{"id":"https://openalex.org/W1999780609","doi":"https://doi.org/10.1109/ncc.2015.7084879","title":"Network traffic classification in encrypted environment: A case study of Google Hangout","display_name":"Network traffic classification in encrypted environment: A case study of Google Hangout","publication_year":2015,"publication_date":"2015-02-01","ids":{"openalex":"https://openalex.org/W1999780609","doi":"https://doi.org/10.1109/ncc.2015.7084879","mag":"1999780609"},"language":"en","primary_location":{"id":"doi:10.1109/ncc.2015.7084879","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ncc.2015.7084879","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Twenty First National Conference on Communications (NCC)","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/A5077102590","display_name":"Jayeeta Datta","orcid":null},"institutions":[{"id":"https://openalex.org/I64295750","display_name":"Indian Institute of Technology Indore","ror":"https://ror.org/01hhf7w52","country_code":"IN","type":"education","lineage":["https://openalex.org/I64295750"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Jayeeta Datta","raw_affiliation_strings":["Department of Computer Science and Engineering, Indian Institute of Technology, Indore","[Department of Computer Science and Engineering, Indian Institute of Technology, Indore, India]"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology, Indore","institution_ids":["https://openalex.org/I64295750"]},{"raw_affiliation_string":"[Department of Computer Science and Engineering, Indian Institute of Technology, Indore, India]","institution_ids":["https://openalex.org/I64295750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081671324","display_name":"Neha Kataria","orcid":null},"institutions":[{"id":"https://openalex.org/I64295750","display_name":"Indian Institute of Technology Indore","ror":"https://ror.org/01hhf7w52","country_code":"IN","type":"education","lineage":["https://openalex.org/I64295750"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Neha Kataria","raw_affiliation_strings":["Department of Computer Science and Engineering, Indian Institute of Technology, Indore","[Department of Computer Science and Engineering, Indian Institute of Technology, Indore, India]"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology, Indore","institution_ids":["https://openalex.org/I64295750"]},{"raw_affiliation_string":"[Department of Computer Science and Engineering, Indian Institute of Technology, Indore, India]","institution_ids":["https://openalex.org/I64295750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028480555","display_name":"Neminath Hubballi","orcid":"https://orcid.org/0000-0001-9669-9773"},"institutions":[{"id":"https://openalex.org/I64295750","display_name":"Indian Institute of Technology Indore","ror":"https://ror.org/01hhf7w52","country_code":"IN","type":"education","lineage":["https://openalex.org/I64295750"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Neminath Hubballi","raw_affiliation_strings":["Department of Computer Science and Engineering, Indian Institute of Technology, Indore","[Department of Computer Science and Engineering, Indian Institute of Technology, Indore, India]"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology, Indore","institution_ids":["https://openalex.org/I64295750"]},{"raw_affiliation_string":"[Department of Computer Science and Engineering, Indian Institute of Technology, Indore, India]","institution_ids":["https://openalex.org/I64295750"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077102590"],"corresponding_institution_ids":["https://openalex.org/I64295750"],"apc_list":null,"apc_paid":null,"fwci":1.7804,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.88533821,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"28","issue":null,"first_page":"1","last_page":"6"},"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":1.0,"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":1.0,"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":0.9995999932289124,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9976000189781189,"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/traffic-classification","display_name":"Traffic classification","score":0.8454934358596802},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8329220414161682},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.5777668952941895},{"id":"https://openalex.org/keywords/deep-packet-inspection","display_name":"Deep packet inspection","score":0.5467190146446228},{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.542717695236206},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5261982083320618},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.5149191617965698},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5146411657333374},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.49802184104919434},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.47273388504981995},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4668232798576355},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.4641047716140747},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.44558608531951904},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.42289048433303833},{"id":"https://openalex.org/keywords/quality-of-service","display_name":"Quality of