{"id":"https://openalex.org/W4206141718","doi":"https://doi.org/10.1186/s40537-021-00558-z","title":"IoT information theft prediction using ensemble feature selection","display_name":"IoT information theft prediction using ensemble feature selection","publication_year":2022,"publication_date":"2022-01-06","ids":{"openalex":"https://openalex.org/W4206141718","doi":"https://doi.org/10.1186/s40537-021-00558-z"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-021-00558-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-021-00558-z","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-021-00558-z","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/s40537-021-00558-z","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004094853","display_name":"Joffrey L. Leevy","orcid":"https://orcid.org/0000-0002-7079-7540"},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Joffrey L. Leevy","raw_affiliation_strings":["Florida Atlantic University, 777 Glades Road, Boca Raton, 33431, FL, USA"],"raw_orcid":"https://orcid.org/0000-0002-7079-7540","affiliations":[{"raw_affiliation_string":"Florida Atlantic University, 777 Glades Road, Boca Raton, 33431, FL, USA","institution_ids":["https://openalex.org/I63772739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047489766","display_name":"John Hancock","orcid":null},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John Hancock","raw_affiliation_strings":["Florida Atlantic University, 777 Glades Road, Boca Raton, 33431, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Florida Atlantic University, 777 Glades Road, Boca Raton, 33431, FL, USA","institution_ids":["https://openalex.org/I63772739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089170562","display_name":"Taghi M. Khoshgoftaar","orcid":null},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Taghi M. Khoshgoftaar","raw_affiliation_strings":["Florida Atlantic University, 777 Glades Road, Boca Raton, 33431, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Florida Atlantic University, 777 Glades Road, Boca Raton, 33431, FL, USA","institution_ids":["https://openalex.org/I63772739"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059862877","display_name":"Jared M. Peterson","orcid":null},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jared M. Peterson","raw_affiliation_strings":["Florida Atlantic University, 777 Glades Road, Boca Raton, 33431, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Florida Atlantic University, 777 Glades Road, Boca Raton, 33431, FL, USA","institution_ids":["https://openalex.org/I63772739"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5004094853"],"corresponding_institution_ids":["https://openalex.org/I63772739"],"apc_list":{"value":2290,"currency":"USD","value_usd":2290},"apc_paid":{"value":2290,"currency":"USD","value_usd":2290},"fwci":3.0329,"has_fulltext":true,"cited_by_count":27,"citation_normalized_percentile":{"value":0.91147673,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"9","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":0.9997000098228455,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9990000128746033,"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":0.8382512331008911},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7872493267059326},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.7317173480987549},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.7266054153442383},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.6257932186126709},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.624657154083252},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6245538592338562},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5995421409606934},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5979523062705994},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.5634851455688477},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49545252323150635},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.48645564913749695},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4603744149208069},{"id":"https://openalex.org/keywords/computational-intelligence","display_name":"Computational intelligence","score":0.4256269335746765},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.38469183444976807},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.29679277539253235}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8382512331008911},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7872493267059326},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.7317173480987549},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7266054153442383},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.6257932186126709},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.624657154083252},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6245538592338562},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5995421409606934},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5979523062705994},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.5634851455688477},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49545252323150635},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.48645564913749695},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4603744149208069},{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.4256269335746765},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.38469183444976807},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29679277539253235},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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:10.1186/s40537-021-00558-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-021-00558-z","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-021-00558-z","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:d4605ff8d8fd4b9c8aa16603020017b8","is_oa":true,"landing_page_url":"https://doaj.org/article/d4605ff8d8fd4b9c8aa16603020017b8","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":"Journal