乐胖代购免代理版

{"id":"https://openalex.org/W3176102326","doi":"https://doi.org/10.1049/cps2.12013","title":"Network intrusion detection using machine learning approaches: Addressing data imbalance","display_name":"Network intrusion detection using machine learning approaches: Addressing data imbalance","publication_year":2021,"publication_date":"2021-06-23","ids":{"openalex":"https://openalex.org/W3176102326","doi":"https://doi.org/10.1049/cps2.12013","mag":"3176102326"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1049/cps2.12013","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/cps2.12013","source":{"id":"https://openalex.org/S4210178773","display_name":"IET Cyber-Physical Systems Theory & Applications","issn_l":"2398-3396","issn":["2398-3396"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/cps2.12013","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070445790","display_name":"Rahbar Ahsan","orcid":"https://orcid.org/0000-0001-6624-1462"},"institutions":[{"id":"https://openalex.org/I67031392","display_name":"Carleton University","ror":"https://ror.org/02qtvee93","country_code":"CA","type":"education","lineage":["https://openalex.org/I67031392"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Rahbar Ahsan","raw_affiliation_strings":["School of Computer Science, Carleton University, Ottawa, Canada"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Carleton University, Ottawa, Canada","institution_ids":["https://openalex.org/I67031392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100651614","display_name":"Wei Shi","orcid":"https://orcid.org/0000-0002-3071-8350"},"institutions":[{"id":"https://openalex.org/I67031392","display_name":"Carleton University","ror":"https://ror.org/02qtvee93","country_code":"CA","type":"education","lineage":["https://openalex.org/I67031392"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Wei Shi","raw_affiliation_strings":["School of Information Technology, Carleton University, Ottawa, Canada"],"affiliations":[{"raw_affiliation_string":"School of Information Technology, Carleton University, Ottawa, Canada","institution_ids":["https://openalex.org/I67031392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009496814","display_name":"Jean\u2010Pierre Corriveau","orcid":"https://orcid.org/0000-0002-6570-3108"},"institutions":[{"id":"https://openalex.org/I67031392","display_name":"Carleton University","ror":"https://ror.org/02qtvee93","country_code":"CA","type":"education","lineage":["https://openalex.org/I67031392"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jean\u2010Pierre Corriveau","raw_affiliation_strings":["School of Computer Science, Carleton University, Ottawa, Canada"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Carleton University, Ottawa, Canada","institution_ids":["https://openalex.org/I67031392"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5070445790"],"corresponding_institution_ids":["https://openalex.org/I67031392"],"apc_list":{"value":2000,"currency":"EUR","value_usd":2200,"provenance":"doaj"},"apc_paid":{"value":2000,"currency":"EUR","value_usd":2200,"provenance":"doaj"},"fwci":1.896,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.786866,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":92},"biblio":{"volume":"7","issue":"1","first_page":"30","last_page":"39"},"is_retracted":false,"is_paratext":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":0.9997,"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":0.9992,"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/oversampling","display_name":"Oversampling","score":0.67002535},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6593709}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.79303694},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7909542},{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.7836255},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7286521},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.67547137},{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.67002535},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6593709},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.48804227},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4825008},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46208426},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41637412},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1049/cps2.12013","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/cps2.12013","source":{"id":"https://openalex.org/S4210178773","display_name":"IET Cyber-Physical Systems Theory & Applications","issn_l":"2398-3396","issn":["2398-3396"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1049/cps2.12013","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/cps2.12013","source":{"id":"https://openalex.org/S4210178773","display_name":"IET Cyber-Physical Systems Theory & Applications","issn_l":"2398-3396","issn":["2398-3396"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"display_name":"Peace, justice, and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.44}],"grants":[{"funder":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada","award_id":"RGPIN\u20102020\u201006482"}],"datasets":[],"versions":[],"referenced_works_count":24,"referenced_works":["https://openalex.org/W1966741850","https://openalex.org/W1993220166","https://openalex.org/W1997415712","https://openalex.org/W2099940443","https://openalex.org/W2100495367","https://openalex.org/W2101234009","https://openalex.org/W2148143831","https://openalex.org/W2184413800","https://openalex.org/W2401501243","https://openalex.org/W2749908420","https://openalex.org/W2762776925","https://openalex.org/W2766315530","https://openalex.org/W2803255133","https://openalex.org/W2807786182","https://openalex.org/W2893186842","https://openalex.org/W2904969546","https://openalex.org/W2905097561","https://openalex.org/W2926701059","https://openalex.org/W2929803724","https://openalex.org/W2946127746","https://openalex.org/W2950250245","https://openalex.org/W3014732532","https://openalex.org/W3037958117","https://openalex.org/W3155649056"],"related_works":["https://openalex.org/W80466363","https://openalex.org/W4389233021","https://openalex.org/W4308469503","https://openalex.org/W4288337828","https://openalex.org/W4287816717","https://openalex.org/W32988189","https://openalex.org/W3016117175","https://openalex.org/W2947132063","https://openalex.org/W2904737874","https://openalex.org/W2399571531"],"abstract_inverted_index":{"Cybersecurity":[0],"has":[1],"become":[2],"a":[3,44,88],"significant":[4],"issue.":[5],"Machine":[6],"learning":[7,60,66,111,127],"algorithms":[8],"are":[9,24,133,159],"known":[10],"to":[11,103,119],"help":[12],"identify":[13],"cyberattacks":[14],"such":[15],"as":[16,62,64],"network":[17,21],"intrusion.":[18],"However,":[19],"common":[20],"intrusion":[22,40,81],"datasets":[23],"negatively":[25],"affected":[26],"by":[27],"class":[28],"imbalance:":[29],"the":[30,37,52,69,121,131,150],"normal":[31],"traffic":[32,41],"behaviour":[33,42],"constitutes":[34],"most":[35],"of":[36,51,56,87,123,130,149,156],"dataset,":[38],"whereas":[39],"forms":[43],"significantly":[45],"smaller":[46],"portion.":[47],"A":[48,113],"comparative":[49],"evaluation":[50],"performance":[53,106],"is":[54,116],"conducted":[55,152],"several":[57],"classical":[58,109],"machine":[59,110,126],"algorithms,":[61,67],"well":[63],"deep":[65],"on":[68],"well-known":[70],"National":[71],"Security":[72],"Lab":[73],"Knowledge":[74],"Discovery":[75],"and":[76,97,144,153],"Data":[77],"Mining":[78],"dataset":[79],"for":[80],"detection.":[82],"More":[83],"specifically,":[84],"two":[85],"variants":[86],"fully":[89],"connected":[90],"neural":[91],"network,":[92],"one":[93,98],"with":[94,137],"an":[95,154],"autoencoder":[96],"without,":[99],"have":[100],"been":[101],"implemented":[102],"compare":[104],"their":[105,157],"against":[107],"seven":[108],"algorithms.":[112,128],"voting":[114],"classifier":[115],"also":[117],"proposed":[118],"combine":[120],"decisions":[122],"these":[124],"nine":[125],"All":[129],"models":[132],"tested":[134],"in":[135],"combination":[136],"three":[138],"different":[139],"resampling":[140],"techniques:":[141],"oversampling,":[142],"undersampling,":[143],"hybrid":[145],"sampling.":[146],"The":[147],"details":[148],"experiments":[151],"analysis":[155],"results":[158],"then":[160],"discussed.":[161]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3176102326","counts_by_year":[{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2024-12-29T11:29:19.531153","created_date":"2021-07-05"}