{"id":"https://openalex.org/W7117728183","doi":"https://doi.org/10.1109/wincom65874.2025.11313359","title":"Intrusion Detection in IoT Networks Using Hybrid Feature Selection","display_name":"Intrusion Detection in IoT Networks Using Hybrid Feature Selection","publication_year":2025,"publication_date":"2025-11-25","ids":{"openalex":"https://openalex.org/W7117728183","doi":"https://doi.org/10.1109/wincom65874.2025.11313359"},"language":null,"primary_location":{"id":"doi:10.1109/wincom65874.2025.11313359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wincom65874.2025.11313359","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 12th International Conference on Wireless Networks and Mobile Communications (WINCOM)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5121649579","display_name":"Aya El Hjajbi","orcid":null},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Aya El Hjajbi","raw_affiliation_strings":["Ibn Tofail University,LRI Research Laboratory,Kenitra,Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ibn Tofail University,LRI Research Laboratory,Kenitra,Morocco","institution_ids":["https://openalex.org/I3121676899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107013741","display_name":"Taha Archi","orcid":null},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Taha Archi","raw_affiliation_strings":["Ibn Tofail University,LRI Research Laboratory,Kenitra,Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ibn Tofail University,LRI Research Laboratory,Kenitra,Morocco","institution_ids":["https://openalex.org/I3121676899"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088541702","display_name":"Mohammed Benattou","orcid":"https://orcid.org/0000-0002-9659-5138"},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Mohammed Benattou","raw_affiliation_strings":["Ibn Tofail University,LRI Research Laboratory,Kenitra,Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ibn Tofail University,LRI Research Laboratory,Kenitra,Morocco","institution_ids":["https://openalex.org/I3121676899"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I3121676899"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.5502563,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9122999906539917,"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":0.9122999906539917,"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/T10917","display_name":"Smart Grid Security and Resilience","score":0.011800000444054604,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"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":0.006899999920278788,"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/intrusion-detection-system","display_name":"Intrusion detection system","score":0.7415000200271606},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.7197999954223633},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.659600019454956},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.6557000279426575},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.614799976348877},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.5547999739646912},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.512499988079071},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.47850000858306885}],"concepts":[{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.7415000200271606},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7197999954223633},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7032999992370605},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.659600019454956},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.6557000279426575},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6292999982833862},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.614799976348877},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.5547999739646912},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.512499988079071},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.47850000858306885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39430001378059387},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3578999936580658},{"id":"https://openalex.org/C2779696439","wikidata":"https://www.wikidata.org/wiki/Q7512811","display_name":"Signature (topology)","level":2,"score":0.35580000281333923},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.3499000072479248},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.3465999960899353},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33480000495910645},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32839998602867126},{"id":"https://openalex.org/C137524506","wikidata":"https://www.wikidata.org/wiki/Q2247688","display_name":"Anomaly-based intrusion detection system","level":3,"score":0.311599999666214},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.30169999599456787},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.262800008058548},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wincom65874.2025.11313359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wincom65874.2025.11313359","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 12th International Conference on Wireless Networks and Mobile Communications (WINCOM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2061438946","https://openalex.org/W2081430599","https://openalex.org/W2290883490","https://openalex.org/W2925507233","https://openalex.org/W2978801942","https://openalex.org/W3006034509","https://openalex.org/W3022604549","https://openalex.org/W3045300548","https://openalex.org/W3157871125","https://openalex.org/W3158054680","https://openalex.org/W3195827928","https://openalex.org/W4288043987","https://openalex.org/W4323050995","https://openalex.org/W4384823082","https://openalex.org/W4387654046","https://openalex.org/W4387761032","https://openalex.org/W4391851654","https://openalex.org/W4392120324","https://openalex.org/W4399385997","https://openalex.org/W4401568078","https://openalex.org/W4402263897","https://openalex.org/W4404978949","https://openalex.org/W4405697399"],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,5,10,107],"fast":[2],"growth":[3],"of":[4,7,12,88],"Internet":[6],"Things":[8],"(IoT),":[9],"potential":[11],"cyber":[13],"attacks":[14],"has":[15],"also":[16],"increased.":[17],"Consequently,":[18],"Intrusion":[19],"Detection":[20],"Systems":[21],"(IDS)":[22],"are":[23,33,91],"now":[24],"essential":[25],"for":[26],"protecting":[27],"IoT":[28,58],"systems.":[29],"Traditional":[30],"IDS":[31],"models":[32],"impacted":[34],"by":[35],"large-dimensional,":[36],"imbalanced,":[37],"and":[38,52,75,101,123,134],"noisy":[39],"traffic":[40],"data.":[41],"Feature":[42],"selection":[43,63],"is":[44,80],"a":[45,67,99],"central":[46],"requirement":[47],"to":[48,97,128],"minimize":[49],"computational":[50],"overhead":[51],"maximize":[53],"detection":[54],"precision":[55],"in":[56,82],"low-powered":[57],"devices.":[59],"A":[60],"novel":[61],"feature":[62,86],"method":[64],"based":[65],"on":[66],"joint":[68],"approach":[69],"that":[70,111],"integrates":[71],"Symmetrical":[72],"Uncertainty":[73],"(SU)":[74],"Trace":[76],"Ratio":[77],"Criterion":[78],"(TRC)":[79],"proposed":[81],"this":[83],"paper.":[84],"The":[85],"sets":[87],"dual-ranked":[89],"rankings":[90],"combined":[92],"through":[93],"average":[94],"rank":[95],"aggregation":[96],"produce":[98],"compact":[100],"informative":[102],"subset.":[103],"Experimental":[104],"testing,":[105],"using":[106],"IoTID20":[108],"dataset,":[109],"shows":[110],"combining":[112],"SU":[113],"with":[114],"TRC":[115,133],"significantly":[116],"boosts":[117],"attack":[118],"detection,":[119],"improves":[120],"overall":[121],"accuracy,":[122],"reduces":[124],"false":[125],"positives":[126],"compared":[127],"individual":[129],"algorithms":[130],"such":[131],"as":[132],"SU.":[135]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-12-31T00:00:00"}
