{"id":"https://openalex.org/W4414648257","doi":"https://doi.org/10.1109/vtc2025-spring65109.2025.11174553","title":"V2XFormer: Transformer-Based Anomaly Detection for Vehicle-to-Everything Communication","display_name":"V2XFormer: Transformer-Based Anomaly Detection for Vehicle-to-Everything Communication","publication_year":2025,"publication_date":"2025-06-17","ids":{"openalex":"https://openalex.org/W4414648257","doi":"https://doi.org/10.1109/vtc2025-spring65109.2025.11174553"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2025-spring65109.2025.11174553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2025-spring65109.2025.11174553","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 101st Vehicular Technology Conference (VTC2025-Spring)","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/A5053119935","display_name":"Harindra S. Mavikumbure","orcid":"https://orcid.org/0000-0003-0637-2430"},"institutions":[{"id":"https://openalex.org/I184840846","display_name":"Virginia Commonwealth University","ror":"https://ror.org/02nkdxk79","country_code":"US","type":"education","lineage":["https://openalex.org/I184840846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Harindra S. Mavikumbure","raw_affiliation_strings":["Virginia Commonwealth University,Department of Computer Science,Richmond,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Commonwealth University,Department of Computer Science,Richmond,USA","institution_ids":["https://openalex.org/I184840846"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037613213","display_name":"Victor Cobilean","orcid":"https://orcid.org/0000-0003-0546-7577"},"institutions":[{"id":"https://openalex.org/I184840846","display_name":"Virginia Commonwealth University","ror":"https://ror.org/02nkdxk79","country_code":"US","type":"education","lineage":["https://openalex.org/I184840846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Victor Cobilean","raw_affiliation_strings":["Virginia Commonwealth University,Department of Computer Science,Richmond,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Commonwealth University,Department of Computer Science,Richmond,USA","institution_ids":["https://openalex.org/I184840846"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031428916","display_name":"Chathurika S. Wickramasinghe","orcid":"https://orcid.org/0000-0002-3333-5101"},"institutions":[{"id":"https://openalex.org/I184840846","display_name":"Virginia Commonwealth University","ror":"https://ror.org/02nkdxk79","country_code":"US","type":"education","lineage":["https://openalex.org/I184840846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chathurika S. Wickramasinghe","raw_affiliation_strings":["Virginia Commonwealth University,Department of Computer Science,Richmond,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Commonwealth University,Department of Computer Science,Richmond,USA","institution_ids":["https://openalex.org/I184840846"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111285733","display_name":"Devin Drake","orcid":null},"institutions":[{"id":"https://openalex.org/I184840846","display_name":"Virginia Commonwealth University","ror":"https://ror.org/02nkdxk79","country_code":"US","type":"education","lineage":["https://openalex.org/I184840846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Devin Drake","raw_affiliation_strings":["Virginia Commonwealth University,Department of Computer Science,Richmond,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Commonwealth University,Department of Computer Science,Richmond,USA","institution_ids":["https://openalex.org/I184840846"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032679061","display_name":"Milos Manic","orcid":"https://orcid.org/0000-0003-1484-7678"},"institutions":[{"id":"https://openalex.org/I184840846","display_name":"Virginia Commonwealth University","ror":"https://ror.org/02nkdxk79","country_code":"US","type":"education","lineage":["https://openalex.org/I184840846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Milos Manic","raw_affiliation_strings":["Virginia Commonwealth University,Department of Computer Science,Richmond,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Commonwealth University,Department of Computer Science,Richmond,USA","institution_ids":["https://openalex.org/I184840846"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I184840846"],"apc_list":null,"apc_paid":null,"fwci":1.673,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.85653375,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9958000183105469,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9958000183105469,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9930999875068665,"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":0.9803000092506409,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7720999717712402},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.6644999980926514},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5993000268936157},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.516700029373169},{"id":"https://openalex.org/keywords/denial-of-service-attack","display_name":"Denial-of-service