{"id":"https://openalex.org/W3009136487","doi":"https://doi.org/10.1109/icoin48656.2020.9016470","title":"Cross-domain Network Traffic Classification Using Unsupervised Domain Adaptation","display_name":"Cross-domain Network Traffic Classification Using Unsupervised Domain Adaptation","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3009136487","doi":"https://doi.org/10.1109/icoin48656.2020.9016470","mag":"3009136487"},"language":"en","primary_location":{"id":"doi:10.1109/icoin48656.2020.9016470","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icoin48656.2020.9016470","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Information Networking (ICOIN)","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/A5043932367","display_name":"Dongpu Li","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dongpu Li","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082713659","display_name":"Qifeng Yuan","orcid":"https://orcid.org/0000-0002-2010-5091"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qifeng Yuan","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100428606","display_name":"Tan Li","orcid":"https://orcid.org/0000-0001-6129-4792"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tan Li","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045720734","display_name":"Shuangwu Chen","orcid":"https://orcid.org/0000-0003-2817-9738"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuangwu Chen","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083577000","display_name":"Jian Yang","orcid":"https://orcid.org/0000-0002-7329-4738"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Yang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5043932367"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":0.3977,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.67064826,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"245","last_page":"250"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9994999766349792,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9994999766349792,"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":0.9904000163078308,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9764000177383423,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7678282260894775},{"id":"https://openalex.org/keywords/traffic-classification","display_name":"Traffic classification","score":0.6596679091453552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5977429747581482},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.530090868473053},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5296936631202698},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5280811786651611},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.5137304067611694},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4633612632751465},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.4470415711402893},{"id":"https://openalex.org/keywords/malware","display_name":"Malware","score":0.4372740685939789},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.415982723236084},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.09756991267204285},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.08706048130989075}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7678282260894775},{"id":"https://openalex.org/C169988225","wikidata":"https://www.wikidata.org/wiki/Q7832484","display_name":"Traffic classification","level":3,"score":0.6596679091453552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5977429747581482},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.530090868473053},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5296936631202698},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5280811786651611},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.5137304067611694},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4633612632751465},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.4470415711402893},{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.4372740685939789},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.415982723236084},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.09756991267204285},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.08706048130989075},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icoin48656.2020.9016470","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icoin48656.2020.9016470","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Information Networking (ICOIN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1803485664","https://openalex.org/W2062401262","https://openalex.org/W2096943734","https://openalex.org/W2115403315","https://openalex.org/W2165698076","https://openalex.org/W2463241543","https://openalex.org/W2786808285","https://openalex.org/W2890479120","https://openalex.org/W2897202622","https://openalex.org/W2921165530","https://openalex.org/W2936870844","https://openalex.org/W2962608904","https://openalex.org/W2963852441","https://openalex.org/W2967474335","https://openalex.org/W6718795669","https://openalex.org/W6755186462"],"related_works":["https://openalex.org/W4301398392","https://openalex.org/W2997818875","https://openalex.org/W4379534844","https://openalex.org/W266939152","https://openalex.org/W2587627203","https://openalex.org/W3178296362","https://openalex.org/W2924962435","https://openalex.org/W3103293871","https://openalex.org/W2393595964","https://openalex.org/W4302774412"],"abstract_inverted_index":{"Traffic":[0,89],"classification":[1,90,136,170],"greatly":[2],"contributes":[3],"to":[4,41,82,93,109,122,133,138,160,164],"traffic":[5,7,59,72,85,112,169,210],"billing,":[6],"engineering,":[8],"malware":[9],"detection":[10],"and":[11,45,75,143,150],"so":[12],"forth.":[13],"Motivated":[14],"by":[15,176],"the":[16,26,58,70,84,95,114,119,134,144,162,166,182,189],"recent":[17],"advents":[18],"in":[19],"machine":[20],"learning":[21],"(ML)":[22],"including":[23],"deep":[24],"learning,":[25],"statistical-based":[27],"method":[28],"has":[29],"achieved":[30],"a":[31,36,43,106,127],"satisfactory":[32],"performance.":[33],"Despite":[34],"that,":[35,155],"pre-trained":[37],"model":[38],"is":[39,49,56,91,118,131],"insufficient":[40],"tackle":[42,94,123],"diverse":[44],"uncertain":[46],"network":[47,97,178],"which":[48,117],"rarely":[50],"considered":[51],"yet.":[52],"The":[53,197],"underlying":[54],"problem":[55],"that":[57,201],"used":[60,159],"during":[61],"training":[62,148],"(source":[63],"domain)":[64,74],"could":[65],"be":[66],"very":[67],"different":[68,87],"from":[69,86],"test":[71],"(target":[73],"meanwhile":[76],"there":[77],"are":[78,158,174],"not":[79],"sufficient":[80],"data":[81,149,157],"cover":[83],"domains.":[88],"expected":[92],"cross-domain":[96,111,209],"traffic.":[98],"By":[99],"using":[100],"unsupervised":[101],"domain":[102],"adaptation,":[103],"we":[104,187],"propose":[105],"novel":[107],"framework":[108,191],"classify":[110],"for":[113,208],"above":[115],"scenario,":[116],"first":[120],"attempt":[121],"this":[124],"problem.":[125],"Specifically,":[126],"feature":[128],"transformation":[129],"module":[130],"added":[132],"current":[135],"task":[137],"adapt":[139],"both":[140],"marginal":[141],"distribution":[142,146],"conditional":[145],"of":[147,168,184],"new":[151],"unlabeled":[152],"data.":[153],"After":[154],"transformed":[156],"retrain":[161],"classifier":[163],"boost":[165],"accuracy":[167,205],"when":[171],"statistical":[172],"features":[173],"changed":[175],"varied":[177],"conditions.":[179],"To":[180],"prove":[181],"universality":[183],"our":[185,202],"approach,":[186],"evaluate":[188],"proposed":[190],"based":[192],"on":[193],"five":[194],"common":[195],"models.":[196],"experiment":[198],"results":[199],"demonstrate":[200],"approach":[203],"achieves":[204],"over":[206],"86%":[207],"classification.":[211]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}