{"id":"https://openalex.org/W4390496050","doi":"https://doi.org/10.1109/lnet.2023.3349301","title":"Malicious Traffic Detection With Noise Labels Based on Cross-Modal Consistency","display_name":"Malicious Traffic Detection With Noise Labels Based on Cross-Modal Consistency","publication_year":2024,"publication_date":"2024-01-02","ids":{"openalex":"https://openalex.org/W4390496050","doi":"https://doi.org/10.1109/lnet.2023.3349301"},"language":"en","primary_location":{"id":"doi:10.1109/lnet.2023.3349301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lnet.2023.3349301","pdf_url":null,"source":{"id":"https://openalex.org/S4210234060","display_name":"IEEE Networking Letters","issn_l":"2576-3156","issn":["2576-3156"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Networking Letters","raw_type":"journal-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/A5028566827","display_name":"Qingjun Yuan","orcid":"https://orcid.org/0000-0002-6598-8190"},"institutions":[{"id":"https://openalex.org/I4210132990","display_name":"State Key Laboratory of Cryptology","ror":"https://ror.org/02pn5rj08","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210132990"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qingjun Yuan","raw_affiliation_strings":["Henan Key Laboratory of Network Cryptography Technology, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Henan Key Laboratory of Network Cryptography Technology, Zhengzhou, China","institution_ids":["https://openalex.org/I4210132990"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029715489","display_name":"Weina Niu","orcid":"https://orcid.org/0000-0002-3235-3463"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weina Niu","raw_affiliation_strings":["School of Computer Science and Engineering, Institute for Cyber Security, University of Electronic Science and Technology of China, Chengdu, China","Institute for Cyber Security, School of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China","Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Institute for Cyber Security, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"Institute for Cyber Security, School of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079565555","display_name":"Yongjuan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210132990","display_name":"State Key Laboratory of Cryptology","ror":"https://ror.org/02pn5rj08","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210132990"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongjuan Wang","raw_affiliation_strings":["Henan Key Laboratory of Network Cryptography Technology, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Henan Key Laboratory of Network Cryptography Technology, Zhengzhou, China","institution_ids":["https://openalex.org/I4210132990"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052269317","display_name":"Gaopeng Gou","orcid":"https://orcid.org/0000-0002-3533-4874"},"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":"Gaopeng Gou","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/A5100715992","display_name":"Bin Lu","orcid":"https://orcid.org/0000-0002-2775-2056"},"institutions":[{"id":"https://openalex.org/I4210132990","display_name":"State Key Laboratory of Cryptology","ror":"https://ror.org/02pn5rj08","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210132990"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Lu","raw_affiliation_strings":["Henan Key Laboratory of Network Cryptography Technology, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Henan Key Laboratory of Network Cryptography Technology, Zhengzhou, China","institution_ids":["https://openalex.org/I4210132990"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5028566827"],"corresponding_institution_ids":["https://openalex.org/I4210132990"],"apc_list":null,"apc_paid":null,"fwci":1.0425,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.78426942,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"6","issue":"2","first_page":"148","last_page":"151"},"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":0.9973000288009644,"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":0.9973000288009644,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9968000054359436,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.996399998664856,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.7789870500564575},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7479315996170044},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6280376315116882},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.6219995617866516},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.6029863357543945},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5880563259124756},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4582601487636566},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4530101716518402},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.4444931745529175},{"id":"https://openalex.org/keywords/traffic-sign-recognition","display_name":"Traffic sign recognition","score":0.42833638191223145},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38974475860595703},{"id":"https://openalex.org/keywords/traffic-sign","display_name":"Traffic sign","score":0.1130656898021698},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08919119834899902},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07977074384689331},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.074981689453125}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7789870500564575},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7479315996170044},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6280376315116882},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.6219995617866516},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.6029863357543945},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5880563259124756},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4582601487636566},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4530101716518402},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4444931745529175},{"id":"https://openalex.org/C6528762","wikidata":"https://www.wikidata.org/wiki/Q1574298","display_name":"Traffic sign recognition","level":4,"score":0.42833638191223145},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38974475860595703},{"id":"https://openalex.org/C2983860417","wikidata":"https://www.wikidata.org/wiki/Q170285","display_name":"Traffic sign","level":3,"score":0.1130656898021698},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08919119834899902},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07977074384689331},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.074981689453125},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lnet.2023.3349301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lnet.2023.3349301","pdf_url":null,"source":{"id":"https://openalex.org/S4210234060","display_name":"IEEE Networking Letters","issn_l":"2576-3156","issn":["2576-3156"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Networking Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5}],"awards":[{"id":"https://openalex.org/G6027530306","display_name":null,"funder_award_id":"62372086","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6859718134","display_name":null,"funder_award_id":"2023YFB2705000","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2743556905","https://openalex.org/W2743678626","https://openalex.org/W2789828921","https://openalex.org/W2919493784","https://openalex.org/W2924689635","https://openalex.org/W2990009274","https://openalex.org/W3190486510","https://openalex.org/W3205655893","https://openalex.org/W4285198896","https://openalex.org/W4313591247","https://openalex.org/W4377101054","https://openalex.org/W6738471490","https://openalex.org/W6751647823","https://openalex.org/W6758632346"],"related_works":["https://openalex.org/W2185469136","https://openalex.org/W4283820116","https://openalex.org/W4382897155","https://openalex.org/W3048636285","https://openalex.org/W4306353150","https://openalex.org/W8219677","https://openalex.org/W2977842967","https://openalex.org/W2168054807","https://openalex.org/W4301143707","https://openalex.org/W2952745240"],"abstract_inverted_index":{"To":[0],"train":[1],"robust":[2],"malicious":[3],"traffic":[4],"identification":[5],"models":[6],"under":[7],"noisy":[8,53,65],"labeled":[9],"datasets,":[10],"a":[11],"number":[12],"of":[13,46,71,74,93],"learning":[14],"with":[15,40],"noise":[16],"labels":[17],"approaches":[18],"have":[19,27],"been":[20,28],"introduced,":[21],"among":[22],"which":[23],"parallel":[24,75],"training":[25,34],"methods":[26,35],"proved":[29],"to":[30,37,42,62],"be":[31],"effective.":[32],"Parallel":[33],"tend":[36],"select":[38],"samples":[39],"disagreement":[41],"mitigate":[43],"the":[44,69,72,78,91],"risk":[45,92],"self-control":[47,94],"degradation.":[48],"However,":[49],"it":[50],"also":[51],"introduces":[52],"knowledge":[54,66],"into":[55],"training.":[56],"In":[57],"this":[58],"letter,":[59],"we":[60],"try":[61],"avoid":[63],"introducing":[64],"by":[67],"enhancing":[68],"consistency":[70],"representations":[73],"networks.":[76],"Meanwhile,":[77],"two":[79],"networks":[80],"are":[81],"heterogeneous":[82],"and":[83],"introduce":[84],"information":[85],"from":[86,96],"different":[87],"modalities,":[88],"thus":[89],"mitigating":[90],"degradation":[95],"multiple":[97],"perspectives.":[98]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
