{"id":"https://openalex.org/W2290009603","doi":"https://doi.org/10.1109/glocom.2014.7417076","title":"Separation of Background and Foreground Traffic Based on Periodicity Analysis","display_name":"Separation of Background and Foreground Traffic Based on Periodicity Analysis","publication_year":2014,"publication_date":"2014-12-01","ids":{"openalex":"https://openalex.org/W2290009603","doi":"https://doi.org/10.1109/glocom.2014.7417076","mag":"2290009603"},"language":"en","primary_location":{"id":"doi:10.1109/glocom.2014.7417076","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2014.7417076","pdf_url":null,"source":{"id":"https://openalex.org/S4363607712","display_name":"2015 IEEE Global Communications Conference (GLOBECOM)","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":"2015 IEEE Global Communications Conference (GLOBECOM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5029807151","display_name":"Quang Tran Minh","orcid":"https://orcid.org/0000-0003-1408-2919"},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Quang Tran Minh","raw_affiliation_strings":["KDDI R&D Laboratories Inc., Fujimino-shi, Saitama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI R&D Laboratories Inc., Fujimino-shi, Saitama, Japan","institution_ids":["https://openalex.org/I4210164495"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034517950","display_name":"Hideyuki Koto","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hideyuki Koto","raw_affiliation_strings":["KDDI R&D Laboratories Inc., Fujimino-shi, Saitama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI R&D Laboratories Inc., Fujimino-shi, Saitama, Japan","institution_ids":["https://openalex.org/I4210164495"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065435508","display_name":"Takeshi Kitahara","orcid":"https://orcid.org/0000-0001-7063-5122"},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takeshi Kitahara","raw_affiliation_strings":["KDDI R&D Laboratories Inc., Fujimino-shi, Saitama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI R&D Laboratories Inc., Fujimino-shi, Saitama, Japan","institution_ids":["https://openalex.org/I4210164495"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100432082","display_name":"Lu Chen","orcid":"https://orcid.org/0000-0002-3840-7151"},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Lu Chen","raw_affiliation_strings":["KDDI R&D Laboratories Inc., Fujimino-shi, Saitama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI R&D Laboratories Inc., Fujimino-shi, Saitama, Japan","institution_ids":["https://openalex.org/I4210164495"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090165182","display_name":"Shin\u2019ichi Arakawa","orcid":"https://orcid.org/0000-0002-9376-977X"},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shin'ichi Arakawa","raw_affiliation_strings":["KDDI R&D Laboratories Inc., Fujimino-shi, Saitama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI R&D Laboratories Inc., Fujimino-shi, Saitama, Japan","institution_ids":["https://openalex.org/I4210164495"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111489163","display_name":"Shigehiro Ano","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shigehiro Ano","raw_affiliation_strings":["KDDI R&D Laboratories Inc., Fujimino-shi, Saitama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI R&D Laboratories Inc., Fujimino-shi, Saitama, Japan","institution_ids":["https://openalex.org/I4210164495"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019839911","display_name":"Masayuki Murata","orcid":"https://orcid.org/0000-0002-4168-2875"},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masayuki Murata","raw_affiliation_strings":["KDDI R&D Laboratories Inc., Fujimino-shi, Saitama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI R&D Laboratories Inc., Fujimino-shi, Saitama, Japan","institution_ids":["https://openalex.org/I4210164495"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210164495"],"apc_list":null,"apc_paid":null,"fwci":0.4135,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.62267973,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"2","issue":null,"first_page":"1","last_page":"7"},"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":0.9988999962806702,"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":0.9988999962806702,"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":0.9957000017166138,"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/T10138","display_name":"Network Traffic and Congestion Control","score":0.9947999715805054,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.73350590467453},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5631677508354187},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5040897130966187},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48448607325553894},{"id":"https://openalex.org/keywords/independence","display_name":"Independence (probability