{"id":"https://openalex.org/W4410226682","doi":"https://doi.org/10.1109/jiot.2025.3568503","title":"Modeling Realistic Adversarial Traffic Against Deep-Learning-Based Intrusion Detection System in Industrial IoT","display_name":"Modeling Realistic Adversarial Traffic Against Deep-Learning-Based Intrusion Detection System in Industrial IoT","publication_year":2025,"publication_date":"2025-05-09","ids":{"openalex":"https://openalex.org/W4410226682","doi":"https://doi.org/10.1109/jiot.2025.3568503"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2025.3568503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3568503","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/A5079875566","display_name":"Wei Yao","orcid":"https://orcid.org/0000-0003-3278-3049"},"institutions":[{"id":"https://openalex.org/I2799850029","display_name":"Dongguan University of Technology","ror":"https://ror.org/01m8p7q42","country_code":"CN","type":"education","lineage":["https://openalex.org/I2799850029"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Yao","raw_affiliation_strings":["School of Electrical Engineering and Intelligentization, Dongguan University of Technology, Dongguan, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Intelligentization, Dongguan University of Technology, Dongguan, China","institution_ids":["https://openalex.org/I2799850029"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102864216","display_name":"Haixia Peng","orcid":"https://orcid.org/0000-0001-7206-4706"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haixia Peng","raw_affiliation_strings":["School of Information and Communications Engineering, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communications Engineering, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101693651","display_name":"Qihao Li","orcid":"https://orcid.org/0000-0002-2602-142X"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qihao Li","raw_affiliation_strings":["College of Communication Engineering, Jilin University, Changchun, China"],"affiliations":[{"raw_affiliation_string":"College of Communication Engineering, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100773343","display_name":"Xuemin Shen","orcid":"https://orcid.org/0000-0002-4140-287X"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xuemin Shen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada","Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5079875566"],"corresponding_institution_ids":["https://openalex.org/I2799850029"],"apc_list":null,"apc_paid":null,"fwci":4.2386,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.93729136,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"12","issue":"15","first_page":"29540","last_page":"29554"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9865000247955322,"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"}},"topics":[{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9865000247955322,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9858999848365784,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9703999757766724,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/adversarial-system","display_name":"Adversarial system","score":0.8408731818199158},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8000093102455139},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.6801294684410095},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5733060836791992},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5215744376182556},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.43858253955841064},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.38641178607940674},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3595220446586609}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8408731818199158},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8000093102455139},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.6801294684410095},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5733060836791992},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5215744376182556},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.43858253955841064},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.38641178607940674},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3595220446586609},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2025.3568503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3568503","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":[],"awards":[{"id":"https://openalex.org/G262863636","display_name":null,"funder_award_id":"62301411","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5542935369","display_name":null,"funder_award_id":"221110333","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5956518121","display_name":null,"funder_award_id":"20231900700022","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W2296452361","https://openalex.org/W2802061317","https://openalex.org/W2802196017","https://openalex.org/W2889836475","https://openalex.org/W2905526464","https://openalex.org/W2911505293","https://openalex.org/W2925211503","https://openalex.org/W2944643572","https://openalex.org/W2963197901","https://openalex.org/W2963857521","https://openalex.org/W2969468102","https://openalex.org/W2991408690","https://openalex.org/W2995671208","https://openalex.org/W3009195050","https://openalex.org/W3021740526","https://openalex.org/W3102844060","https://openalex.org/W3134622107","https://openalex.org/W3164964481","https://openalex.org/W3165205057","https://openalex.org/W3200583622","https://openalex.org/W4206331418","https://openalex.org/W4206450891","https://openalex.org/W4283382503","https://openalex.org/W4296962561","https://openalex.org/W4313591247","https://openalex.org/W4364361361","https://openalex.org/W4382281941","https://openalex.org/W4386695618","https://openalex.org/W4387010514","https://openalex.org/W4387817744","https://openalex.org/W4388923662","https://openalex.org/W4391689920","https://openalex.org/W4391989542","https://openalex.org/W4394851017","https://openalex.org/W4399352978","https://openalex.org/W6631843488","https://openalex.org/W6637162671","https://openalex.org/W6640425456","https://openalex.org/W6731927902","https://openalex.org/W6756678122","https://openalex.org/W6761377332","https://openalex.org/W6774681163","https://openalex.org/W6810434748"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W4285226279","https://openalex.org/W4380075502"],"abstract_inverted_index":{"The":[0],"widely":[1],"deployment":[2],"of":[3,171,184],"infrastructure":[4],"and":[5,122,156],"wireless":[6],"interfaces":[7],"increases":[8],"industrial":[9],"IoT":[10],"(IIoT)":[11],"vulnerability":[12],"to":[13,39,48,89,110,137],"network":[14,21],"intrusions,":[15],"highlighting":[16],"the":[17,92,128,154,177,182,185],"requirements":[18],"for":[19,34,63],"robust":[20],"intrusion":[22],"detection":[23],"systems":[24],"(NIDSs).":[25],"Although":[26],"deep":[27],"learning":[28,115],"(DL)":[29],"provides":[30],"a":[31,56,84,105,166],"promising":[32],"solution":[33],"NIDSs,":[35],"it":[36],"remains":[37],"susceptible":[38],"adversarial":[40,58,108,112,143,186],"attacks":[41],"as":[42],"minor":[43],"input":[44],"perturbations":[45],"can":[46,95,164],"lead":[47],"major":[49],"misclassifications.":[50],"In":[51],"this":[52],"paper,":[53],"we":[54,82],"propose":[55,104],"packet-level":[57,106],"traffic":[59,87,94,113],"generation":[60],"(PATG)":[61],"approach":[62],"attacking":[64],"NIDSs":[65,152],"in":[66,119,153],"IIoT,":[67],"which":[68,126],"not":[69],"only":[70],"aligns":[71],"with":[72,173],"domain":[73],"constraints":[74],"but":[75],"also":[76],"evades":[77],"various":[78],"DL-based":[79,129,151],"NIDSs.":[80,130],"Particularly,":[81],"introduce":[83],"reversible":[85],"abstract":[86],"representation":[88],"ensure":[90],"that":[91,162],"original":[93],"be":[96],"effectively":[97],"modified":[98],"while":[99,176],"preserving":[100],"its":[101],"functionality.":[102],"We":[103,131,145],"generative":[107],"networks":[109],"craft":[111],"by":[114],"benign":[116],"data":[117],"distribution":[118],"feature":[120],"space":[121],"simulating":[123],"evasion":[124,168],"behaviors,":[125],"escapes":[127],"further":[132],"design":[133],"two":[134],"defense":[135,178],"schemes":[136],"enhance":[138],"system":[139],"resilience":[140],"against":[141],"proposed":[142],"attacks.":[144,187],"evaluate":[146],"PATG":[147,163],"on":[148],"nine":[149],"state-of-the-art":[150],"Kitsune":[155],"CICIoT23":[157],"datasets.":[158],"Experimental":[159],"results":[160],"demonstrate":[161],"achieve":[165],"maximum":[167],"increase":[169],"rate":[170],"99%":[172],"cost-effective":[174],"execution,":[175],"methods":[179],"significantly":[180],"mitigate":[181],"impact":[183]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