service","score":0.4133925139904022},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40945714712142944},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.28645920753479004},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.2161378562450409}],"concepts":[{"id":"https://openalex.org/C169988225","wikidata":"https://www.wikidata.org/wiki/Q7832484","display_name":"Traffic classification","level":3,"score":0.8454934358596802},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8329220414161682},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.5777668952941895},{"id":"https://openalex.org/C204679922","wikidata":"https://www.wikidata.org/wiki/Q734252","display_name":"Deep packet inspection","level":3,"score":0.5467190146446228},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.542717695236206},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5261982083320618},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.5149191617965698},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5146411657333374},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49802184104919434},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.47273388504981995},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4668232798576355},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.4641047716140747},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.44558608531951904},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.42289048433303833},{"id":"https://openalex.org/C5119721","wikidata":"https://www.wikidata.org/wiki/Q220501","display_name":"Quality of service","level":2,"score":0.4133925139904022},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40945714712142944},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.28645920753479004},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2161378562450409},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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":2,"locations":[{"id":"doi:10.1109/ncc.2015.7084879","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ncc.2015.7084879","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Twenty First National Conference on Communications (NCC)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.707.4267","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.707.4267","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://iiti.ac.in/people/%7Eneminath/Papers/NCC.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1510529350","https://openalex.org/W1521553548","https://openalex.org/W1553465615","https://openalex.org/W1860651521","https://openalex.org/W2019774807","https://openalex.org/W2051000513","https://openalex.org/W2055261595","https://openalex.org/W2073089243","https://openalex.org/W2096674597","https://openalex.org/W2122226347","https://openalex.org/W2127561666","https://openalex.org/W2144098589","https://openalex.org/W2149274049","https://openalex.org/W2149600645","https://openalex.org/W2150779517","https://openalex.org/W2155926039","https://openalex.org/W2157349061","https://openalex.org/W2158215699","https://openalex.org/W2161840551","https://openalex.org/W6630566201","https://openalex.org/W6638932293","https://openalex.org/W6655507990","https://openalex.org/W7073596755"],"related_works":["https://openalex.org/W2041550843","https://openalex.org/W2537489883","https://openalex.org/W2017644937","https://openalex.org/W4387977367","https://openalex.org/W1976515580","https://openalex.org/W2141272333","https://openalex.org/W3011161512","https://openalex.org/W2928278548","https://openalex.org/W2978828483","https://openalex.org/W4301866626"],"abstract_inverted_index":{"Traffic":[0],"classification":[1,129,161],"is":[2,28,93],"an":[3],"important":[4],"task":[5],"for":[6,15],"providing":[7],"differentiated":[8],"service":[9],"quality":[10],"to":[11,32,38,55,101,158],"applications":[12,23],"and":[13,24,75,86,124,136,149],"also":[14],"security":[16],"monitoring.":[17],"With":[18],"the":[19,34,39,57,160],"advent":[20],"of":[21,113,116,120,142,147],"peer-to-peer":[22,96],"tunneling":[25],"techniques":[26,54],"it":[27],"becoming":[29],"increasingly":[30],"difficult":[31],"identify":[33,56],"traffic":[35,118],"without":[36],"going":[37],"application":[40,58,70,97],"semantics.":[41],"Several":[42],"approaches":[43],"have":[44],"been":[45],"proposed":[46],"(with":[47],"varied":[48],"success)":[49],"which":[50],"use":[51],"machine":[52],"learning":[53],"traffic.":[59],"In":[60],"this":[61],"paper":[62],"we":[63],"propose":[64],"a":[65,83,94,110],"novel":[66],"technique":[67],"based":[68,72],"on":[69,127],"behavior":[71],"feature":[73],"extraction":[74],"classification.":[76],"We":[77,106,138],"experiment":[78],"with":[79,109,144],"Google":[80,91],"Hangout":[81,92],"as":[82],"case":[84,157],"study":[85],"report":[87,125],"its":[88],"detection":[89],"results.":[90],"semi":[95],"allowing":[98],"two":[99],"parties":[100],"do":[102],"video":[103],"chat":[104],"online.":[105],"performed":[107,150],"experiments":[108,143],"dataset":[111],"consisting":[112,119],"several":[114],"hours":[115],"network":[117],"2.5":[121],"million":[122],"packets":[123],"results":[126],"3":[128,140],"algorithms":[130],"namely":[131],"Naive":[132],"Base,":[133],"decision":[134],"tree":[135],"AdaBoost.":[137],"conducted":[139],"sets":[141],"different":[145],"combinations":[146],"data":[148],"10":[151],"fold":[152],"cross":[153],"validation":[154],"in":[155],"each":[156],"assess":[159],"performance.":[162]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}