theory)","score":0.4680734872817993},{"id":"https://openalex.org/keywords/separation","display_name":"Separation (statistics)","score":0.459943026304245},{"id":"https://openalex.org/keywords/traffic-classification","display_name":"Traffic classification","score":0.4258941411972046},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40941035747528076},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3533094525337219},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2984464764595032},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.15265241265296936},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09504866600036621},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07698780298233032}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.73350590467453},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5631677508354187},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5040897130966187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48448607325553894},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.4680734872817993},{"id":"https://openalex.org/C2776061190","wikidata":"https://www.wikidata.org/wiki/Q7451805","display_name":"Separation (statistics)","level":2,"score":0.459943026304245},{"id":"https://openalex.org/C169988225","wikidata":"https://www.wikidata.org/wiki/Q7832484","display_name":"Traffic classification","level":3,"score":0.4258941411972046},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40941035747528076},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3533094525337219},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2984464764595032},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.15265241265296936},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09504866600036621},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07698780298233032},{"id":"https://openalex.org/C5119721","wikidata":"https://www.wikidata.org/wiki/Q220501","display_name":"Quality of service","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/glocom.2014.7417076","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2014.7417076","pdf_url":null,"source":{"id":"https://openalex.org/S4363607712","display_name":"2015 IEEE Global Communications Conference (GLOBECOM)","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":"2015 IEEE Global Communications Conference (GLOBECOM)","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":14,"referenced_works":["https://openalex.org/W2038571076","https://openalex.org/W2043605178","https://openalex.org/W2096118443","https://openalex.org/W2099078385","https://openalex.org/W2115826098","https://openalex.org/W2141829082","https://openalex.org/W2143715657","https://openalex.org/W2148500771","https://openalex.org/W2582983765","https://openalex.org/W2752061190","https://openalex.org/W2752853835","https://openalex.org/W6660044709","https://openalex.org/W6661061886","https://openalex.org/W6744529318"],"related_works":["https://openalex.org/W1975632186","https://openalex.org/W3027745756","https://openalex.org/W2531880140","https://openalex.org/W3205213561","https://openalex.org/W2036609560","https://openalex.org/W346861917","https://openalex.org/W3024018414","https://openalex.org/W385273440","https://openalex.org/W4380081032","https://openalex.org/W2068561554"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,84],"novel":[4],"approach":[5,42,88],"to":[6,31,45,93,124,137],"separating":[7],"background":[8],"(BG)":[9],"and":[10,52,118,135],"foreground":[11],"(FG)":[12],"traffic":[13,20,54,72,97,108],"based":[14],"on":[15,75],"periodicity":[16,61],"analysis.":[17],"As":[18,83],"BG":[19,34],"is":[21,29,43],"commonly":[22],"periodically":[23],"generated":[24],"by":[25,110],"applications,":[26],"this":[27],"trait":[28],"leveraged":[30],"effectively":[32],"detect":[33],"traffic.":[35],"Concretely,":[36],"the":[37,59,86,94,102,116,121,125],"Period":[38],"Candidate":[39],"Array":[40],"(PCA)":[41],"proposed":[44,87],"extract":[46],"only":[47],"necessary":[48],"information":[49],"from":[50],"long":[51],"sparse":[53],"flows,":[55],"hence":[56],"quickly":[57],"detects":[58],"flows'":[60],"with":[62,70,106],"low":[63],"computational":[64,131],"cost.":[65],"The":[66],"PCA":[67,103,122],"works":[68,105],"directly":[69],"\"on-site''":[71],"without":[73],"depending":[74],"historical":[76,138],"data":[77],"as":[78],"in":[79,128],"machine":[80],"learning":[81],"methods.":[82],"result,":[85],"can":[89],"be":[90],"immediately":[91],"applied":[92],"real":[95],"world":[96],"management":[98],"systems.":[99],"In":[100],"addition,":[101],"properly":[104],"latency-included":[107],"affected":[109],"network":[111],"delays.":[112],"Experimental":[113],"results":[114],"reveal":[115],"effectiveness":[117],"efficiency":[119],"of":[120,130],"compared":[123],"conventional":[126],"methods":[127],"terms":[129],"cost,":[132],"memory":[133],"usage,":[134],"independence":[136],"data.":[139]},"counts_by_year":[{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
