{"id":"https://openalex.org/W3142140293","doi":"https://doi.org/10.1155/2021/6659022","title":"Deep-Feature-Based Autoencoder Network for Few-Shot Malicious Traffic Detection","display_name":"Deep-Feature-Based Autoencoder Network for Few-Shot Malicious Traffic Detection","publication_year":2021,"publication_date":"2021-03-26","ids":{"openalex":"https://openalex.org/W3142140293","doi":"https://doi.org/10.1155/2021/6659022","mag":"3142140293"},"language":"en","primary_location":{"id":"doi:10.1155/2021/6659022","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/6659022","pdf_url":"https://downloads.hindawi.com/journals/scn/2021/6659022.pdf","source":{"id":"https://openalex.org/S120683614","display_name":"Security and Communication Networks","issn_l":"1939-0114","issn":["1939-0114","1939-0122"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Security and Communication Networks","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://downloads.hindawi.com/journals/scn/2021/6659022.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049069235","display_name":"Mingshu He","orcid":"https://orcid.org/0000-0002-2896-4595"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingshu He","raw_affiliation_strings":["School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China"],"raw_orcid":"https://orcid.org/0000-0002-2896-4595","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100428970","display_name":"Xiaojuan Wang","orcid":"https://orcid.org/0000-0002-3490-963X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaojuan Wang","raw_affiliation_strings":["School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China"],"raw_orcid":"https://orcid.org/0000-0002-3490-963X","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008532258","display_name":"Junhua Zhou","orcid":"https://orcid.org/0000-0002-5538-6671"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junhua Zhou","raw_affiliation_strings":["State Key Laboratory of Intelligent Manufacturing System Technology, Beijing Institute of Electronic System Engineering, Beijing 100854, China"],"raw_orcid":"https://orcid.org/0000-0002-5538-6671","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Intelligent Manufacturing System Technology, Beijing Institute of Electronic System Engineering, Beijing 100854, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033049437","display_name":"Yuanyuan Xi","orcid":"https://orcid.org/0000-0003-0089-3980"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Yuanyuan Xi","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm SE-10044, Sweden"],"raw_orcid":"https://orcid.org/0000-0003-0089-3980","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm SE-10044, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039217360","display_name":"Lei Jin","orcid":"https://orcid.org/0000-0003-4855-2464"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Jin","raw_affiliation_strings":["School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China"],"raw_orcid":"https://orcid.org/0000-0003-4855-2464","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xinlei Wang","orcid":"https://orcid.org/0000-0002-7383-0852"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinlei Wang","raw_affiliation_strings":["School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China"],"raw_orcid":"https://orcid.org/0000-0002-7383-0852","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100428970"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":{"value":2100,"currency":"USD","value_usd":2100},"apc_paid":{"value":2100,"currency":"USD","value_usd":2100},"fwci":4.5576,"has_fulltext":true,"cited_by_count":42,"citation_normalized_percentile":{"value":0.94734799,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"2021","issue":null,"first_page":"1","last_page":"13"},"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.894059419631958},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8816220760345459},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6999799013137817},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6753787398338318},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.611494779586792},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5861872434616089},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.5802839994430542},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5662862658500671},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5412532687187195},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.503865659236908},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.41131892800331116},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4045713245868683},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3412173390388489},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.14002403616905212}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.894059419631958},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8816220760345459},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6999799013137817},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6753787398338318},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.611494779586792},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5861872434616089},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.5802839994430542},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5662862658500671},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5412532687187195},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.503865659236908},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.41131892800331116},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4045713245868683},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3412173390388489},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.14002403616905212},{"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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1155/2021/6659022","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/6659022","pdf_url":"https://downloads.hindawi.com/journals/scn/2021/6659022.pdf","source":{"id":"https://openalex.org/S120683614","display_name":"Security