{"id":"https://openalex.org/W2794048982","doi":"https://doi.org/10.1109/access.2018.2810198","title":"An Improved Intrusion Detection Algorithm Based on GA and SVM","display_name":"An Improved Intrusion Detection Algorithm Based on GA and SVM","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2794048982","doi":"https://doi.org/10.1109/access.2018.2810198","mag":"2794048982"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2810198","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2810198","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2810198","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089817007","display_name":"Peiying Tao","orcid":"https://orcid.org/0000-0003-1469-5694"},"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":"Peiying Tao","raw_affiliation_strings":["Key Laboratory of Broadband Wireless Communication and Sensor Network Technology, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-1469-5694","affiliations":[{"raw_affiliation_string":"Key Laboratory of Broadband Wireless Communication and Sensor Network Technology, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050582535","display_name":"Zhe Sun","orcid":"https://orcid.org/0000-0001-6694-2568"},"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":"Zhe Sun","raw_affiliation_strings":["Key Laboratory of Broadband Wireless Communication and Sensor Network Technology, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Broadband Wireless Communication and Sensor Network Technology, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112600034","display_name":"Zhixin Sun","orcid":"https://orcid.org/0000-0001-7006-7233"},"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":"Zhixin Sun","raw_affiliation_strings":["Key Laboratory of Broadband Wireless Communication and Sensor Network Technology, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Broadband Wireless Communication and Sensor Network Technology, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":18.0071,"has_fulltext":false,"cited_by_count":262,"citation_normalized_percentile":{"value":0.99389015,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"6","issue":null,"first_page":"13624","last_page":"13631"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9998999834060669,"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":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9973999857902527,"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":0.995199978351593,"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/support-vector-machine","display_name":"Support vector machine","score":0.8101741671562195},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.762797474861145},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6484696269035339},{"id":"https://openalex.org/keywords/crossover","display_name":"Crossover","score":0.6383197903633118},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6162671446800232},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.5953232049942017},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.5684854984283447},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5244422554969788},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5198640823364258},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46509090065956116},{"id":"https://openalex.org/keywords/false-positive-rate","display_name":"False positive rate","score":0.4636121690273285},{"id":"https://openalex.org/keywords/population-based-incremental-learning","display_name":"Population-based incremental learning","score":0.44238054752349854},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.4195480942726135},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.41353869438171387},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41016942262649536},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3359082043170929}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8101741671562195},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.762797474861145},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6484696269035339},{"id":"https://openalex.org/C122507166","wikidata":"https://www.wikidata.org/wiki/Q628906","display_name":"Crossover","level":2,"score":0.6383197903633118},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6162671446800232},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5953232049942017},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.5684854984283447},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5244422554969788},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5198640823364258},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46509090065956116},{"id":"https://openalex.org/C95922358","wikidata":"https://www.wikidata.org/wiki/Q5432725","display_name":"False positive rate","level":2,"score":0.4636121690273285},{"id":"https://openalex.org/C184497298","wikidata":"https://www.wikidata.org/wiki/Q7229773","display_name":"Population-based incremental