{"id":"https://openalex.org/W4299618167","doi":"https://doi.org/10.1109/icc45855.2022.9838567","title":"A Lightweight Semi-Supervised Learning Method Based on Consistency Regularization for Intrusion Detection","display_name":"A Lightweight Semi-Supervised Learning Method Based on Consistency Regularization for Intrusion Detection","publication_year":2022,"publication_date":"2022-05-16","ids":{"openalex":"https://openalex.org/W4299618167","doi":"https://doi.org/10.1109/icc45855.2022.9838567"},"language":"en","primary_location":{"id":"doi:10.1109/icc45855.2022.9838567","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9838567","pdf_url":null,"source":{"id":"https://openalex.org/S4363607711","display_name":"ICC 2022 - IEEE International Conference on Communications","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":"ICC 2022 - IEEE International Conference on Communications","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/A5070155692","display_name":"Ruijie Zhao","orcid":"https://orcid.org/0000-0001-6168-8687"},"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":true,"raw_author_name":"Ruijie Zhao","raw_affiliation_strings":["Shanghai Jiao Tong University,School of Electronic Information and Electrical Engineering,Shanghai,China","School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,School of Electronic Information and Electrical Engineering,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102023748","display_name":"Tiantian Tang","orcid":"https://orcid.org/0000-0002-8596-1227"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiantian Tang","raw_affiliation_strings":["NJUPT,College of Telecommunications and Information Engineering,Nanjing,China","College of Telecommunications and Information Engineering, NJUPT, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"NJUPT,College of Telecommunications and Information Engineering,Nanjing,China","institution_ids":["https://openalex.org/I41198531"]},{"raw_affiliation_string":"College of Telecommunications and Information Engineering, NJUPT, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027367677","display_name":"Guan Gui","orcid":"https://orcid.org/0000-0003-3888-2881"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guan Gui","raw_affiliation_strings":["NJUPT,College of Telecommunications and Information Engineering,Nanjing,China","College of Telecommunications and Information Engineering, NJUPT, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"NJUPT,College of Telecommunications and Information Engineering,Nanjing,China","institution_ids":["https://openalex.org/I41198531"]},{"raw_affiliation_string":"College of Telecommunications and Information Engineering, NJUPT, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062829885","display_name":"Zhi Xue","orcid":"https://orcid.org/0000-0003-2875-304X"},"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":"Zhi Xue","raw_affiliation_strings":["Shanghai Jiao Tong University,School of Electronic Information and Electrical Engineering,Shanghai,China","School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,School of Electronic Information and Electrical Engineering,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5070155692"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.8639,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.67825362,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3124","last_page":"3129"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":1.0,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9995999932289124,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9975000023841858,"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/computer-science","display_name":"Computer science","score":0.8089902400970459},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.8082332611083984},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6957175135612488},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6430777907371521},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5625454783439636},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5272825360298157},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5048821568489075},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4949900507926941},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4672923684120178},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42298778891563416}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8089902400970459},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.8082332611083984},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6957175135612488},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6430777907371521},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5625454783439636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5272825360298157},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5048821568489075},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4949900507926941},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4672923684120178},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42298778891563416},{"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc45855.2022.9838567","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9838567","pdf_url":null,"source":{"id":"https://openalex.org/S4363607711","display_name":"ICC 2022 - IEEE International Conference on Communications","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":"ICC 2022 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5099999904632568}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322999","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2106426069","https://openalex.org/W2625602624","https://openalex.org/W2808449955","https://openalex.org/W2900713154","https://openalex.org/W2926701059","https://openalex.org/W2951970475","https://openalex.org/W2953070460","https://openalex.org/W2963391384","https://openalex.org/W2980185226","https://openalex.org/W2996900869","https://openalex.org/W3006704479","https://openalex.org/W3013798241","https://openalex.org/W3022558251","https://openalex.org/W3126140213","https://openalex.org/W3170485195","https://openalex.org/W3206674745","https://openalex.org/W6733814495","https://openalex.org/W6764051988"],"related_works":["https://openalex.org/W96612179","https://openalex.org/W2566006169","https://openalex.org/W2770234245","https://openalex.org/W2987774938","https://openalex.org/W2378211422","https://openalex.org/W632915154","https://openalex.org/W4229499248","https://openalex.org/W2745001401","https://openalex.org/W4378874356","https://openalex.org/W2055733372"],"abstract_inverted_index":{"With":[0],"the":[1,4,27,32,64,77,93,124,153,163],"development":[2,79],"of":[3,7,29,37,66,70,80,87,95,156],"Industrial":[5],"Internet":[6],"Things":[8],"(IIoT),":[9],"more":[10,56],"frequent":[11],"attacks":[12,172],"occur":[13],"to":[14],"intrude":[15],"IIoT":[16,88],"devices.":[17],"A":[18],"reasonably":[19],"designed":[20],"intrusion":[21,38,50,81,118],"detection":[22,39,51,125,154],"method":[23,112,122],"can":[24,168],"effectively":[25,169],"guarantee":[26],"security":[28],"IIoT.":[30],"Over":[31],"past":[33],"decade,":[34],"different":[35],"methods":[36],"based":[40,113],"on":[41,114,146],"deep":[42],"learning":[43,110],"(DL)":[44],"have":[45],"been":[46],"proposed,":[47],"which":[48],"helps":[49],"keep":[52],"evolving":[53],"and":[54,72,166],"become":[55,74],"robust.":[57],"However,":[58],"these":[59,102],"previous":[60],"researches":[61],"usually":[62],"require":[63],"participation":[65],"a":[67,107],"large":[68],"number":[69],"experts,":[71],"gradually":[73],"invalid":[75],"with":[76],"continuous":[78],"methods.":[82],"The":[83],"limited":[84],"compute":[85],"capability":[86],"devices":[89],"also":[90],"greatly":[91],"hinder":[92],"deployment":[94],"overly":[96],"complex":[97,174],"DL":[98],"models.":[99],"To":[100],"address":[101],"challenges,":[103],"this":[104],"paper":[105],"proposes":[106],"lightweight":[108],"semi-supervised":[109],"(LSSL)":[111],"consistency":[115,133,164],"regularization":[116],"for":[117,132,140],"detection.":[119],"Our":[120],"proposed":[121],"enhances":[123],"performance":[126,155],"by":[127,162],"using":[128],"unlabeled":[129],"traffic":[130],"data":[131],"training.":[134],"Besides,":[135],"we":[136],"adopt":[137],"separable":[138],"convolutions":[139],"efficient":[141],"feature":[142],"extraction.":[143],"Experimental":[144],"results":[145],"two":[147],"widely-used":[148],"benchmark":[149],"datasets":[150],"show":[151],"that":[152],"our":[157],"model":[158],"is":[159],"significantly":[160],"improved":[161],"training,":[165],"it":[167],"detect":[170],"various":[171],"in":[173],"networks.":[175]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
