{"id":"https://openalex.org/W4310398036","doi":"https://doi.org/10.3390/s22239326","title":"Evaluation of Machine Learning Techniques for Traffic Flow-Based Intrusion Detection","display_name":"Evaluation of Machine Learning Techniques for Traffic Flow-Based Intrusion Detection","publication_year":2022,"publication_date":"2022-11-30","ids":{"openalex":"https://openalex.org/W4310398036","doi":"https://doi.org/10.3390/s22239326","pmid":"https://pubmed.ncbi.nlm.nih.gov/36502028"},"language":"en","primary_location":{"id":"doi:10.3390/s22239326","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22239326","pdf_url":"https://www.mdpi.com/1424-8220/22/23/9326/pdf?version=1669800160","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/23/9326/pdf?version=1669800160","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032796449","display_name":"Maria A. Rodriguez","orcid":"https://orcid.org/0000-0002-2831-8526"},"institutions":[{"id":"https://openalex.org/I255234318","display_name":"Universidad de Zaragoza","ror":"https://ror.org/012a91z28","country_code":"ES","type":"education","lineage":["https://openalex.org/I255234318"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Mar\u00eda Rodr\u00edguez","raw_affiliation_strings":["Arag\u00f3n Institute of Engineering Research (I3A), University of Zaragoza, 50018 Zaragoza, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arag\u00f3n Institute of Engineering Research (I3A), University of Zaragoza, 50018 Zaragoza, Spain","institution_ids":["https://openalex.org/I255234318"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054935370","display_name":"\u00c1lvaro Alesanco","orcid":"https://orcid.org/0000-0002-5254-1402"},"institutions":[{"id":"https://openalex.org/I255234318","display_name":"Universidad de Zaragoza","ror":"https://ror.org/012a91z28","country_code":"ES","type":"education","lineage":["https://openalex.org/I255234318"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"\u00c1lvaro Alesanco","raw_affiliation_strings":["Arag\u00f3n Institute of Engineering Research (I3A), University of Zaragoza, 50018 Zaragoza, Spain"],"raw_orcid":"https://orcid.org/0000-0002-5254-1402","affiliations":[{"raw_affiliation_string":"Arag\u00f3n Institute of Engineering Research (I3A), University of Zaragoza, 50018 Zaragoza, Spain","institution_ids":["https://openalex.org/I255234318"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049919298","display_name":"Lorena Mehavilla","orcid":null},"institutions":[{"id":"https://openalex.org/I255234318","display_name":"Universidad de Zaragoza","ror":"https://ror.org/012a91z28","country_code":"ES","type":"education","lineage":["https://openalex.org/I255234318"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Lorena Mehavilla","raw_affiliation_strings":["Arag\u00f3n Institute of Engineering Research (I3A), University of Zaragoza, 50018 Zaragoza, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arag\u00f3n Institute of Engineering Research (I3A), University of Zaragoza, 50018 Zaragoza, Spain","institution_ids":["https://openalex.org/I255234318"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100678002","display_name":"J. Garc\u00eda","orcid":"https://orcid.org/0000-0001-9485-7678"},"institutions":[{"id":"https://openalex.org/I255234318","display_name":"Universidad de Zaragoza","ror":"https://ror.org/012a91z28","country_code":"ES","type":"education","lineage":["https://openalex.org/I255234318"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Jos\u00e9 Garc\u00eda","raw_affiliation_strings":["Arag\u00f3n Institute of Engineering Research (I3A), University of Zaragoza, 50018 Zaragoza, Spain"],"raw_orcid":"https://orcid.org/0000-0001-9485-7678","affiliations":[{"raw_affiliation_string":"Arag\u00f3n Institute of Engineering Research (I3A), University of Zaragoza, 50018 Zaragoza, Spain","institution_ids":["https://openalex.org/I255234318"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100678002"],"corresponding_institution_ids":["https://openalex.org/I255234318"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":4.9857,"has_fulltext":true,"cited_by_count":39,"citation_normalized_percentile":{"value":0.95580827,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"22","issue":"23","first_page":"9326","last_page":"9326"},"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":0.9997000098228455,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.8191220164299011},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.728215217590332},{"id":"https://openalex.org/keywords/c4.5-algorithm","display_name":"C4.5 