{"id":"https://openalex.org/W7128812845","doi":"https://doi.org/10.1109/jiot.2026.3664682","title":"Image-Based Dual Defense Strategy for Adversarially Robust IDS in Smart Agriculture","display_name":"Image-Based Dual Defense Strategy for Adversarially Robust IDS in Smart Agriculture","publication_year":2026,"publication_date":"2026-02-13","ids":{"openalex":"https://openalex.org/W7128812845","doi":"https://doi.org/10.1109/jiot.2026.3664682"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2026.3664682","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3664682","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"},"type":"article","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/A5009667420","display_name":"Rafika Saadouni","orcid":null},"institutions":[{"id":"https://openalex.org/I40193446","display_name":"University Ferhat Abbas of Setif","ror":"https://ror.org/02rzqza52","country_code":"DZ","type":"education","lineage":["https://openalex.org/I40193446"]}],"countries":["DZ"],"is_corresponding":true,"raw_author_name":"Rafika Saadouni","raw_affiliation_strings":["LRSD Laboratory, Ferhat Abbas University of Setif 1, Setif, Algeria"],"raw_orcid":"https://orcid.org/0009-0004-9420-7594","affiliations":[{"raw_affiliation_string":"LRSD Laboratory, Ferhat Abbas University of Setif 1, Setif, Algeria","institution_ids":["https://openalex.org/I40193446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057081296","display_name":"Chirihane Gherbi","orcid":"https://orcid.org/0000-0002-0551-3978"},"institutions":[{"id":"https://openalex.org/I40193446","display_name":"University Ferhat Abbas of Setif","ror":"https://ror.org/02rzqza52","country_code":"DZ","type":"education","lineage":["https://openalex.org/I40193446"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Chirihane Gherbi","raw_affiliation_strings":["LRSD Laboratory, Ferhat Abbas University of Setif 1, Setif, Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LRSD Laboratory, Ferhat Abbas University of Setif 1, Setif, Algeria","institution_ids":["https://openalex.org/I40193446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026844364","display_name":"Zibouda Aliouat","orcid":"https://orcid.org/0000-0002-7007-7607"},"institutions":[{"id":"https://openalex.org/I40193446","display_name":"University Ferhat Abbas of Setif","ror":"https://ror.org/02rzqza52","country_code":"DZ","type":"education","lineage":["https://openalex.org/I40193446"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Zibouda Aliouat","raw_affiliation_strings":["LRSD Laboratory, Ferhat Abbas University of Setif 1, Setif, Algeria"],"raw_orcid":"https://orcid.org/0000-0002-7007-7607","affiliations":[{"raw_affiliation_string":"LRSD Laboratory, Ferhat Abbas University of Setif 1, Setif, Algeria","institution_ids":["https://openalex.org/I40193446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005025214","display_name":"Yasmine Harbi","orcid":"https://orcid.org/0000-0001-6731-7895"},"institutions":[{"id":"https://openalex.org/I40193446","display_name":"University Ferhat Abbas of Setif","ror":"https://ror.org/02rzqza52","country_code":"DZ","type":"education","lineage":["https://openalex.org/I40193446"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Yasmine Harbi","raw_affiliation_strings":["LRSD Laboratory, Ferhat Abbas University of Setif 1, Setif, Algeria"],"raw_orcid":"https://orcid.org/0000-0001-6731-7895","affiliations":[{"raw_affiliation_string":"LRSD Laboratory, Ferhat Abbas University of Setif 1, Setif, Algeria","institution_ids":["https://openalex.org/I40193446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038155470","display_name":"Amina Khacha","orcid":"https://orcid.org/0009-0009-3299-8622"},"institutions":[{"id":"https://openalex.org/I40193446","display_name":"University Ferhat Abbas of Setif","ror":"https://ror.org/02rzqza52","country_code":"DZ","type":"education","lineage":["https://openalex.org/I40193446"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Amina Khacha","raw_affiliation_strings":["LRSD Laboratory, Ferhat Abbas University of Setif 1, Setif, Algeria"],"raw_orcid":"https://orcid.org/0009-0009-3299-8622","affiliations":[{"raw_affiliation_string":"LRSD Laboratory, Ferhat Abbas University of Setif 1, Setif, Algeria","institution_ids":["https://openalex.org/I40193446"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073123782","display_name":"Hakim Mabed","orcid":"https://orcid.org/0000-0001-8358-4029"},"institutions":[{"id":"https://openalex.org/I37553959","display_name":"Universit\u00e9 de technologie de belfort-montb\u00e9liard","ror":"https://ror.org/05bn3m307","country_code":"FR","type":"education","lineage":["https://openalex.org/I37553959"]},{"id":"https://openalex.org/I4210118524","display_name":"Universit\u00e9 Bourgogne Franche-Comt\u00e9","ror":"https://ror.org/02dn7x778","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210118524"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Hakim Mabed","raw_affiliation_strings":["DISC/FEMTO-ST, University Bourgogne Franche-Comté, Montbeliard, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DISC/FEMTO-ST, University Bourgogne