{"id":"https://openalex.org/W3214335780","doi":"https://doi.org/10.1109/access.2021.3128181","title":"A Network Traffic Classification Method Based on Graph Convolution and LSTM","display_name":"A Network Traffic Classification Method Based on Graph Convolution and LSTM","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3214335780","doi":"https://doi.org/10.1109/access.2021.3128181","mag":"3214335780"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3128181","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3128181","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2021.3128181","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100602975","display_name":"Yang Pan","orcid":"https://orcid.org/0009-0004-4610-7230"},"institutions":[{"id":"https://openalex.org/I4210148639","display_name":"Wuhan Engineering Science & Technology Institute","ror":"https://ror.org/04ez3r306","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210148639"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yang Pan","raw_affiliation_strings":["China Energy Science and Technology Research Institute Co., Ltd Wuhan Branch, Wuhan 430077, China"],"affiliations":[{"raw_affiliation_string":"China Energy Science and Technology Research Institute Co., Ltd Wuhan Branch, Wuhan 430077, China","institution_ids":["https://openalex.org/I4210148639"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114526293","display_name":"Xiao Zhang","orcid":"https://orcid.org/0000-0003-4065-4407"},"institutions":[{"id":"https://openalex.org/I4210148639","display_name":"Wuhan Engineering Science & Technology Institute","ror":"https://ror.org/04ez3r306","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210148639"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Zhang","raw_affiliation_strings":["China Energy Science and Technology Research Institute Co., Ltd Wuhan Branch, Wuhan 430077, China"],"affiliations":[{"raw_affiliation_string":"China Energy Science and Technology Research Institute Co., Ltd Wuhan Branch, Wuhan 430077, China","institution_ids":["https://openalex.org/I4210148639"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101473033","display_name":"Hui Jiang","orcid":"https://orcid.org/0000-0002-5640-5686"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Jiang","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan 430072, China. (e-mail: jh0829@whu.edu.cn)","School of Computer Science, Wuhan University, Wuhan, China","ORCiD"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan 430072, China. (e-mail: jh0829@whu.edu.cn)","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060261737","display_name":"Cong Li","orcid":"https://orcid.org/0000-0003-4543-215X"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210100789","display_name":"Wuhan College","ror":"https://ror.org/01dashf18","country_code":"CN","type":"nonprofit","lineage":["https://openalex.org/I4210100789"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cong Li","raw_affiliation_strings":["Wuhan City College, Wuhan 430083, China and School of Computer Science, Wuhan University, Wuhan 430072, China"],"affiliations":[{"raw_affiliation_string":"Wuhan City College, Wuhan 430083, China and School of Computer Science, Wuhan University, Wuhan 430072, China","institution_ids":["https://openalex.org/I37461747","https://openalex.org/I4210100789"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100602975"],"corresponding_institution_ids":["https://openalex.org/I4210148639"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.5597,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.89955697,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"158261","last_page":"158272"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9995999932289124,"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":0.9995999932289124,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9993000030517578,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8055992126464844},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.661521315574646},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6098559498786926},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5777603387832642},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5630474090576172},{"id":"https://openalex.org/keywords/traffic-classification","display_name":"Traffic classification","score":0.531216025352478},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5271346569061279},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5176442265510559},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.4874999225139618},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.445158988237381},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43543541431427},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.4101860523223877},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.23043149709701538},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.14033615589141846}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8055992126464844},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.661521315574646},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6098559498786926},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5777603387832642},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5630474090576172},{"id":"https://openalex.org/C169988225","wikidata":"https://www.wikidata.org/wiki/Q7832484","display_name":"Traffic