algorithm","score":0.697577714920044},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5969061851501465},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5698947310447693},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5587756633758545},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.4954568147659302},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.49504223465919495},{"id":"https://openalex.org/keywords/traffic-classification","display_name":"Traffic classification","score":0.4835631549358368},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.48001593351364136},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.46275874972343445},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43028879165649414},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.41661909222602844},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.32079535722732544},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.2635113000869751},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.24092337489128113},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.22404420375823975}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8191220164299011},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.728215217590332},{"id":"https://openalex.org/C52003472","wikidata":"https://www.wikidata.org/wiki/Q1022655","display_name":"C4.5 algorithm","level":4,"score":0.697577714920044},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5969061851501465},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5698947310447693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5587756633758545},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.4954568147659302},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.49504223465919495},{"id":"https://openalex.org/C169988225","wikidata":"https://www.wikidata.org/wiki/Q7832484","display_name":"Traffic classification","level":3,"score":0.4835631549358368},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.48001593351364136},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.46275874972343445},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43028879165649414},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.41661909222602844},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32079535722732544},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2635113000869751},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.24092337489128113},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.22404420375823975}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011788","descriptor_name":"Quality of Life","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011788","descriptor_name":"Quality of Life","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011788","descriptor_name":"Quality of Life","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":7,"locations":[{"id":"doi:10.3390/s22239326","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22239326","pdf_url":"https://www.mdpi.com/1424-8220/22/23/9326/pdf?version=1669800160","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:36502028","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36502028","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:a35eaf2a7c634373a59b6cfe6fe09f3e","is_oa":true,"landing_page_url":"https://doaj.org/article/a35eaf2a7c634373a59b6cfe6fe09f3e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 22, Iss 23, p 9326 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/23/9326/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22239326","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 22; Issue 23; Pages: 9326","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9740321","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9740321","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:zaguan.unizar.es:120213","is_oa":true,"landing_page_url":"http://zaguan.unizar.es/record/120213","pdf_url":null,"source":{"id":"https://openalex.org/S4306401812","display_name":"Zaguan (University of Zaragoza Repository)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I255234318","host_organization_name":"Universidad de Zaragoza","host_organization_lineage":["https://openalex.org/I255234318"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:zenodo.org:12684339","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ s22239326","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, 22, 