{"id":"https://openalex.org/W4311484473","doi":"https://doi.org/10.1186/s40537-022-00661-9","title":"A new feature popularity framework for detecting cyberattacks using popular features","display_name":"A new feature popularity framework for detecting cyberattacks using popular features","publication_year":2022,"publication_date":"2022-12-15","ids":{"openalex":"https://openalex.org/W4311484473","doi":"https://doi.org/10.1186/s40537-022-00661-9"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-022-00661-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-022-00661-9","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-022-00661-9","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/s40537-022-00661-9","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001819774","display_name":"Richard Zuech","orcid":"https://orcid.org/0000-0002-5526-1094"},"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":"Richard Zuech","raw_affiliation_strings":["Florida Atlantic University, 777 Glades Road, Boca Raton, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Florida Atlantic University, 777 Glades Road, Boca Raton, 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, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Florida Atlantic University, 777 Glades Road, Boca Raton, FL, USA","institution_ids":["https://openalex.org/I63772739"]}]},{"author_position":"last","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, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Florida Atlantic University, 777 Glades Road, Boca Raton, FL, USA","institution_ids":["https://openalex.org/I63772739"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5001819774"],"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":0.5832,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.6787837,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"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":0.9998000264167786,"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":0.9998000264167786,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9955999851226807,"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/popularity","display_name":"Popularity","score":0.8776310086250305},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8224400877952576},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7504897117614746},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5316282510757446},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5194839239120483},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4799407124519348},{"id":"https://openalex.org/keywords/byte","display_name":"Byte","score":0.43707650899887085}],"concepts":[{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.8776310086250305},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8224400877952576},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7504897117614746},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5316282510757446},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5194839239120483},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4799407124519348},{"id":"https://openalex.org/C43364308","wikidata":"https://www.wikidata.org/wiki/Q8799","display_name":"Byte","level":2,"score":0.43707650899887085},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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:10.1186/s40537-022-00661-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-022-00661-9","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-022-00661-9","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:d7d58d9dd24346d795f53d84e60f5a71","is_oa":true,"landing_page_url":"https://doaj.org/article/d7d58d9dd24346d795f53d84e60f5a71","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 1-30 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-022-00661-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-022-00661-9","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-022-00661-9","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":[],"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":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4311484473.pdf","grobid_xml":"https://content.openalex.org/works/W4311484473.