of Big Data, Vol 9, Iss 1, Pp 1-48 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-021-00558-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-021-00558-z","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-021-00558-z","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":[{"display_name":"Peace, Justice and strong institutions","score":0.6700000166893005,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310801","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387"},{"id":"https://openalex.org/F4320317380","display_name":"Universidad del Atl\u00e1ntico","ror":"https://ror.org/05mm1w714"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4206141718.pdf","grobid_xml":"https://content.openalex.org/works/W4206141718.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W1966716734","https://openalex.org/W2023938061","https://openalex.org/W2088403794","https://openalex.org/W2101754595","https://openalex.org/W2141014056","https://openalex.org/W2164627280","https://openalex.org/W2279833412","https://openalex.org/W2318802957","https://openalex.org/W2594014086","https://openalex.org/W2611652092","https://openalex.org/W2724268118","https://openalex.org/W2766428736","https://openalex.org/W2788113938","https://openalex.org/W2807319534","https://openalex.org/W2896236534","https://openalex.org/W2899434936","https://openalex.org/W2901835867","https://openalex.org/W2911964244","https://openalex.org/W2912326390","https://openalex.org/W2913130920","https://openalex.org/W2913326662","https://openalex.org/W2952066300","https://openalex.org/W2963748489","https://openalex.org/W2966632508","https://openalex.org/W2971991542","https://openalex.org/W2972553609","https://openalex.org/W2997604048","https://openalex.org/W3000307855","https://openalex.org/W3005895046","https://openalex.org/W3013692727","https://openalex.org/W3014810737","https://openalex.org/W3041121917","https://openalex.org/W3044867970","https://openalex.org/W3084540277","https://openalex.org/W3094948551","https://openalex.org/W3105233262","https://openalex.org/W3105570852","https://openalex.org/W3108630703","https://openalex.org/W3109522940","https://openalex.org/W3116162736","https://openalex.org/W3116191808","https://openalex.org/W3120244865","https://openalex.org/W3146612261","https://openalex.org/W3162222846","https://openalex.org/W3165582150","https://openalex.org/W3206014301","https://openalex.org/W3207891930","https://openalex.org/W4212859211","https://openalex.org/W4235730433","https://openalex.org/W4248220371"],"related_works":["https://openalex.org/W2099182244","https://openalex.org/W2794896638","https://openalex.org/W1580150424","https://openalex.org/W1807784185","https://openalex.org/W2325482571","https://openalex.org/W4390905871","https://openalex.org/W2076543106","https://openalex.org/W4241032203","https://openalex.org/W3202800081","https://openalex.org/W2088798842"],"abstract_inverted_index":{"Abstract":[0],"The":[1,117,156],"recent":[2],"years":[3],"have":[4],"seen":[5],"a":[6,123,152],"proliferation":[7],"of":[8,10,23,88,106,126],"Internet":[9],"Things":[11],"(IoT)":[12],"devices":[13],"and":[14,78,134,138,151,172,203],"an":[15,20],"associated":[16],"security":[17],"risk":[18],"from":[19,64,74],"increasing":[21],"volume":[22],"malicious":[24],"traffic":[25,44],"worldwide.":[26],"For":[27,179],"this":[28,49],"reason,":[29],"datasets":[30],"such":[31],"as":[32,69,71],"Bot-IoT":[33,56],"were":[34],"created":[35],"to":[36,41,57],"train":[37],"machine":[38],"learning":[39],"classifiers":[40,118],"identify":[42],"attack":[43,100],"in":[45],"IoT":[46],"networks.":[47],"In":[48],"study,":[50],"we":[51,120,183],"build":[52],"predictive":[53],"models":[54],"with":[55],"detect":[58],"attacks":[59],"represented":[60],"by":[61],"dataset":[62,72],"instances":[63,73],"the":[65,75,86,113,166,175,180],"Information":[66],"Theft":[67],"category,":[68],"well":[70],"data":[76,208],"exfiltration":[77],"keylogging":[79],"subcategories.":[80],"Our":[81],"contribution":[82],"is":[83],"centered":[84],"on":[85,94],"evaluation":[87],"ensemble":[89,105,128,187],"feature":[90,198],"selection":[91],"techniques":[92],"(FSTs)":[93],"classification":[95,161,192],"performance":[96,162,193],"for":[97,159],"these":[98],"specific":[99],"instances.":[101],"A":[102],"group":[103],"or":[104],"FSTs":[107,188],"will":[108],"often":[109],"perform":[110],"better":[111],"than":[112],"best":[114],"individual":[115],"technique.":[116],"that":[119,185],"use":[121],"are":[122,163,195],"diverse":[124],"set":[125],"four":[127,139],"learners":[129,141],"(Light":[130],"GBM,":[131],"CatBoost,":[132],"XGBoost,":[133],"random":[135],"forest":[136],"(RF))":[137],"non-ensemble":[140],"(logistic":[142],"regression":[143],"(LR),":[144],"decision":[145],"tree":[146],"(DT),":[147],"Naive":[148],"Bayes":[149],"(NB),":[150],"multi-layer":[153],"perceptron":[154],"(MLP)).":[155],"metrics":[157],"used":[158],"evaluating":[160],"area":[164],"under":[165],"receiver":[167],"operating":[168],"characteristic":[169],"curve":[170,177],"(AUC)":[171],"Area":[173],"Under":[174],"precision-recall":[176],"(AUPRC).":[178],"most":[181],"part,":[182],"determined":[184],"our":[186],"do":[189],"not":[190],"affect":[191],"but":[194],"beneficial":[196],"because":[197],"reduction":[199],"eases":[200],"computational":[201],"burden":[202],"provides":[204],"insight":[205],"through":[206],"improved":[207],"visualization.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}