{"id":"https://openalex.org/W2916813124","doi":"https://doi.org/10.1109/glocom.2018.8647508","title":"APPCLASSIFIER: Automated App Inference on Encrypted Traffic via Meta Data Analysis","display_name":"APPCLASSIFIER: Automated App Inference on Encrypted Traffic via Meta Data Analysis","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2916813124","doi":"https://doi.org/10.1109/glocom.2018.8647508","mag":"2916813124"},"language":"en","primary_location":{"id":"doi:10.1109/glocom.2018.8647508","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2018.8647508","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 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/A5030028368","display_name":"Chong Xiang","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chong Xiang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101754102","display_name":"Qingrong Chen","orcid":"https://orcid.org/0000-0001-6472-7186"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingrong Chen","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009850797","display_name":"Minhui Xue","orcid":"https://orcid.org/0000-0002-9172-4252"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Minhui Xue","raw_affiliation_strings":["Macquarie University, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Macquarie University, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039106671","display_name":"Haojin Zhu","orcid":"https://orcid.org/0000-0001-5079-4556"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haojin Zhu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"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":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":0.9994000196456909,"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/T10138","display_name":"Network Traffic and Congestion Control","score":0.9954000115394592,"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":0.7767269611358643},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7568361759185791},{"id":"https://openalex.org/keywords/traffic-analysis","display_name":"Traffic analysis","score":0.645978569984436},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.538644552230835},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5343707203865051},{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.4819895625114441},{"id":"https://openalex.org/keywords/traffic-classification","display_name":"Traffic classification","score":0.45358139276504517},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.44847604632377625},{"id":"https://openalex.org/keywords/traffic-noise","display_name":"Traffic noise","score":0.4448028802871704},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.43068253993988037},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42928218841552734},{"id":"https://openalex.org/keywords/android","display_name":"Android (operating system)","score":0.42050081491470337},{"id":"https://openalex.org/keywords/floating-car-data","display_name":"Floating car data","score":0.4190126061439514},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.4164501428604126},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33482369780540466},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.31218281388282776},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.23431119322776794},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.12841352820396423},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10302573442459106},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.10235467553138733}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7767269611358643},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7568361759185791},{"id":"https://openalex.org/C2781317605","wikidata":"https://www.wikidata.org/wiki/Q7832483","display_name":"Traffic analysis","level":2,"score":0.645978569984436},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.538644552230835},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5343707203865051},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.4819895625114441},{"id":"https://openalex.org/C169988225","wikidata":"https://www.wikidata.org/wiki/Q7832484","display_name":"Traffic classification","level":3,"score":0.45358139276504517},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.44847604632377625},{"id":"https://openalex.org/C2781353297","wikidata":"https://www.wikidata.org/wiki/Q1748361","display_name":"Traffic noise","level":3,"score":0.4448028802871704},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.43068253993988037},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42928218841552734},{"id":"https://openalex.org/C557433098","wikidata":"https://www.wikidata.org/wiki/Q94","display_name":"Android (operating system)","level":2,"score":0.42050081491470337},{"id":"https://openalex.org/C64093975","wikidata":"https://www.wikidata.org/wiki/Q356677","display_name":"Floating car data","level":3,"score":0.4190126061439514},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.4164501428604126},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33482369780540466},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.31218281388282776},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.23431119322776794},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.12841352820396423},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10302573442459106},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.10235467553138733},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/glocom.2018.8647508","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2018.8647508","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Global Communications Conference (GLOBECOM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2000756828","https://openalex.org/W2125838338","https://openalex.org/W2190207511","https://openalex.org/W2467159119","https://openalex.org/W2557283755","https://openalex.org/W2755121186","https://openalex.org/W2783301790","https://openalex.org/W2911964244","https://openalex.org/W2963403784","https://openalex.org/W2963953172","https://openalex.org/W3103367901","https://openalex.org/W4297668352","https://openalex.org/W6697016611"],"related_works":["https://openalex.org/W4301398392","https://openalex.org/W2997818875","https://openalex.org/W4379534844","https://openalex.org/W266939152","https://openalex.org/W2587627203","https://openalex.org/W2410941711","https://openalex.org/W3178296362","https://openalex.org/W2924962435","https://openalex.org/W2141958076","https://openalex.org/W4233316175"],"abstract_inverted_index":{"As":[0,160],"smart":[1,92],"phones":[2],"gradually":[3],"become":[4],"the":[5,30,39,51,62,76,95,103,124],"dominant":[6],"network":[7,19],"traffic":[8,11,36,68,100,132,141,153,158,171,183],"generators,":[9],"app":[10,33,58,114,119],"analysis":[12,172],"methods":[13,149],"have":[14,27],"gained":[15],"great":[16],"interests":[17],"for":[18,117,139,169,181],"management":[20],"and":[21,131,173],"targeted":[22],"advertisement.":[23],"Specifically,":[24],"previous":[25],"works":[26,48],"shown":[28],"that":[29,85,107],"scalability":[31],"of":[32,167],"inference":[34,53,137,165],"via":[35],"meta-data":[37],"has":[38],"edge":[40],"over":[41],"traditional":[42],"payload":[43],"based":[44,148],"analysis.":[45,142],"However,":[46],"such":[47],"mainly":[49],"considered":[50],"ideal":[52],"scenario":[54],"where":[55],"only":[56],"one":[57],"is":[59],"running":[60],"on":[61,90],"client's":[63],"device,":[64],"without":[65],"any":[66],"background":[67,97],"noise":[69],"interfered.":[70],"In":[71],"this":[72],"paper,":[73],"we":[74,109],"extend":[75],"research":[77],"to":[78,135,150,155,179],"a":[79,91,161],"more":[80],"practical":[81],"scenario,":[82],"by":[83,102],"assuming":[84],"multiple":[86],"apps":[87],"simultaneously":[88],"run":[89],"phone":[93],"in":[94,127],"noisy":[96],"with":[98],"complex":[99],"generated":[101],"operating":[104],"system.":[105],"To":[106],"end,":[108],"propose":[110,145],"APPCLASSIFIER,":[111],"an":[112],"Android":[113],"fingerprinting":[115],"scheme":[116],"real-time":[118,157,182],"inference.":[120,159,184],"We":[121,143],"first":[122],"leverage":[123],"observed":[125],"differences":[126],"packet":[128],"size":[129],"distributions":[130],"sequential":[133],"behaviors":[134],"boost":[136],"accuracy":[138,166],"noise-free":[140,170],"then":[144],"novel":[146],"heuristic":[147],"re-correct":[151],"mislabeled":[152],"flows":[154],"realize":[156],"result,":[162],"APPCLASSIFIER":[163],"achieves":[164],"82.3%":[168],"reduces":[174],"error":[175],"rate":[176],"from":[177],"66.7%":[178],"36.4%":[180]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}