learning","level":3,"score":0.44238054752349854},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4195480942726135},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.41353869438171387},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41016942262649536},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3359082043170929},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2810198","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2810198","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c9797012c0ae457189afc0f6d971f5d5","is_oa":true,"landing_page_url":"https://doaj.org/article/c9797012c0ae457189afc0f6d971f5d5","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":"IEEE Access, Vol 6, Pp 13624-13631 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2810198","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2810198","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5799999833106995,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G2210598306","display_name":null,"funder_award_id":"61602259","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3580208","display_name":null,"funder_award_id":"BK20150866","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G4229554593","display_name":null,"funder_award_id":"BK20160913","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G5620472912","display_name":"\u57fa\u4e8e6LoBLE\u7684\u4f4e\u529f\u8017\u84dd\u7259\u7f51\u72b6\u7f51\u7edc\u90bb\u5c45\u53d1\u73b0\u673a\u5236\u7814\u7a76","funder_award_id":"61702281","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6153705047","display_name":"\u57fa\u4e8e\u53ef\u5851\u6027\u5e72\u6270\u7684\u65e0\u7ebf\u4f20\u611f\u5668\u7f51\u7edc\u65f6\u95f4\u540c\u6b65\u673a\u5236\u7814\u7a76","funder_award_id":"61373135","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7678994517","display_name":"\u8f6f\u4ef6\u5b9a\u4e49\u5927\u6570\u636e\u7f51\u7edc\u5f02\u5e38\u6d41\u91cf\u68c0\u6d4b\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61672299","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation 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/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1505615071","https://openalex.org/W1967376128","https://openalex.org/W2031901130","https://openalex.org/W2035155387","https://openalex.org/W2047603677","https://openalex.org/W2469293760","https://openalex.org/W2493920898","https://openalex.org/W2512989563","https://openalex.org/W2524655848","https://openalex.org/W2536661541","https://openalex.org/W2541712849","https://openalex.org/W2546923044","https://openalex.org/W2599306383","https://openalex.org/W2608629053","https://openalex.org/W2619636815","https://openalex.org/W2622445371","https://openalex.org/W2748936647"],"related_works":["https://openalex.org/W2363406585","https://openalex.org/W2393267898","https://openalex.org/W2369874171","https://openalex.org/W2383301100","https://openalex.org/W2392864074","https://openalex.org/W2352639800","https://openalex.org/W2376095800","https://openalex.org/W3112374511","https://openalex.org/W1965918352","https://openalex.org/W2931259"],"abstract_inverted_index":{"In":[0],"the":[1,7,51,67,72,75,78,85,95,112,119,124,130,137,141,156,159,163,168,173,183,189],"era":[2],"of":[3,10,61,74,91,146],"big":[4],"data,":[5],"with":[6,115,177],"increasing":[8],"number":[9],"audit":[11],"data":[12],"features,":[13],"human-centered":[14],"smart":[15],"intrusion":[16,34,44,180],"detection":[17,35,181,184],"system":[18],"performance":[19],"is":[20,186],"decreasing":[21],"in":[22,118],"training":[23],"time":[24],"and":[25,28,46,58,77,88,99,128,144,171,188,192],"classification":[26,174],"accuracy,":[27],"many":[29],"support":[30,62],"vector":[31,63],"machine":[32,64],"(SVM)-based":[33],"algorithms":[36],"have":[37],"been":[38],"widely":[39],"used":[40],"to":[41,94,136],"identify":[42],"an":[43,116],"quickly":[45],"accurately.":[47],"This":[48],"paper":[49],"proposes":[50],"FWP-SVM-genetic":[52],"algorithm":[53,82,114,157,160],"(GA)":[54],"(feature":[55],"selection,":[56],"weight,":[57],"parameter":[59],"optimization":[60],"based":[65,70,110],"on":[66,71,111],"genetic":[68,113],"algorithm)":[69],"characteristics":[73],"GA":[76,92],"SVM":[79,125,147],"algorithm.":[80],"The":[81,151],"first":[83],"optimizes":[84],"crossover":[86],"probability":[87,90],"mutation":[89],"according":[93,135],"population":[96],"evolution":[97],"algebra":[98],"fitness":[100,120],"value;":[101],"then,":[102],"it":[103],"subsequently":[104],"uses":[105],"a":[106],"feature":[107,139,142],"selection":[108],"method":[109],"innovation":[117],"function":[121],"that":[122,155],"decreases":[123,167],"error":[126,169],"rate":[127,185],"increases":[129,162],"true":[131,164],"positive":[132,165,191],"rate.":[133],"Finally,":[134],"optimal":[138],"subset,":[140],"weights":[143],"parameters":[145],"are":[148,196],"simultaneously":[149],"optimized.":[150],"simulation":[152],"results":[153],"show":[154],"accelerates":[158],"convergence,":[161],"rate,":[166,170],"shortens":[172],"time.":[175],"Compared":[176],"other":[178],"SVM-based":[179],"algorithms,":[182],"higher":[187],"false":[190,193],"negative":[194],"rates":[195],"lower.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":29},{"year":2024,"cited_by_count":43},{"year":2023,"cited_by_count":46},{"year":2022,"cited_by_count":46},{"year":2021,"cited_by_count":51},{"year":2020,"cited_by_count":29},{"year":2019,"cited_by_count":13},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