and Communication Networks","issn_l":"1939-0114","issn":["1939-0114","1939-0122"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Security and Communication Networks","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:09683c87fbb746a2a8d192ddfb2a8c3e","is_oa":false,"landing_page_url":"https://doaj.org/article/09683c87fbb746a2a8d192ddfb2a8c3e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Security and Communication Networks, Vol 2021 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2021/6659022","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/6659022","pdf_url":"https://downloads.hindawi.com/journals/scn/2021/6659022.pdf","source":{"id":"https://openalex.org/S120683614","display_name":"Security and Communication Networks","issn_l":"1939-0114","issn":["1939-0114","1939-0122"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Security and Communication Networks","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5299944411","display_name":"\u57fa\u4e8e\u7269\u8054\u7f51\u534f\u540c\u8ba1\u7b97\u7684\u884c\u4e3a\u8ba4\u77e5\u4e0e\u9690\u79c1\u5b89\u5168\u7814\u7a76","funder_award_id":"62071056","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321470","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3142140293.pdf","grobid_xml":"https://content.openalex.org/works/W3142140293.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W61646295","https://openalex.org/W2062227835","https://openalex.org/W2062401262","https://openalex.org/W2096474000","https://openalex.org/W2107427360","https://openalex.org/W2399941526","https://openalex.org/W2557831587","https://openalex.org/W2606697812","https://openalex.org/W2618530766","https://openalex.org/W2620369751","https://openalex.org/W2752782242","https://openalex.org/W2765181145","https://openalex.org/W2767106145","https://openalex.org/W2767359317","https://openalex.org/W2805674924","https://openalex.org/W2889640721","https://openalex.org/W2898652425","https://openalex.org/W2928842143","https://openalex.org/W2942292460","https://openalex.org/W2946127746","https://openalex.org/W2946156428","https://openalex.org/W2954996726","https://openalex.org/W2960634417","https://openalex.org/W2972414240","https://openalex.org/W3002972450","https://openalex.org/W3016011534","https://openalex.org/W3035510612","https://openalex.org/W3035604903","https://openalex.org/W3038955483","https://openalex.org/W3040566484","https://openalex.org/W3042784555","https://openalex.org/W3046042764","https://openalex.org/W3090139223","https://openalex.org/W3091379954","https://openalex.org/W3095473261","https://openalex.org/W3098957257","https://openalex.org/W3139818551"],"related_works":["https://openalex.org/W3186512740","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4363671829","https://openalex.org/W4392946183","https://openalex.org/W2780476542","https://openalex.org/W4405887298","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570"],"abstract_inverted_index":{"With":[0],"the":[1,16,22,50,66,91,95,116,135,141,154,159,171,188,192,197,221,233,241,245],"increase":[2],"of":[3,21,24,46,52,60,68,98,134,161,174,194,199],"Internet":[4,23],"visits":[5],"and":[6,12,18,127,140,237],"connections,":[7],"it":[8,83],"is":[9,55,84,202],"becoming":[10],"essential":[11],"arduous":[13],"to":[14,89,114,153,157,232],"protect":[15],"networks":[17,125],"different":[19],"devices":[20],"Things":[25],"(IoT)":[26],"from":[27],"malicious":[28,69],"attacks.":[29],"The":[30,165,212],"intrusion":[31],"detection":[32,93,107,120,201,246],"systems":[33],"(IDSs)":[34],"based":[35,121],"on":[36,122],"supervised":[37,137],"machine":[38],"learning":[39],"(ML)":[40],"methods":[41],"require":[42],"a":[43,85,110,147,249],"large":[44],"number":[45,51,97],"labeled":[47],"samples.":[48,101],"However,":[49],"abnormal":[53,99,112,149,200],"behaviors":[54],"far":[56],"less":[57],"than":[58],"that":[59,65,216],"normal":[61,175,208],"behaviors,":[62],"let":[63],"alone":[64],"shots":[67],"behavior":[70,100,227],"samples":[71,113,150,176,209],"which":[72],"can":[73,219],"be":[74],"intercepted":[75],"as":[76,177],"training":[77,178,207],"dataset":[78],"are":[79,151],"actually":[80],"limited.":[81],"Consequently,":[82],"key":[86],"research":[87],"topic":[88],"conduct":[90],"anomaly":[92,106,228],"for":[94],"small":[96,195],"This":[102,130],"paper":[103],"proposes":[104],"an":[105],"model":[108,131,236,243],"with":[109,205,210],"few":[111,148],"solve":[115,220],"problem":[117],"in":[118,187,225,248],"few-shot":[119],"convolutional":[123],"neural":[124],"(CNN)":[126],"autoencoder":[128],"(AE).":[129],"mainly":[132],"consists":[133],"CNN-based":[136],"pretraining":[138,189,193],"module":[139,156,168],"AE-based":[142],"data":[143,166],"reconstruction":[144,167],"module.":[145,190],"Only":[146],"utilized":[152],"pretrain":[155],"build":[158],"structure":[160],"extracting":[162],"deep":[163,172],"features.":[164],"simply":[169],"chooses":[170],"features":[173],"data.":[179],"There":[180],"also":[181],"exist":[182],"some":[183],"effective":[184],"attention":[185],"mechanisms":[186],"Through":[191],"samples,":[196],"accuracy":[198],"improved":[203],"compared":[204],"merely":[206],"AE.":[211],"simulation":[213],"results":[214,247],"prove":[215],"this":[217],"solution":[218],"above":[222],"problems":[223],"occurring":[224],"network":[226],"detection.":[229],"In":[230],"comparison":[231],"original":[234],"AE":[235],"other":[238],"clustering":[239],"methods,":[240],"proposed":[242],"advances":[244],"visible":[250],"way.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":4}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
