{"id":"https://openalex.org/W4308279687","doi":"https://doi.org/10.1109/nas55553.2022.9925450","title":"Weakly Supervised Learning for Network Traffic Classification","display_name":"Weakly Supervised Learning for Network Traffic Classification","publication_year":2022,"publication_date":"2022-10-01","ids":{"openalex":"https://openalex.org/W4308279687","doi":"https://doi.org/10.1109/nas55553.2022.9925450"},"language":"en","primary_location":{"id":"doi:10.1109/nas55553.2022.9925450","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nas55553.2022.9925450","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Networking, Architecture and Storage (NAS)","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/A5048859921","display_name":"Onur Barut","orcid":"https://orcid.org/0000-0002-0599-1515"},"institutions":[{"id":"https://openalex.org/I133738476","display_name":"University of Massachusetts Lowell","ror":"https://ror.org/03hamhx47","country_code":"US","type":"education","lineage":["https://openalex.org/I133738476"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Onur Barut","raw_affiliation_strings":["University of Massachusetts Lowell,Dept. of Electrical and Computer Eng.,Lowell,USA","Dept. of Electrical and Computer Eng., University of Massachusetts Lowell, Lowell, USA"],"affiliations":[{"raw_affiliation_string":"University of Massachusetts Lowell,Dept. of Electrical and Computer Eng.,Lowell,USA","institution_ids":["https://openalex.org/I133738476"]},{"raw_affiliation_string":"Dept. of Electrical and Computer Eng., University of Massachusetts Lowell, Lowell, USA","institution_ids":["https://openalex.org/I133738476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100378800","display_name":"Tong Zhang","orcid":"https://orcid.org/0000-0002-7025-6365"},"institutions":[{"id":"https://openalex.org/I1343180700","display_name":"Intel (United States)","ror":"https://ror.org/01ek73717","country_code":"US","type":"company","lineage":["https://openalex.org/I1343180700"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tong Zhang","raw_affiliation_strings":["Network Platforms Group, Intel Corporation,Santa Clara,USA","Network Platforms Group, Intel Corporation, Santa Clara, USA"],"affiliations":[{"raw_affiliation_string":"Network Platforms Group, Intel Corporation,Santa Clara,USA","institution_ids":["https://openalex.org/I1343180700"]},{"raw_affiliation_string":"Network Platforms Group, Intel Corporation, Santa Clara, USA","institution_ids":["https://openalex.org/I1343180700"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101732106","display_name":"Peilong Li","orcid":"https://orcid.org/0000-0002-1325-2667"},"institutions":[{"id":"https://openalex.org/I35429941","display_name":"Elizabethtown College","ror":"https://ror.org/01y0mgq54","country_code":"US","type":"education","lineage":["https://openalex.org/I35429941"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peilong Li","raw_affiliation_strings":["Elizabethtown College,Dept. of Computer Science,Elizabethtown,USA","Dept. of Computer Science, Elizabethtown College, Elizabethtown, USA"],"affiliations":[{"raw_affiliation_string":"Elizabethtown College,Dept. of Computer Science,Elizabethtown,USA","institution_ids":["https://openalex.org/I35429941"]},{"raw_affiliation_string":"Dept. of Computer Science, Elizabethtown College, Elizabethtown, USA","institution_ids":["https://openalex.org/I35429941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5048859921"],"corresponding_institution_ids":["https://openalex.org/I133738476"],"apc_list":null,"apc_paid":null,"fwci":0.1326,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5377982,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"abs 1812 9761","issue":null,"first_page":"1","last_page":"4"},"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":0.9998999834060669,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9994000196456909,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9976999759674072,"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/computer-science","display_name":"Computer science","score":0.7893932461738586},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.751160204410553},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6791396141052246},{"id":"https://openalex.org/keywords/traffic-classification","display_name":"Traffic