264167786,"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/T12127","display_name":"Software System Performance and Reliability","score":0.9980000257492065,"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/autoencoder","display_name":"Autoencoder","score":0.9002887010574341},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.8110613822937012},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7637062072753906},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.6999326348304749},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6661176681518555},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6656016111373901},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5355780720710754},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4126441180706024},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34328562021255493},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3318954110145569},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2965693175792694},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07254379987716675}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9002887010574341},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8110613822937012},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7637062072753906},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.6999326348304749},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6661176681518555},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6656016111373901},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5355780720710754},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4126441180706024},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34328562021255493},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3318954110145569},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2965693175792694},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07254379987716675},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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},{"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:10.1186/s42400-022-00134-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42400-022-00134-9","pdf_url":"https://cybersecurity.springeropen.com/counter/pdf/10.1186/s42400-022-00134-9","source":{"id":"https://openalex.org/S3035238565","display_name":"Cybersecurity","issn_l":"2523-3246","issn":["2523-3246"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybersecurity","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:65668d32267c42339b01ef2066e0e0a2","is_oa":true,"landing_page_url":"https://doaj.org/article/65668d32267c42339b01ef2066e0e0a2","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Cybersecurity, Vol 6, Iss 1, Pp 1-13 (2023)","raw_type":"article"},{"id":"pmh:oai:zenodo.org:110065","is_oa":true,"landing_page_url":"https://www.openaccessrepository.it/record/110065","pdf_url":null,"source":{"id":"https://openalex.org/S4306402478","display_name":"INFM-OAR (INFN Catania)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210116497","host_organization_name":"Istituto Nazionale di Fisica Nucleare, Sezione di Catania","host_organization_lineage":["https://openalex.org/I4210116497"],"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":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1186/s42400-022-00134-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42400-022-00134-9","pdf_url":"https://cybersecurity.springeropen.com/counter/pdf/10.1186/s42400-022-00134-9","source":{"id":"https://openalex.org/S3035238565","display_name":"Cybersecurity","issn_l":"2523-3246","issn":["2523-3246"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybersecurity","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4313590336.pdf"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W2017257315","https://openalex.org/W2054988483","https://openalex.org/W2114296561","https://openalex.org/W2127979711","https://openalex.org/W2783047817","https://openalex.org/W2904014272","https://openalex.org/W2908818413","https://openalex.org/W2949676527","https://openalex.org/W2959716986","https://openalex.org/W3005084388","https://openalex.org/W3016010691","https://openalex.org/W3024993002","https://openalex.org/W3035311645","https://openalex.org/W3035965352","https://openalex.org/W3039782758","https://openalex.org/W3096790059","https://openalex.org/W3099878876","https://openalex.org/W3101655119","https://openalex.org/W3107519323","https://openalex.org/W3119708449","https://openalex.org/W3121022046","https://openalex.org/W3129768586","https://openalex.org/W3196617585","https://openalex.org/W4206130810","https://openalex.org/W4210713267","https://openalex.org/W4226214891","https://openalex.org/W4234971943","https://openalex.org/W4241974762","https://openalex.org/W4376849835"],"related_works":["https://openalex.org/W3186512740","https://openalex.org/W3017266184","https://openalex.org/W3202913553","https://openalex.org/W3194885736","https://openalex.org/W3046391934","https://openalex.org/W4363671829","https://openalex.org/W2806741695","https://openalex.org/W3210364259","https://openalex.org/W4290647774","https://openalex.org/W3189286258"],"abstract_inverted_index":{"Abstract":[0],"Nowadays,":[1],"cloud":[2,42,49,126],"computing":[3,14,24,127],"provides":[4],"easy":[5],"access":[6],"to":[7,37,159,226,248,279],"a":[8,132,178,210,220,244,258],"set":[9],"of":[10,41,94,135,168,205,231,271,285],"variable":[11],"and":[12,32,46,91,139,290],"configurable":[13],"resources":[15],"based":[16,119,188],"on":[17,48,120,189],"user":[18],"demand":[19],"through":[20,28],"the":[21,38,136,146,166,194,202,216,228,250,254,263,269,272,280],"network.":[22],"Cloud":[23],"services":[25],"are":[26,55,70],"available":[27],"common":[29],"internet":[30],"protocols":[31],"network":[33,61,66,78,107],"standards.":[34],"In":[35,157],"addition":[36],"unique":[39],"benefits":[40],"computing,":[43],"insecure":[44],"communication":[45],"attacks":[47],"networks":[50],"cannot":[51],"be":[52],"ignored.":[53],"There":[54],"several":[56],"techniques":[57,199],"for":[58,122],"dealing":[59],"with":[60,142],"attacks.":[62],"To":[63],"this":[64],"end,":[65],"anomaly":[67,97,123,153,161,169,185,197,237],"detection":[68,98,124,186,198],"systems":[69,99],"widely":[71],"used":[72,150],"as":[73,151,209,235,257],"an":[74,116,152,183,236],"effective":[75],"countermeasure":[76],"against":[77],"anomalies.":[79,95,251],"The":[80,129],"anomaly-based":[81],"approach":[82,180],"generally":[83],"learns":[84,131],"normal":[85,137,164],"traffic":[86,108],"patterns":[87,93],"in":[88,104,125,262,283],"various":[89],"ways":[90],"identifies":[92],"Network":[96],"have":[100,176],"gained":[101],"much":[102],"attention":[103],"intelligently":[105],"monitoring":[106],"using":[109],"machine":[110],"learning":[111],"methods.":[112],"This":[113,222],"paper":[114],"presents":[115],"efficient":[117],"model":[118,225],"autoencoders":[121],"networks.":[128],"autoencoder":[130],"basic":[133],"representation":[134],"data":[138,162,190],"its":[140],"reconstruction":[141,147,191,203,217,229],"minimum":[143],"error.":[144,192],"Therefore,":[145],"error":[148,204,218,230],"is":[149,219],"or":[154,238],"classification":[155,167,239,246],"metric.":[156,240],"addition,":[158],"detecting":[160],"from":[163],"data,":[165],"types":[170],"has":[171,275],"also":[172],"been":[173],"investigated.":[174],"We":[175,241,252],"proposed":[177,273],"new":[179],"by":[181],"examining":[182],"autoencoder\u2019s":[184],"method":[187,274],"Unlike":[193],"existing":[195,281],"autoencoder-based":[196],"that":[200,215,268],"consider":[201],"all":[206],"input":[207,233],"features":[208],"single":[211],"value,":[212],"we":[213],"assume":[214],"vector.":[221],"enables":[223],"our":[224],"use":[227,253],"every":[232],"feature":[234],"further":[242],"propose":[243],"multi-class":[245],"structure":[247],"classify":[249],"CIDDS-001":[255],"dataset":[256,261],"commonly":[259],"accepted":[260],"literature.":[264],"Our":[265],"evaluations":[266],"show":[267],"performance":[270],"improved":[276],"considerably":[277],"compared":[278],"ones":[282],"terms":[284],"accuracy,":[286],"recall,":[287],"false-positive":[288],"rate,":[289],"F1-score":[291],"metrics.":[292]},"counts_by_year":[{"year":2026,"cited_by_count":17},{"year":2025,"cited_by_count":61},{"year":2024,"cited_by_count":36},{"year":2023,"cited_by_count":18}],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-10-10T00:00:00"}