Franche-Comté, Montbeliard, France","institution_ids":["https://openalex.org/I4210118524","https://openalex.org/I37553959"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5009667420"],"corresponding_institution_ids":["https://openalex.org/I40193446"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28148354,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"9","first_page":"19443","last_page":"19457"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.30559998750686646,"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"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.30559998750686646,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.16130000352859497,"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":0.1574999988079071,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5060999989509583},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.47119998931884766},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.4595000147819519},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.4115999937057495},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3700000047683716},{"id":"https://openalex.org/keywords/resilience","display_name":"Resilience (materials science)","score":0.36890000104904175},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.3610000014305115}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8288000226020813},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5060999989509583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4740000069141388},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.47119998931884766},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.4595000147819519},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4133000075817108},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.4115999937057495},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.374099999666214},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3700000047683716},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3610000014305115},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3560999929904938},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.34279999136924744},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3262999951839447},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.3181999921798706},{"id":"https://openalex.org/C124119293","wikidata":"https://www.wikidata.org/wiki/Q6046081","display_name":"Interdiction","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.2930000126361847},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.2671000063419342}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2026.3664682","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3664682","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7771518230438232,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[{"id":"https://openalex.org/G2036951780","display_name":null,"funder_award_id":"PHC 24MDU109","funder_id":"https://openalex.org/F4320323942","funder_display_name":"Campus France"}],"funders":[{"id":"https://openalex.org/F4320323942","display_name":"Campus France","ror":"https://ror.org/04wtce741"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,75,126,144],"integration":[1],"of":[2,4,44,162,177,193,230],"Internet":[3],"Things":[5],"(IoT)":[6],"technologies":[7],"into":[8,80],"smart":[9,72,249],"agriculture":[10,73,250],"has":[11],"significantly":[12],"enhanced":[13],"automation,":[14],"monitoring,":[15],"and":[16,25,33,82,95],"productivity.":[17],"However,":[18],"these":[19,62],"systems":[20],"introduce":[21],"critical":[22],"cybersecurity":[23],"vulnerabilities":[24],"generate":[26],"heterogeneous":[27],"data,":[28,47],"including":[29],"structured":[30],"network":[31,78],"traffic":[32,79,137],"image-based":[34,69],"inputs.":[35],"This":[36],"requires":[37],"an":[38,191],"intrusion":[39],"detection":[40,58],"system":[41,76,187,223],"(IDS)":[42],"capable":[43],"handling":[45],"multimodal":[46,240],"particularly":[48],"since":[49],"adversarial":[50,124,142,219,254],"attacks":[51],"can":[52],"manipulate":[53],"inputs":[54],"to":[55,120,200],"evade":[56],"traditional":[57],"models.":[59],"To":[60,197],"address":[61],"challenges,":[63],"this":[64],"paper":[65],"proposes":[66],"a":[67,96,104,110,227,243],"novel":[68],"IDS":[70,145,205,241],"for":[71,85,92,99,248],"environments.":[74],"transforms":[77],"images":[81,212],"employs":[83],"VGG16":[84],"feature":[86,93],"extraction,":[87],"Binary":[88],"Greylag":[89],"Goose":[90],"Optimization":[91],"selection,":[94],"random":[97],"forest":[98],"classification.":[100],"It":[101],"further":[102],"integrates":[103],"dual":[105,158],"defense":[106,159],"strategy":[107],"that":[108,237],"combines":[109],"Convolutional":[111],"Autoencoder":[112],"Denoising":[113],"(CAED)":[114],"module":[115],"with":[116,174],"Adversarial":[117],"Training":[118],"(AT)":[119],"improve":[121],"robustness":[122],"against":[123],"perturbations.":[125],"proposed":[127,239],"solution":[128,247],"is":[129,206],"evaluated":[130],"on":[131],"the":[132,157,186,204,214,222,238],"CICIoT2023":[133],"dataset":[134],"in":[135],"eight":[136],"classes":[138],"under":[139,182],"three":[140],"white-box":[141],"attacks.":[143],"demonstrates":[146],"strong":[147,183],"resilience":[148],"across":[149],"all":[150],"perturbation":[151],"levels.":[152],"For":[153],"weak":[154],"perturbations":[155,168,184],"(\u03b5=0.01),":[156],"achieves":[160],"accuracies":[161,176],"at":[163,178,194,231],"least":[164,179,195,232],"99.46%.":[165],"Under":[166,217],"moderate":[167],"(\u03b5=0.1),":[169],"it":[170],"maintains":[171,224],"high":[172],"performance":[173],"macro-averaged":[175,228],"99.39%.":[180],"Even":[181],"(\u03b5=0.3),":[185,221],"remains":[188],"robust,":[189],"attaining":[190],"accuracy":[192,229],"96.50%.":[196],"assess":[198],"generalization":[199],"real":[201],"agricultural":[202,215],"settings,":[203],"also":[207],"tested":[208],"using":[209],"native":[210],"crop":[211],"from":[213],"dataset.":[216],"severe":[218],"distortion":[220],"robustness,":[225],"achieving":[226],"96.71%.":[233],"These":[234],"results":[235],"confirm":[236],"provides":[242],"resilient,":[244],"adaptive":[245],"security":[246],"networks":[251],"facing":[252],"advanced":[253],"threats.":[255]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2026-02-14T00:00:00"}