{"id":"https://openalex.org/W4392120324","doi":"https://doi.org/10.1186/s40537-024-00892-y","title":"Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning","display_name":"Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning","publication_year":2024,"publication_date":"2024-02-24","ids":{"openalex":"https://openalex.org/W4392120324","doi":"https://doi.org/10.1186/s40537-024-00892-y"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-024-00892-y","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-024-00892-y","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-024-00892-y","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-024-00892-y","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101828523","display_name":"Jing Li","orcid":"https://orcid.org/0000-0002-8235-9038"},"institutions":[{"id":"https://openalex.org/I4210089915","display_name":"Newcastle University Medicine Malaysia","ror":"https://ror.org/009e9eq52","country_code":"MY","type":"education","lineage":["https://openalex.org/I4210089915"]},{"id":"https://openalex.org/I4576418","display_name":"University of Technology Malaysia","ror":"https://ror.org/026w31v75","country_code":"MY","type":"education","lineage":["https://openalex.org/I4576418"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Jing Li","raw_affiliation_strings":["University of Technology Malaysia, Johor Bahru, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology Malaysia, Johor Bahru, Malaysia","institution_ids":["https://openalex.org/I4210089915","https://openalex.org/I4576418"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086606810","display_name":"Mohd Shahizan Othman","orcid":"https://orcid.org/0000-0003-4261-1873"},"institutions":[{"id":"https://openalex.org/I4210089915","display_name":"Newcastle University Medicine Malaysia","ror":"https://ror.org/009e9eq52","country_code":"MY","type":"education","lineage":["https://openalex.org/I4210089915"]},{"id":"https://openalex.org/I4576418","display_name":"University of Technology Malaysia","ror":"https://ror.org/026w31v75","country_code":"MY","type":"education","lineage":["https://openalex.org/I4576418"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Mohd Shahizan Othman","raw_affiliation_strings":["University of Technology Malaysia, Johor Bahru, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology Malaysia, Johor Bahru, Malaysia","institution_ids":["https://openalex.org/I4210089915","https://openalex.org/I4576418"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089927436","display_name":"Hewan Chen","orcid":"https://orcid.org/0009-0003-6259-3817"},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hewan Chen","raw_affiliation_strings":["China Jiliang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Jiliang University, Hangzhou, China","institution_ids":["https://openalex.org/I55538621"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079146277","display_name":"Lizawati Mi Yusuf","orcid":"https://orcid.org/0000-0003-4171-3253"},"institutions":[{"id":"https://openalex.org/I4210089915","display_name":"Newcastle University Medicine Malaysia","ror":"https://ror.org/009e9eq52","country_code":"MY","type":"education","lineage":["https://openalex.org/I4210089915"]},{"id":"https://openalex.org/I4576418","display_name":"University of Technology Malaysia","ror":"https://ror.org/026w31v75","country_code":"MY","type":"education","lineage":["https://openalex.org/I4576418"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Lizawati Mi Yusuf","raw_affiliation_strings":["University of Technology Malaysia, Johor Bahru, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology Malaysia, Johor Bahru, Malaysia","institution_ids":["https://openalex.org/I4210089915","https://openalex.org/I4576418"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5089927436"],"corresponding_institution_ids":["https://openalex.org/I55538621"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":47.1591,"has_fulltext":true,"cited_by_count":147,"citation_normalized_percentile":{"value":0.99957002,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"11","issue":"1","first_page":null,"last_page":null},"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9994999766349792,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9988999962806702,"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":0.8478232622146606},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.8455572724342346},{"id":"https://openalex.org/keywords/computational-science-and-engineering","display_name":"Computational Science and Engineering","score":0.7204656600952148},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.7092643976211548},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.6329708099365234},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6058880686759949},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5892921686172485},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5723000764846802},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.503117024898529},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49695828557014465},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4488891065120697},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36724570393562317},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.13484010100364685}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8478232622146606},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.8455572724342346},{"id":"https://openalex.org/C68597687","wikidata":"https://www.wikidata.org/wiki/Q362601","display_name":"Computational Science and