{"id":"https://openalex.org/W2978660033","doi":"https://doi.org/10.1109/ijcnn.2019.8851964","title":"isAnon: Flow-Based Anonymity Network Traffic Identification Using Extreme Gradient Boosting","display_name":"isAnon: Flow-Based Anonymity Network Traffic Identification Using Extreme Gradient Boosting","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2978660033","doi":"https://doi.org/10.1109/ijcnn.2019.8851964","mag":"2978660033"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8851964","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851964","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","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/A5101649775","display_name":"Zhenzhen Cai","orcid":"https://orcid.org/0009-0006-1177-058X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhenzhen Cai","raw_affiliation_strings":["School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102920589","display_name":"Bo Jiang","orcid":"https://orcid.org/0000-0002-7185-990X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Jiang","raw_affiliation_strings":["Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210156404","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012305916","display_name":"Zhigang L\u00fc","orcid":"https://orcid.org/0000-0001-5102-6217"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhigang Lu","raw_affiliation_strings":["School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Junrong Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junrong Liu","raw_affiliation_strings":["Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210156404","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001790767","display_name":"Pingchuan Ma","orcid":"https://orcid.org/0000-0003-3752-0803"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pingchuan Ma","raw_affiliation_strings":["School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101649775"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":1.3023,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.85873787,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.9918000102043152,"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/T12034","display_name":"Digital and Cyber Forensics","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.7656046748161316},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6816069483757019},{"id":"https://openalex.org/keywords/anonymity","display_name":"Anonymity","score":0.6167041063308716},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5692824125289917},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5456044673919678},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.482667475938797},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4698580503463745},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.43389806151390076},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40312299132347107},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.166224867105484},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1515142321586609}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7656046748161316},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6816069483757019},{"id":"https://openalex.org/C178005623","wikidata":"https://www.wikidata.org/wiki/Q308859","display_name":"Anonymity","level":2,"score":0.6167041063308716},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5692824125289917},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5456044673919678},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.482667475938797},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4698580503463745},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.43389806151390076},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40312299132347107},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.166224867105484},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1515142321586609},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8851964","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851964","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1536141561","https://openalex.org/W1570448133","https://openalex.org/W1580004440","https://openalex.org/W1655958391","https://openalex.org/W1815005891","https://openalex.org/W1964234701","https://openalex.org/W1979279626","https://openalex.org/W1985776777","https://openalex.org/W1992157848","https://openalex.org/W1992562179","https://openalex.org/W2001984188","https://openalex.org/W2006676204","https://openalex.org/W2070493638","https://openalex.org/W2094245741","https://openalex.org/W2102004764","https://openalex.org/W2103647628","https://openalex.org/W2104114371","https://openalex.org/W2123243822","https://openalex.org/W2143305710","https://openalex.org/W2148679464","https://openalex.org/W2149772057","https://openalex.org/W2154776925","https://openalex.org/W2158215699","https://openalex.org/W2232014569","https://openalex.org/W2295598076","https://openalex.org/W2343828539","https://openalex.org/W2613715541","https://openalex.org/W2779898574","https://openalex.org/W2801435620","https://openalex.org/W2834885115","https://openalex.org/W3100723659","https://openalex.org/W3102476541","https://openalex.org/W3160110679","https://openalex.org/W6682981795","https://openalex.org/W6690002673","https://openalex.org/W6795103906"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W2922073769","https://openalex.org/W2393964553","https://openalex.org/W2121565117","https://openalex.org/W1487831638","https://openalex.org/W4295122168","https://openalex.org/W3155717344","https://openalex.org/W1770458422","https://openalex.org/W2145188897"],"abstract_inverted_index":{"The":[0,12],"abuse":[1],"of":[2,15,29,38,54,60,161],"anonymous":[3],"communication":[4],"technology":[5],"brings":[6],"serious":[7],"challenges":[8],"to":[9,34,95,124,137],"network":[10,17,70,154],"supervision.":[11],"valid":[13],"identification":[14,72,169],"anonymity":[16,41,69,153],"traffic":[18,71,155],"is":[19],"a":[20,79,109],"prerequisite":[21],"and":[22,46,90,100,118,141],"fundamentally":[23],"important":[24],"for":[25,144],"preventing":[26],"the":[27,35,58,131,159],"violence":[28],"such":[30],"techniques.":[31],"However,":[32],"due":[33],"distinct":[36],"characteristics":[37],"flow":[39],"from":[40],"networks":[42,143],"including":[43],"Tor,":[44,139],"I2P,":[45,140],"JonDonym,":[47],"existing":[48],"studies":[49],"don't":[50],"take":[51],"full":[52],"advantage":[53],"these":[55],"features,":[56],"damaging":[57],"accuracy":[59],"identification.":[61],"In":[62],"this":[63],"paper,":[64],"we":[65,129],"propose":[66],"an":[67,114,119],"effective":[68],"model,":[73],"called":[74],"isAnon.":[75],"Firstly,":[76],"isAnon":[77,163],"designs":[78],"novel":[80],"hybrid":[81],"feature":[82],"selection":[83],"algorithm":[84,94,136],"by":[85],"combining":[86],"Modified":[87],"Mutual":[88],"Information":[89],"Random":[91],"Forest":[92],"(MMIRF)":[93],"filter":[96],"out":[97],"some":[98],"irrelevant":[99],"redundant":[101],"features":[102],"quickly.":[103],"Secondly,":[104],"our":[105,162],"proposed":[106],"model":[107,126,164],"applies":[108],"nested":[110],"cross-validation":[111,117,123],"scheme":[112],"with":[113,166],"inner":[115],"5-fold":[116],"outer":[120],"Monte":[121],"Carlo":[122],"prevent":[125],"overfitting.":[127],"Finally,":[128],"use":[130],"Extreme":[132],"Gradient":[133],"Boosting":[134],"(XGBoost)":[135],"identify":[138],"JonDonym":[142],"four":[145],"scenarios.":[146],"Comprehensive":[147],"experimental":[148],"results":[149],"on":[150],"several":[151],"real-world":[152],"datasets":[156],"clearly":[157],"show":[158],"effectiveness":[160],"compared":[165],"state-of-the-art":[167],"baseline":[168],"methods.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3}],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2025-10-10T00:00:00"}