9326, (2022)","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.3390/s22239326","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22239326","pdf_url":"https://www.mdpi.com/1424-8220/22/23/9326/pdf?version=1669800160","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2219859537","display_name":null,"funder_award_id":"FEDER 2014-2020","funder_id":"https://openalex.org/F4320326208","funder_display_name":"Gobierno de Arag\u00f3n"},{"id":"https://openalex.org/G3727029632","display_name":null,"funder_award_id":"T31_20R","funder_id":"https://openalex.org/F4320326208","funder_display_name":"Gobierno de Arag\u00f3n"},{"id":"https://openalex.org/G3952741677","display_name":null,"funder_award_id":"UZ2021-TEC-01","funder_id":"https://openalex.org/F4320324111","funder_display_name":"Universidad de Zaragoza"},{"id":"https://openalex.org/G4163225974","display_name":null,"funder_award_id":"T31_20R","funder_id":"https://openalex.org/F4320324111","funder_display_name":"Universidad de Zaragoza"},{"id":"https://openalex.org/G6240230012","display_name":null,"funder_award_id":"2014-2020","funder_id":"https://openalex.org/F4320324111","funder_display_name":"Universidad de Zaragoza"}],"funders":[{"id":"https://openalex.org/F4320324111","display_name":"Universidad de Zaragoza","ror":"https://ror.org/012a91z28"},{"id":"https://openalex.org/F4320326208","display_name":"Gobierno de Arag\u00f3n","ror":"https://ror.org/0425pg203"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4310398036.pdf","grobid_xml":"https://content.openalex.org/works/W4310398036.grobid-xml"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W1495061682","https://openalex.org/W1512098439","https://openalex.org/W1528113134","https://openalex.org/W1570448133","https://openalex.org/W1912123407","https://openalex.org/W1952056635","https://openalex.org/W1966809779","https://openalex.org/W1988918299","https://openalex.org/W1991147747","https://openalex.org/W1999427165","https://openalex.org/W2031163547","https://openalex.org/W2087016914","https://openalex.org/W2099940443","https://openalex.org/W2101109743","https://openalex.org/W2132166479","https://openalex.org/W2142889610","https://openalex.org/W2143305710","https://openalex.org/W2278186031","https://openalex.org/W2296509296","https://openalex.org/W2342408547","https://openalex.org/W2620580412","https://openalex.org/W2732560875","https://openalex.org/W2770942607","https://openalex.org/W2785474195","https://openalex.org/W2789828921","https://openalex.org/W2801897485","https://openalex.org/W2911964244","https://openalex.org/W2921708219","https://openalex.org/W2924689635","https://openalex.org/W2959969964","https://openalex.org/W2978751771","https://openalex.org/W3016974523","https://openalex.org/W3042173389","https://openalex.org/W3043530913","https://openalex.org/W3172979816","https://openalex.org/W3180062783","https://openalex.org/W3194033356","https://openalex.org/W3213692590","https://openalex.org/W3217648337","https://openalex.org/W4205699531","https://openalex.org/W4206268789","https://openalex.org/W4213315959","https://openalex.org/W4241072669","https://openalex.org/W4244238212","https://openalex.org/W6640726002","https://openalex.org/W6676769703","https://openalex.org/W6750899311","https://openalex.org/W6768847047","https://openalex.org/W6800048129"],"related_works":["https://openalex.org/W3133985961","https://openalex.org/W2149721642","https://openalex.org/W4301398392","https://openalex.org/W2587362999","https://openalex.org/W2997818875","https://openalex.org/W4379534844","https://openalex.org/W266939152","https://openalex.org/W2587627203","https://openalex.org/W3178296362","https://openalex.org/W2924962435"],"abstract_inverted_index":{"Cybersecurity":[0],"is":[1,27,44,100,135,172,349],"one":[2],"of":[3,7,22,50,61,166,177,290,308,312,342,353,366,416],"the":[4,20,25,121,186,199,206,217,229,269,280,306,310,315,326,343,356,361,364,387,401,407,443,463,471,480,500],"great":[5,46],"challenges":[6],"today's":[8],"world.":[9],"Rapid":[10],"technological":[11],"development":[12],"has":[13,321,396],"allowed":[14],"society":[15],"to":[16,78,114,119,184,215,267,359,399,405,411,455,468,499],"prosper":[17],"and":[18,24,37,53,131,163,188,192,247,261,292,300,305,336,410,446,485],"improve":[19],"quality":[21],"life":[23],"world":[26],"more":[28,55],"dependent":[29],"on":[30,127,256,462],"new":[31,51,81],"technologies.":[32],"Managing":[33],"security":[34],"risks":[35],"quickly":[36],"effectively,":[38],"preventing,":[39],"identifying,":[40],"or":[41