classification","level":3,"score":0.531216025352478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5271346569061279},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5176442265510559},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.4874999225139618},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.445158988237381},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43543541431427},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.4101860523223877},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.23043149709701538},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.14033615589141846},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3128181","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3128181","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:efa3cd7d73dc471592d08ee90056e436","is_oa":true,"landing_page_url":"https://doaj.org/article/efa3cd7d73dc471592d08ee90056e436","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 158261-158272 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3128181","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3128181","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8384381454","display_name":null,"funder_award_id":"61772386","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2187089797","https://openalex.org/W2296509296","https://openalex.org/W2765533176","https://openalex.org/W2783741806","https://openalex.org/W2801080689","https://openalex.org/W2805665873","https://openalex.org/W2895859872","https://openalex.org/W2901504064","https://openalex.org/W2903942159","https://openalex.org/W2916106175","https://openalex.org/W2924211215","https://openalex.org/W2946373483","https://openalex.org/W2962946486","https://openalex.org/W2964015378","https://openalex.org/W3001675796","https://openalex.org/W3017346274","https://openalex.org/W3025255083","https://openalex.org/W3032021129","https://openalex.org/W3036727658","https://openalex.org/W3043077209","https://openalex.org/W3082065751","https://openalex.org/W3086419524","https://openalex.org/W3093410479","https://openalex.org/W3094686023","https://openalex.org/W3097487972","https://openalex.org/W3097529015","https://openalex.org/W3120162223","https://openalex.org/W3154450391","https://openalex.org/W3185895012","https://openalex.org/W6726873649","https://openalex.org/W6752449833","https://openalex.org/W6760001035"],"related_works":["https://openalex.org/W2989490741","https://openalex.org/W3092506759","https://openalex.org/W2367545121","https://openalex.org/W4248881655","https://openalex.org/W2482165163","https://openalex.org/W3010890513","https://openalex.org/W120741642","https://openalex.org/W138569904","https://openalex.org/W2390914021","https://openalex.org/W2389417819"],"abstract_inverted_index":{"In":[0,53],"the":[1,30,46,56,83,89,95,110,113,118,127,133,155,158],"identification":[2],"of":[3,20,33,55,98,112,136,157],"normal":[4],"and":[5,73,101,151,161],"abnormal":[6],"traffic":[7,22,34,51,61,84,138],"flows,":[8,62],"Convolutional":[9],"Neural":[10],"Network":[11],"(CNN)":[12],"is":[13,28,115],"commonly":[14],"used":[15],"to":[16,38,93,104],"extract":[17,94,105,132],"spatial":[18,48,96,99],"features":[19,97,135],"network":[21,60,92,137],"at":[23],"present.":[24],"However,":[25],"its":[26,106],"limitation":[27],"that":[29,126],"one-dimensional":[31],"form":[32],"flow":[35,85],"data":[36,80,121],"needs":[37],"be":[39],"converted":[40],"into":[41],"two-dimensional":[42],"form,":[43],"without":[44],"considering":[45],"potential":[47,57,134],"correlation":[49,58],"between":[50,59],"flows.":[52],"view":[54],"this":[63],"paper":[64],"proposes":[65],"a":[66],"classification":[67,165],"method":[68,129],"based":[69],"on":[70,82,117],"graph":[71,90],"convolution":[72],"Long-Short":[74],"Term":[75],"Memory":[76],"(LSTM).":[77],"First,":[78],"perform":[79],"preprocessing":[81],"data,":[86],"then":[87],"use":[88,102],"convolutional":[91],"topology":[100],"LSTM":[103,149],"temporal":[107],"features.":[108],"Finally,":[109],"performance":[111],"algorithm":[114,160],"evaluated":[116],"sampled":[119],"UNSW-NB15":[120],"set.":[122],"Experimental":[123],"results":[124],"show":[125],"proposed":[128,159],"can":[130],"effectively":[131],"data.":[139],"Compared":[140],"with":[141],"other":[142],"methods":[143],"such":[144],"as":[145],"feature":[146],"selection,":[147],"bidirectional":[148],"(BiDLSTM)":[150],"CNN-LSTM,":[152],"it":[153],"proves":[154],"effectiveness":[156],"performs":[162],"better":[163],"in":[164],"performance.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2}],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2025-10-10T00:00:00"}
