{"id":"https://openalex.org/W4411446825","doi":"https://doi.org/10.1109/tvt.2025.3581456","title":"Enhancing Machine Learning-Based IDS for Vehicular Networks by Addressing Adversarial Attacks","display_name":"Enhancing Machine Learning-Based IDS for Vehicular Networks by Addressing Adversarial Attacks","publication_year":2025,"publication_date":"2025-06-19","ids":{"openalex":"https://openalex.org/W4411446825","doi":"https://doi.org/10.1109/tvt.2025.3581456"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2025.3581456","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2025.3581456","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Transactions on Vehicular Technology","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":null,"display_name":"Pegah Mansourian","orcid":"https://orcid.org/0000-0002-0402-1242"},"institutions":[{"id":"https://openalex.org/I74413500","display_name":"University of Windsor","ror":"https://ror.org/01gw3d370","country_code":"CA","type":"education","lineage":["https://openalex.org/I74413500"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Pegah Mansourian","raw_affiliation_strings":["University of Windsor, Windsor, ON, Canada"],"affiliations":[{"raw_affiliation_string":"University of Windsor, Windsor, ON, Canada","institution_ids":["https://openalex.org/I74413500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100404886","display_name":"Ning Zhang","orcid":"https://orcid.org/0000-0002-8781-4925"},"institutions":[{"id":"https://openalex.org/I74413500","display_name":"University of Windsor","ror":"https://ror.org/01gw3d370","country_code":"CA","type":"education","lineage":["https://openalex.org/I74413500"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ning Zhang","raw_affiliation_strings":["University of Windsor, Windsor, ON, Canada"],"affiliations":[{"raw_affiliation_string":"University of Windsor, Windsor, ON, Canada","institution_ids":["https://openalex.org/I74413500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055035963","display_name":"Arunita Jaekel","orcid":"https://orcid.org/0000-0001-6836-9670"},"institutions":[{"id":"https://openalex.org/I74413500","display_name":"University of Windsor","ror":"https://ror.org/01gw3d370","country_code":"CA","type":"education","lineage":["https://openalex.org/I74413500"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Arunita Jaekel","raw_affiliation_strings":["University of Windsor, Windsor, ON, Canada"],"affiliations":[{"raw_affiliation_string":"University of Windsor, Windsor, ON, Canada","institution_ids":["https://openalex.org/I74413500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104633549","display_name":"Tim Allsopp","orcid":null},"institutions":[{"id":"https://openalex.org/I2800934870","display_name":"Telus (Canada)","ror":"https://ror.org/040vbkv27","country_code":"CA","type":"company","lineage":["https://openalex.org/I2800934870"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Tim Allsopp","raw_affiliation_strings":["Telus Communications Inc., Vancouver, BC, Canada"],"affiliations":[{"raw_affiliation_string":"Telus Communications Inc., Vancouver, BC, Canada","institution_ids":["https://openalex.org/I2800934870"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74413500"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18049933,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"74","issue":"11","first_page":"16935","last_page":"16946"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9972000122070312,"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":0.9972000122070312,"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/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9915000200271606,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9771000146865845,"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/adversarial-system","display_name":"Adversarial system","score":0.7720649242401123},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6270595192909241},{"id":"https://openalex.org/keywords/adversarial-machine-learning","display_name":"Adversarial machine learning","score":0.4991593360900879},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4907182455062866},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.43491053581237793},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.4297051429748535},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3683464527130127}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7720649242401123},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6270595192909241},{"id":"https://openalex.org/C2778403875","wikidata":"https://www.wikidata.org/wiki/Q20312394","display_name":"Adversarial