{"id":"https://openalex.org/W3048455029","doi":"https://doi.org/10.1109/infocomwkshps50562.2020.9162884","title":"Online Traffic Classification Using Granules","display_name":"Online Traffic Classification Using Granules","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3048455029","doi":"https://doi.org/10.1109/infocomwkshps50562.2020.9162884","mag":"3048455029"},"language":"en","primary_location":{"id":"doi:10.1109/infocomwkshps50562.2020.9162884","is_oa":false,"landing_page_url":"https://doi.org/10.1109/infocomwkshps50562.2020.9162884","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE INFOCOM 2020 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","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/A5053779959","display_name":"Pingping Tang","orcid":"https://orcid.org/0000-0003-0618-507X"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pingping Tang","raw_affiliation_strings":["College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100432282","display_name":"Yuning Dong","orcid":"https://orcid.org/0000-0003-4898-331X"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuning Dong","raw_affiliation_strings":["College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080122431","display_name":"Shiwen Mao","orcid":"https://orcid.org/0000-0002-7052-0007"},"institutions":[{"id":"https://openalex.org/I82497590","display_name":"Auburn University","ror":"https://ror.org/02v80fc35","country_code":"US","type":"education","lineage":["https://openalex.org/I82497590"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shiwen Mao","raw_affiliation_strings":["Auburn University, Auburn, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Auburn University, Auburn, USA","institution_ids":["https://openalex.org/I82497590"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9724,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.78130832,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1135","last_page":"1140"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9997000098228455,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9977999925613403,"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/adaptability","display_name":"Adaptability","score":0.8512173891067505},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7687238454818726},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.6398415565490723},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6354917287826538},{"id":"https://openalex.org/keywords/traffic-classification","display_name":"Traffic classification","score":0.5764895677566528},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5520581603050232},{"id":"https://openalex.org/keywords/granular-computing","display_name":"Granular computing","score":0.5187461376190186},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49117371439933777},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3926142454147339},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.19295912981033325},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.08609780669212341}],"concepts":[{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.8512173891067505},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7687238454818726},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.6398415565490723},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6354917287826538},{"id":"https://openalex.org/C169988225","wikidata":"https://www.wikidata.org/wiki/Q7832484","display_name":"Traffic classification","level":3,"score":0.5764895677566528},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5520581603050232},{"id":"https://openalex.org/C17209119","wikidata":"https://www.wikidata.org/wiki/Q5596712","display_name":"Granular computing","level":3,"score":0.5187461376190186},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49117371439933777},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3926142454147339},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.19295912981033325},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.08609780669212341},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/infocomwkshps50562.2020.9162884","is_oa":false,"landing_page_url":"https://doi.org/10.1109/infocomwkshps50562.2020.9162884","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE INFOCOM 2020 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1972428331","https://openalex.org/W2051347137","https://openalex.org/W2163982943","https://openalex.org/W2288432723","https://openalex.org/W2343742239","https://openalex.org/W2405419323","https://openalex.org/W2508641173","https://openalex.org/W2510407591","https://openalex.org/W2530431744","https://openalex.org/W2587014894","https://openalex.org/W2590526842","https://openalex.org/W2590822257","https://openalex.org/W2753311918","https://openalex.org/W2766827306","https://openalex.org/W2781821509","https://openalex.org/W2794504349","https://openalex.org/W2804320981","https://openalex.org/W2809498732","https://openalex.org/W2883585541","https://openalex.org/W2885862920","https://openalex.org/W2903112418","https://openalex.org/W2913645831","https://openalex.org/W2928382658","https://openalex.org/W2962837596","https://openalex.org/W2974954435","https://openalex.org/W3102887392","https://openalex.org/W6696646998"],"related_works":["https://openalex.org/W2357124094","https://openalex.org/W2387399993","https://openalex.org/W2389739210","https://openalex.org/W2348924972","https://openalex.org/W2365736347","https://openalex.org/W2047454415","https://openalex.org/W2012465643","https://openalex.org/W2773751105","https://openalex.org/W4293863212","https://openalex.org/W2050261031"],"abstract_inverted_index":{"Currently,":[0],"it":[1,96],"is":[2,30,44,85],"still":[3],"a":[4,39],"great":[5],"challenge":[6],"to":[7,32,71,92,114],"achieve":[8],"online":[9],"classification":[10,41,108],"of":[11],"massive":[12],"traffic":[13,57,100],"flows":[14],"under":[15],"dynamic":[16],"network":[17,130],"environments.":[18],"Therefore,":[19],"based":[20],"on":[21],"granular":[22],"computing,":[23],"an":[24],"artificial":[25],"intelligence":[26],"computing":[27],"method,":[28],"which":[29,110],"effective":[31],"process":[33],"missing,":[34],"incomplete,":[35],"or":[36],"noisy":[37],"data,":[38],"novel":[40],"model":[42],"MGrC":[43,75],"proposed":[45],"in":[46,127],"this":[47],"paper.":[48],"In":[49],"MGrC,":[50],"we":[51],"first":[52],"define":[53],"granules":[54,70],"for":[55],"the":[56,61,68,77,83,99,106,112],"flow,":[58],"then":[59],"explore":[60],"correlation":[62],"between":[63,80],"granules,":[64],"and":[65,125],"finally":[66],"establish":[67],"structure":[69],"differentiate":[72],"flow":[73],"types.":[74],"explores":[76],"inherent":[78],"relationship":[79],"packets,":[81],"where":[82],"data":[84],"no":[86],"longer":[87],"isolated,":[88],"but":[89],"closely":[90],"related":[91],"each":[93],"other.":[94],"So,":[95],"can":[97],"identify":[98],"more":[101],"accurately":[102],"when":[103],"compared":[104],"with":[105],"traditional":[107],"methods,":[109],"assume":[111],"packets":[113],"be":[115],"independent.":[116],"The":[117],"experiment":[118],"results":[119],"also":[120],"demonstrate":[121],"its":[122],"superior":[123],"robustness":[124],"adaptability":[126],"highly":[128],"variable":[129],"environment.":[131]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}