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1680392829","https://openalex.org/W1981276685","https://openalex.org/W1981552604","https://openalex.org/W2021200789","https://openalex.org/W2038894244","https://openalex.org/W2088535455","https://openalex.org/W2088794999","https://openalex.org/W2100788563","https://openalex.org/W2118561568","https://openalex.org/W2122210511","https://openalex.org/W2155653793","https://openalex.org/W2165250079","https://openalex.org/W2295598076","https://openalex.org/W2312301617","https://openalex.org/W2343828539","https://openalex.org/W2556301080","https://openalex.org/W2789828921","https://openalex.org/W2899434936","https://openalex.org/W2911964244","https://openalex.org/W3024905798","https://openalex.org/W3037824821","https://openalex.org/W3080177360","https://openalex.org/W3104887532","https://openalex.org/W3105524694","https://openalex.org/W3120244865","https://openalex.org/W3146612261","https://openalex.org/W3159405644","https://openalex.org/W4210491915","https://openalex.org/W4212883601","https://openalex.org/W4297846671","https://openalex.org/W6670422145"],"related_works":["https://openalex.org/W2368605798","https://openalex.org/W2518037665","https://openalex.org/W2348524959","https://openalex.org/W2477036161","https://openalex.org/W2368049389","https://openalex.org/W2384861574","https://openalex.org/W4294565801","https://openalex.org/W2170801710","https://openalex.org/W2952704802","https://openalex.org/W2741781807"],"abstract_inverted_index":{"Abstract":[0],"We":[1,258],"propose":[2],"a":[3,159],"novel":[4],"feature":[5,85,99,107,121,134,171,191,230],"popularity":[6,18,51,100,108,122,135,172,231,316],"framework,":[7],"and":[8,30,46,60,68,76,96,153,210,236,279,285,306,331],"introduce":[9],"this":[10,204],"new":[11,235],"framework":[12,173,232],"to":[13,63,83,114,176,220,319],"the":[14,39,241,276,288,298,303,329,335],"cybersecurity":[15],"domain.":[16],"Feature":[17,50,56,315],"has":[19],"not":[20,226,308],"yet":[21],"been":[22],"used":[23,82],"in":[24,127,174,297,311,340],"machine":[25],"learning":[26],"or":[27],"data":[28],"mining,":[29],"we":[31,252],"implement":[32],"it":[33,256],"with":[34,169,246],"three":[35,91,200,268,293],"web":[36,48,93,201,242,269,294],"attacks":[37,202,295],"from":[38,203,275,282],"CSE-CIC-IDS2018":[40,247],"dataset:":[41],"Brute":[42],"Force,":[43],"SQL":[44],"Injection,":[45],"XSS":[47],"attacks.":[49],"is":[52,109,166,225],"based":[53],"upon":[54],"ensemble":[55,140,147,157],"Selection":[57],"Techniques":[58],"(FSTs)":[59],"allows":[61],"us":[62,234],"more":[64],"easily":[65],"understand":[66],"common":[67],"important":[69],"features":[70,197,217,263,281],"between":[71],"different":[72,92],"cyberattacks.":[73],"Three":[74],"filter-based":[75],"four":[77,194,216,261,313],"supervised":[78],"learning-based":[79],"FSTs":[80,149],"are":[81,102,118],"generate":[84],"subsets":[86,123],"for":[87,106,150],"each":[88,151],"of":[89,130,141,148,287,302,337],"our":[90,98,170,221,267,292],"attack":[94,180,243],"datasets,":[95],"then":[97,154],"frameworks":[101],"applied.":[103],"Classification":[104],"performance":[105,126,224],"mostly":[110],"similar":[111],"as":[112,218,271],"compared":[113],"when":[115,189],"\u201call":[116],"features\u201d":[117],"evaluated":[119],"(with":[120],"having":[124],"better":[125,177,326],"5":[128],"out":[129],"15":[131],"experiments).":[132],"Our":[133],"technique":[136],"effectively":[137],"builds":[138],"an":[139,146],"ensembles":[142],"by":[143],"first":[144],"building":[145,155],"dataset,":[152],"another":[156],"across":[158,198],"dataset":[160],"agreement":[161],"dimension.":[162],"The":[163,193],"Jaccard":[164],"similarity":[165],"also":[167,333],"employed":[168],"order":[175],"identify":[178,266],"which":[179,322],"classes":[181],"should":[182,184,307],"(or":[183],"not)":[185],"be":[186],"grouped":[187],"together":[188],"applying":[190],"popularity.":[192],"most":[195],"popular":[196],"all":[199],"experiment":[205],"are:":[206],"Flow_Bytes_s,":[207],"Flow_IAT_Max,":[208],"Fwd_IAT_Std,":[209],"Fwd_IAT_Total.":[211],"When":[212],"only":[213],"using":[214],"these":[215,260,312],"input":[219],"models,":[222],"classification":[223],"seriously":[227],"degraded.":[228],"This":[229],"granted":[233],"previously":[237],"unseen":[238],"insights":[239],"into":[240,328],"detection":[244],"process":[245],"big":[248],"data,":[249],"even":[250],"though":[251],"had":[253],"intensely":[254],"studied":[255],"previously.":[257],"realized":[259],"particular":[262],"cannot":[264],"properly":[265],"attacks,":[270],"they":[272],"operate":[273,296],"mainly":[274],"time":[277],"dimension":[278],"NetFlow":[280],"layers":[283],"3":[284],"4":[286],"OSI":[289,304],"model.":[290],"Conversely,":[291],"application":[299],"layer":[300],"(7)":[301],"model":[305],"leave":[309],"signatures":[310],"features.":[314],"produces":[317],"easier":[318],"explain":[320],"models":[321,339],"provide":[323],"domain":[324],"experts":[325],"visibility":[327],"problem,":[330],"can":[332],"reduce":[334],"complexity":[336],"implementing":[338],"real-world":[341],"systems.":[342]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4}],"updated_date":"2026-08-22T07:34:49.880490","created_date":"2025-10-10T00:00:00"}