,491],"mitigating":[42],"them":[43],"a":[45,58,80,175,210,251,339,367,391,413,495],"challenge.":[47],"The":[48,141,195,371,421],"appearance":[49],"attacks,":[52,72],"with":[54,272,374,436],"frequency,":[56],"requires":[57],"constant":[59],"update":[60],"threat":[62],"detection":[63,87,483],"methods.":[64],"Traditional":[65],"signature-based":[66],"techniques":[67,95,113,224,373,427,475],"are":[68,75],"effective":[69],"for":[70,137],"known":[71],"but":[73],"they":[74],"not":[76],"able":[77],"detect":[79],"attack.":[82],"For":[83],"this":[84,105,147],"reason,":[85],"intrusion":[86,482],"systems":[88],"(IDS)":[89],"that":[90,99,159,180,470,486],"apply":[91],"machine":[92,111,473],"learning":[93,112,474],"(ML)":[94],"represent":[96],"an":[97],"alternative":[98,497],"gaining":[101],"importance":[102],"today.":[103],"In":[104],"work,":[106],"we":[107],"have":[108,225,264,302],"analyzed":[109],"different":[110,164,288],"determine":[115],"which":[116,134],"ones":[117],"permit":[118],"obtain":[120,412],"best":[122],"traffic":[123,153,157,162,170,187,202,218,299,403,408],"classification":[124,128,223,285,294,422,459],"results":[125,332,423,460],"based":[126,255],"performance":[129,369],"measurements":[130],"execution":[132,448],"times,":[133],"decisive":[136],"further":[138],"real-time":[139],"deployments.":[140],"CICIDS2017":[142,196,464],"dataset":[143,207,465],"was":[144],"selected":[145],"in":[146,209,279,328,355,386,442,479],"work":[148],"since":[149],"it":[150],"contains":[151,198],"bidirectional":[152],"flows":[154,219,409],"(derived":[155],"from":[156,220,418],"captures)":[158],"include":[160],"benign":[161],"types":[165,289],"up-to-date":[167],"attacks.":[168],"Each":[169],"flow":[171],"characterized":[173],"by":[174,337],"set":[176,341,415],"connection-related":[178],"attributes":[179,313,379,417],"can":[181,333],"be":[182,268,334,456,477],"used":[183,398],"model":[185],"distinguish":[189],"between":[190,287,297],"attacks":[191],"normal":[193,298],"flows.":[194,420],"also":[197,433],"raw":[200,402],"network":[201],"captures":[203,404],"collected":[204],"during":[205],"creation":[208],"packet-based":[211],"format,":[212],"thus":[213],"permitting":[214],"extract":[216],"them.":[221],"Various":[222],"been":[226,303,322,397],"evaluated":[227],"using":[228,314,425],"Weka":[230],"software:":[231],"naive":[232],"Bayes,":[233],"logistic,":[234],"multilayer":[235],"perceptron,":[236],"sequential":[237],"minimal":[238],"optimization,":[239],"k-nearest":[240],"neighbors,":[241],"adaptive":[242],"boosting,":[243],"OneR,":[244],"J48,":[245,260,492],"PART,":[246],"random":[248,262],"forest.":[249],"As":[250],"general":[252],"result,":[253],"methods":[254],"decision":[257],"trees":[258],"(PART,":[259],"forest)":[263],"turned":[265],"out":[266],"most":[270,344],"efficient":[271],"F1":[273,382,437],"values":[274,383],"above":[275,384,438],"0.999":[276],"(average":[277,440],"obtained":[278,424,441,461],"complete":[281,388,444],"dataset).":[282],"Moreover,":[283],"multiclass":[284],"(distinguishing":[286,295],"attack)":[291,301],"binary":[293,329],"only":[296],"compared,":[304],"effect":[307],"reducing":[309,325],"number":[311],"correlation-based":[316],"feature":[317],"selection":[318,377],"(CFS)":[319],"technique":[320],"evaluated.":[323],"By":[324],"complexity":[327],"classification,":[330],"better":[331],"obtained,":[335],"selecting":[338],"reduced":[340,414],"relevant":[345],"attributes,":[346],"less":[347],"time":[348,357],"required":[350,358],"(above":[351],"30%":[352],"decrease":[354],"test":[360],"model)":[362],"at":[363],"cost":[365],"small":[368],"loss.":[370],"tree-based":[372,426,472],"CFS":[375],"attribute":[376],"(six":[378],"selected)":[380],"reached":[381],"0.990":[385],"dataset.":[389],"Finally,":[390],"conventional":[392],"tool":[393],"like":[394],"Zeek":[395],"process":[400],"identify":[406],"these":[419],"(with":[428],"14":[429],"Zeek-based":[430],"attributes)":[431],"were":[432],"very":[434],"high,":[435],"0.997":[439],"dataset)":[445],"low":[447],"times":[449],"(allowing":[450],"several":[451],"hundred":[452],"thousand":[453],"flows/s":[454],"processed).":[457],"These":[458],"allow":[466],"us":[467],"affirm":[469],"may":[476,493],"appropriate":[478],"flow-based":[481],"problem":[484],"algorithms,":[487],"such":[488],"as":[489],"PART":[490],"offer":[494],"faster":[496],"solution":[498],"RF":[501],"technique.":[502]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":5}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}