classification","score":0.6614700555801392},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6545031666755676},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5847647190093994},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.569998025894165},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.5090010166168213},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47873708605766296},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4537487328052521},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4408787488937378},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.43552517890930176},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.4225130081176758},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3795304298400879},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3226637542247772},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.12053832411766052}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7893932461738586},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.751160204410553},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6791396141052246},{"id":"https://openalex.org/C169988225","wikidata":"https://www.wikidata.org/wiki/Q7832484","display_name":"Traffic classification","level":3,"score":0.6614700555801392},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6545031666755676},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5847647190093994},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.569998025894165},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.5090010166168213},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47873708605766296},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4537487328052521},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4408787488937378},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.43552517890930176},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.4225130081176758},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3795304298400879},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3226637542247772},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.12053832411766052},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/nas55553.2022.9925450","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nas55553.2022.9925450","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Networking, Architecture and Storage (NAS)","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/W2343828539","https://openalex.org/W2760017128","https://openalex.org/W2769041395","https://openalex.org/W2912327636","https://openalex.org/W2921871306","https://openalex.org/W2959716049","https://openalex.org/W2996980851","https://openalex.org/W2998483179","https://openalex.org/W3022362371","https://openalex.org/W3044193521","https://openalex.org/W3046383450","https://openalex.org/W3118111094","https://openalex.org/W3136394420","https://openalex.org/W3190554502","https://openalex.org/W4312408104","https://openalex.org/W6757578793"],"related_works":["https://openalex.org/W4312414840","https://openalex.org/W2794908468","https://openalex.org/W4206276646","https://openalex.org/W2943467239","https://openalex.org/W1571801203","https://openalex.org/W101422005","https://openalex.org/W192740413","https://openalex.org/W3004135598","https://openalex.org/W2952937263","https://openalex.org/W2131153761"],"abstract_inverted_index":{"With":[0],"advances":[1],"in":[2],"deep":[3,15,92,142],"learning":[4,52],"methods":[5],"and":[6,31,155],"an":[7],"enormous":[8],"amount":[9],"of":[10,61,69,98],"network":[11,126],"traffic":[12,20,26,127],"data,":[13],"training":[14],"neural":[16],"networks":[17],"for":[18,125],"malware":[19],"classification":[21,59,128,135],"directly":[22],"with":[23,65],"the":[24,41,58,111,119,146],"raw":[25],"data":[27,35,71,77],"has":[28,44],"gained":[29],"popularity":[30],"success.":[32],"Obtaining":[33],"labeled":[34,70],"to":[36,56,85,109,117,121,144],"train":[37],"deeper":[38],"models,":[39],"on":[40,102],"other":[42],"hand,":[43],"recently":[45],"become":[46],"a":[47,66,83,133],"significant":[48],"challenge.":[49],"Weakly":[50],"supervised":[51],"approaches":[53],"that":[54,113,140],"aim":[55],"improve":[57],"accuracy":[60,124,151],"classifiers":[62],"previously":[63],"trained":[64],"small":[67],"quantity":[68],"using":[72,129],"widely":[73],"available":[74],"but":[75],"unlabeled":[76,130,147],"have":[78],"grown":[79],"more":[80],"popular":[81],"as":[82,94,106],"solution":[84],"this":[86],"problem.":[87],"We":[88],"propose":[89],"employing":[90],"several":[91],"models":[93,143],"labeling":[95],"functions":[96],"instead":[97],"manual":[99],"definition":[100],"based":[101],"hand-crafted":[103],"features,":[104],"such":[105],"Snorkel":[107],"approach,":[108],"estimate":[110],"labels":[112],"will":[114],"be":[115],"utilized":[116],"tune":[118],"classifier":[120],"increase":[122],"its":[123],"data.":[131],"In":[132],"multi-class":[134],"scenario,":[136],"our":[137],"findings":[138],"demonstrate":[139],"utilizing":[141],"label":[145],"chunk":[148],"can":[149],"enhance":[150],"by":[152,157],"1.5":[153],"%":[154],"F1-score":[156],"5%.":[158]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