machine learning","level":3,"score":0.4991593360900879},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4907182455062866},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.43491053581237793},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4297051429748535},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3683464527130127}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2025.3581456","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2025.3581456","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Transactions on Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2180612164","https://openalex.org/W2923778952","https://openalex.org/W2930249865","https://openalex.org/W2962061624","https://openalex.org/W2963542245","https://openalex.org/W2964314709","https://openalex.org/W2968455244","https://openalex.org/W3006008420","https://openalex.org/W3086579950","https://openalex.org/W3133233862","https://openalex.org/W3148608995","https://openalex.org/W3164321464","https://openalex.org/W3198511875","https://openalex.org/W4226135488","https://openalex.org/W4286005659","https://openalex.org/W4313591247","https://openalex.org/W4319083552","https://openalex.org/W4382203413","https://openalex.org/W4383738214","https://openalex.org/W4391791340"],"related_works":["https://openalex.org/W3048732067","https://openalex.org/W4383468834","https://openalex.org/W4283221438","https://openalex.org/W2900159906","https://openalex.org/W4384648009","https://openalex.org/W4287828318","https://openalex.org/W2406556600","https://openalex.org/W4380352238","https://openalex.org/W3126470649","https://openalex.org/W2930249865"],"abstract_inverted_index":{"In":[0],"Vehicular":[1,149],"Ad":[2],"Hoc":[3],"Networks":[4],"(VANET),":[5],"Intrusion":[6],"Detection":[7],"Systems":[8],"(IDS)":[9],"are":[10,22,62],"pivotal":[11],"in":[12,140],"ensuring":[13],"secure":[14],"communication":[15],"among":[16],"vehicles":[17],"and":[18,75,100,120,158,177,202],"infrastructure.":[19],"These":[20],"systems":[21],"tasked":[23],"with":[24,132],"identifying":[25],"abnormal":[26],"behavior,":[27],"including":[28],"malicious":[29],"attacks":[30],"or":[31],"unauthorized":[32],"access,":[33],"within":[34,92],"the":[35,40,88,126,169,193],"dynamic":[36],"VANET":[37],"environment.":[38],"However,":[39],"advent":[41],"of":[42,90,128,136,153,163,195],"Adversarial":[43],"Examples":[44],"(AE)-inputs":[45],"crafted":[46],"to":[47,55,65,72,86,181,191,200],"deceive":[48],"machine":[49],"learning":[50],"models-has":[51],"introduced":[52],"new":[53],"challenges":[54],"IDS":[56,70,91,150],"effectiveness.":[57],"To":[58],"address":[59],"this,":[60],"researchers":[61],"exploring":[63],"methods":[64],"integrate":[66],"adversarial":[67,95,98,130,164,183],"examples":[68,99,131],"into":[69],"frameworks":[71],"enhance":[73,192],"security":[74,194],"resilience":[76],"against":[77,94,112],"attacks.":[78,96],"This":[79],"paper":[80],"presents":[81],"a":[82,102,141,188],"comprehensive":[83],"framework":[84,186],"designed":[85],"bolster":[87],"robustness":[89],"VANETs":[93],"Leveraging":[97],"employing":[101],"rigorous":[103],"verification":[104],"process,":[105],"our":[106],"methodology":[107],"systematically":[108],"fortifies":[109],"classification":[110],"models":[111],"potential":[113],"threats.":[114],"Through":[115],"iterative":[116],"data":[117],"generation,":[118],"verification,":[119],"model":[121],"adjustment":[122],"stages,":[123],"we":[124],"ensure":[125],"creation":[127],"verified":[129],"an":[133],"optimal":[134],"level":[135],"added":[137],"perturbation,":[138],"culminating":[139],"final":[142],"robust":[143],"model,":[144],"called":[145],"<bold":[146],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[147],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Adversarially-Fortified":[148],"(AFV_IDS)</b>,":[151],"capable":[152],"confidently":[154],"discerning":[155],"between":[156],"normal":[157],"attack":[159],"messages.":[160],"The":[161],"integration":[162],"training":[165],"techniques":[166],"further":[167],"enhances":[168],"model's":[170],"resilience,":[171],"addressing":[172],"previously":[173],"unseen":[174],"blind":[175],"spots":[176],"adjusting":[178],"decision":[179],"boundaries":[180],"accommodate":[182],"instances.":[184],"Our":[185],"offers":[187],"holistic":[189],"solution":[190],"vehicular":[196],"networks,":[197],"thereby":[198],"contributing":[199],"safer":[201],"more":[203],"reliable":[204],"transportation":[205],"systems.":[206]},"counts_by_year":[],"updated_date":"2025-11-23T23:15:26.331081","created_date":"2025-10-10T00:00:00"}
