{"id":"https://openalex.org/W2904326537","doi":"https://doi.org/10.1109/ickii.2018.8569113","title":"Tor Traffic Classification from Raw Packet Header using Convolutional Neural Network","display_name":"Tor Traffic Classification from Raw Packet Header using Convolutional Neural Network","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2904326537","doi":"https://doi.org/10.1109/ickii.2018.8569113","mag":"2904326537"},"language":"en","primary_location":{"id":"doi:10.1109/ickii.2018.8569113","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ickii.2018.8569113","pdf_url":null,"source":{"id":"https://openalex.org/S4306498242","display_name":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","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/A5100343642","display_name":"Minsu Kim","orcid":"https://orcid.org/0000-0003-4472-0926"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Minsu Kim","raw_affiliation_strings":["WINCORE Lab, Ryerson University, Toronto, Ontario, Canada"],"affiliations":[{"raw_affiliation_string":"WINCORE Lab, Ryerson University, Toronto, Ontario, Canada","institution_ids":["https://openalex.org/I530967"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074463174","display_name":"Alagan Anpalagan","orcid":"https://orcid.org/0000-0002-6646-6052"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Alagan Anpalagan","raw_affiliation_strings":["WINCORE Lab, Ryerson University, Toronto, Ontario, Canada"],"affiliations":[{"raw_affiliation_string":"WINCORE Lab, Ryerson University, Toronto, Ontario, Canada","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100343642"],"corresponding_institution_ids":["https://openalex.org/I530967"],"apc_list":null,"apc_paid":null,"fwci":1.2552,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.86560409,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"187","last_page":"190"},"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":0.9990000128746033,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/header","display_name":"Header","score":0.9132577180862427},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.830273449420929},{"id":"https://openalex.org/keywords/traffic-classification","display_name":"Traffic classification","score":0.7047226428985596},{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.6917477250099182},{"id":"https://openalex.org/keywords/deep-packet-inspection","display_name":"Deep packet inspection","score":0.6598584651947021},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6317201256752014},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.499157190322876},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.49449774622917175},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4763234555721283},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45137089490890503},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4075859785079956},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3393568694591522}],"concepts":[{"id":"https://openalex.org/C48105269","wikidata":"https://www.wikidata.org/wiki/Q1141160","display_name":"Header","level":2,"score":0.9132577180862427},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.830273449420929},{"id":"https://openalex.org/C169988225","wikidata":"https://www.wikidata.org/wiki/Q7832484","display_name":"Traffic classification","level":3,"score":0.7047226428985596},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.6917477250099182},{"id":"https://openalex.org/C204679922","wikidata":"https://www.wikidata.org/wiki/Q734252","display_name":"Deep packet inspection","level":3,"score":0.6598584651947021},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6317201256752014},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.499157190322876},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.49449774622917175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4763234555721283},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45137089490890503},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4075859785079956},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3393568694591522}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ickii.2018.8569113","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ickii.2018.8569113","pdf_url":null,"source":{"id":"https://openalex.org/S4306498242","display_name":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.44999998807907104,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1655958391","https://openalex.org/W1983405755","https://openalex.org/W2095705004","https://openalex.org/W2149600645","https://openalex.org/W2402144811","https://openalex.org/W2591712613","https://openalex.org/W2609731728","https://openalex.org/W2743678626","https://openalex.org/W2760710921","https://openalex.org/W2775103799","https://openalex.org/W2777683119","https://openalex.org/W2782597251","https://openalex.org/W2790832484","https://openalex.org/W2919115771","https://openalex.org/W2953384591","https://openalex.org/W2963704216","https://openalex.org/W2964121744","https://openalex.org/W4299319711","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6674330103","https://openalex.org/W6713134421","https://openalex.org/W6748047980"],"related_works":["https://openalex.org/W3175867593","https://openalex.org/W2041550843","https://openalex.org/W4212842074","https://openalex.org/W2904326537","https://openalex.org/W2127561666","https://openalex.org/W2949949254","https://openalex.org/W3163756987","https://openalex.org/W3174245262","https://openalex.org/W4226172882","https://openalex.org/W2085398523"],"abstract_inverted_index":{"As":[0],"the":[1,46,96,104],"amount":[2],"of":[3,45],"network":[4,23,68,91],"traffic":[5,9,59,92,107],"is":[6,32,43],"growing":[7],"exponentially,":[8],"analysis":[10],"and":[11,22,65],"classification":[12],"are":[13],"playing":[14],"a":[15,79],"significant":[16],"role":[17],"for":[18,103],"efficient":[19],"resource":[20],"allocation":[21],"management.":[24],"However,":[25],"with":[26,71],"emerging":[27],"security":[28],"technologies,":[29],"this":[30,84],"work":[31],"becoming":[33],"more":[34],"difficult":[35],"by":[36],"encrypted":[37],"communication":[38],"such":[39],"as":[40],"Tor,":[41],"which":[42],"one":[44],"most":[47],"popular":[48],"encryption":[49],"techniques.":[50],"This":[51],"paper":[52],"proposes":[53],"an":[54],"approach":[55,77,99],"to":[56],"classify":[57],"Tor":[58,90],"using":[60],"hexadecimal":[61],"raw":[62],"packet":[63],"header":[64],"convolutional":[66],"neural":[67],"model.":[69],"Comparing":[70],"competitive":[72],"machine":[73],"learning":[74],"algorithms,":[75],"our":[76,98],"shows":[78,100],"remarkable":[80],"accuracy.":[81],"To":[82],"validate":[83],"method":[85],"publicly,":[86],"we":[87],"use":[88],"UNB-CIC":[89],"dataset.":[93],"Based":[94],"on":[95],"experiments,":[97],"99.3%":[101],"accuracy":[102],"fractionized":[105],"Tor/non-Tor":[106],"classification.":[108]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}