Engineering","level":2,"score":0.7204656600952148},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.7092643976211548},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.6329708099365234},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6058880686759949},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5892921686172485},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5723000764846802},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.503117024898529},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49695828557014465},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4488891065120697},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36724570393562317},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.13484010100364685},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-024-00892-y","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-024-00892-y","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-024-00892-y","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:cfbe3be1c5da4ba6a663cb6c4aac25ab","is_oa":false,"landing_page_url":"https://doaj.org/article/cfbe3be1c5da4ba6a663cb6c4aac25ab","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 11, Iss 1, Pp 1-44 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-024-00892-y","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-024-00892-y","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-024-00892-y","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4699999988079071,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392120324.pdf"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W987648574","https://openalex.org/W1969466477","https://openalex.org/W2008224380","https://openalex.org/W2076384720","https://openalex.org/W2084496302","https://openalex.org/W2096205677","https://openalex.org/W2097034581","https://openalex.org/W2134295053","https://openalex.org/W2155461860","https://openalex.org/W2267339884","https://openalex.org/W2279785795","https://openalex.org/W2284098035","https://openalex.org/W2296509296","https://openalex.org/W2334853001","https://openalex.org/W2557450880","https://openalex.org/W2615698474","https://openalex.org/W2626468835","https://openalex.org/W2748771977","https://openalex.org/W2763978449","https://openalex.org/W2785446263","https://openalex.org/W2795626462","https://openalex.org/W2807786182","https://openalex.org/W2883554196","https://openalex.org/W2892556724","https://openalex.org/W2905186525","https://openalex.org/W2911505293","https://openalex.org/W2913330314","https://openalex.org/W2958489519","https://openalex.org/W2962910311","https://openalex.org/W2963748489","https://openalex.org/W2972414240","https://openalex.org/W2989622188","https://openalex.org/W3001675796","https://openalex.org/W3035366542","https://openalex.org/W3086419524","https://openalex.org/W3095531713","https://openalex.org/W3097529015","https://openalex.org/W3106059286","https://openalex.org/W3106741970","https://openalex.org/W3135011374","https://openalex.org/W3162956350","https://openalex.org/W3163301462","https://openalex.org/W3198200730","https://openalex.org/W3206599325","https://openalex.org/W4200470600","https://openalex.org/W4205136287","https://openalex.org/W4206130810","https://openalex.org/W4206141718","https://openalex.org/W4206450891","https://openalex.org/W4212808029","https://openalex.org/W4221004701","https://openalex.org/W4224272083","https://openalex.org/W4281261386","https://openalex.org/W4312651860","https://openalex.org/W4383218272","https://openalex.org/W4387647860","https://openalex.org/W6641082943"],"related_works":["https://openalex.org/W4245926026","https://openalex.org/W4311097251","https://openalex.org/W2586548817","https://openalex.org/W2625093826","https://openalex.org/W2950174689","https://openalex.org/W4200598720","https://openalex.org/W2921026492","https://openalex.org/W4361251261","https://openalex.org/W3031181660","https://openalex.org/W4285201139"],"abstract_inverted_index":{"Abstract":[0],"Internet":[1],"of":[2,115,128,139,169,211],"Things":[3],"(IoT)":[4],"devices":[5],"are":[6],"widely":[7],"used":[8],"but":[9],"also":[10],"vulnerable":[11],"to":[12,49,134,158],"cyberattacks":[13],"that":[14,127],"can":[15],"cause":[16],"security":[17],"issues.":[18],"To":[19],"protect":[20],"against":[21],"this,":[22],"machine":[23,73,216],"learning":[24],"approaches":[25],"have":[26],"been":[27],"developed":[28],"for":[29,56,67,162,174,184,190,215],"network":[30,69],"intrusion":[31,70,187,218],"detection":[32,54,71,107,188,219],"in":[33,72,136,220],"IoT.":[34],"These":[35],"often":[36],"use":[37],"feature":[38,42,63,103,110,123,142,212],"reduction":[39,124,213],"techniques":[40,214],"like":[41,83],"selection":[43,66,111,143,163],"or":[44],"extraction":[45,64,104,120,165],"before":[46],"feeding":[47],"data":[48],"models.":[50],"This":[51,59,172],"helps":[52],"make":[53],"efficient":[55],"real-time":[57],"needs.":[58],"paper":[60],"thoroughly":[61],"compares":[62],"and":[65,86,99,130,148,177,200],"IoT":[68,92,197,221],"learning-based":[74],"attack":[75],"classification":[76],"framework.":[77],"It":[78],"looks":[79],"at":[80],"performance":[81,108],"metrics":[82],"accuracy,":[84],"f1-score,":[85],"runtime,":[87],"etc.":[88],"on":[89],"the":[90,113,137,160,167,194,205],"heterogenous":[91],"dataset":[93,198],"named":[94],"Network":[95],"TON-IoT":[96,195],"using":[97],"binary":[98,176],"multiclass":[100,178],"classification.":[101,179],"Overall,":[102,204],"gives":[105],"better":[106],"than":[109,164],"as":[112],"number":[114,138,168],"features":[116,170],"is":[117,131],"small.":[118],"Moreover,":[119],"shows":[121],"less":[122,132,145],"compared":[125,151],"with":[126,152],"selection,":[129],"sensitive":[133],"changes":[135],"features.":[140],"However,":[141],"achieves":[144],"model":[146],"training":[147],"inference":[149],"time":[150],"its":[153],"counterpart.":[154],"Also,":[155],"more":[156],"space":[157],"improve":[159],"accuracy":[161],"when":[166],"changes.":[171],"holds":[173],"both":[175],"The":[180],"study":[181],"provides":[182],"guidelines":[183],"selecting":[185],"appropriate":[186],"methods":[189],"particular":[191],"scenarios.":[192],"Before,":[193],"heterogeneous":[196],"comparison":[199,210],"recommendations":[201],"were":[202],"overlooked.":[203],"research":[206],"presents":[207],"a":[208],"thorough":[209],"learning-driven":[217],"networks.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":36},{"year":2025,"cited_by_count":77},{"year":2024,"cited_by_count":34}],"updated_date":"2026-05-23T08:51:43.019350","created_date":"2025-10-10T00:00:00"}