attack","score":0.46619999408721924},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4296000003814697},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.4036000072956085},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.37860000133514404}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7720999717712402},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6678000092506409},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.6644999980926514},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5993000268936157},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.516700029373169},{"id":"https://openalex.org/C38822068","wikidata":"https://www.wikidata.org/wiki/Q131406","display_name":"Denial-of-service attack","level":3,"score":0.46619999408721924},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4607999920845032},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4392000138759613},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4296000003814697},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4244999885559082},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.4036000072956085},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.37860000133514404},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3659999966621399},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.35600000619888306},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3506999909877777},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.34459999203681946},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3212999999523163},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.288100004196167},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2587999999523163},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2554999887943268}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtc2025-spring65109.2025.11174553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2025-spring65109.2025.11174553","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 101st Vehicular Technology Conference (VTC2025-Spring)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W74935252","https://openalex.org/W2908265534","https://openalex.org/W2971089459","https://openalex.org/W2992860123","https://openalex.org/W3038409683","https://openalex.org/W3127143836","https://openalex.org/W3139312002","https://openalex.org/W3197115256","https://openalex.org/W3200339141","https://openalex.org/W4310969694","https://openalex.org/W4313546724","https://openalex.org/W4387544236","https://openalex.org/W4388721324","https://openalex.org/W4388726329","https://openalex.org/W4402570701"],"related_works":[],"abstract_inverted_index":{"The":[0],"Internet":[1],"of":[2,24,41,83,138],"Vehicles":[3],"(IoV)":[4],"has":[5,47],"transformed":[6],"intelligent":[7],"transportation":[8],"systems":[9],"through":[10],"vehicle-to-everything":[11],"(V2X)":[12],"communication,":[13],"improving":[14],"road":[15],"safety":[16],"and":[17,30,65,72,128,169,185],"traffic":[18],"efficiency.":[19],"However,":[20],"the":[21,80,136,139,143,172,176],"dynamic":[22,188],"nature":[23],"vehicular":[25,189],"networks,":[26,105],"with":[27,61,157],"high":[28],"mobility":[29],"shared":[31],"wireless":[32],"resources,":[33],"makes":[34],"them":[35],"vulnerable":[36],"to":[37,69,107,121,187],"attacks":[38],"like":[39],"Denial":[40],"Service":[42],"(DoS).":[43],"Anomaly":[44],"detection":[45,86,99],"(AD)":[46],"proven":[48],"effective":[49],"in":[50,58,74,110,131],"detecting":[51],"such":[52],"threats.":[53],"Yet,":[54],"V2X":[55,111,132,145],"communication":[56],"occurs":[57],"diverse":[59,125],"environments":[60],"varying":[62],"network":[63,126],"coverage":[64],"vehicle":[66],"speeds,":[67],"leading":[68],"domain":[70],"shifts":[71],"variations":[73,130],"feature":[75],"distributions":[76],"that":[77,166],"can":[78],"hinder":[79],"generalization":[81],"performance":[82,137],"traditional":[84],"anomaly":[85,98],"models.":[87],"To":[88],"address":[89],"these":[90],"challenges,":[91],"this":[92],"paper":[93],"presents":[94],"V2XFormer,":[95],"an":[96],"unsupervised":[97,160],"system":[100],"based":[101],"on":[102],"transformer":[103],"neural":[104],"designed":[106],"identify":[108],"anomalies":[109],"communication.":[112,133],"Additionally,":[113],"we":[114],"introduce":[115],"TV2XFormer,":[116],"which":[117],"integrates":[118],"transfer":[119],"learning":[120],"enhance":[122],"adaptability":[123],"across":[124],"conditions":[127],"environmental":[129],"We":[134],"assess":[135],"proposed":[140],"approaches":[141],"using":[142],"VDoS-LRS":[144],"dataset,":[146],"employing":[147],"precision,":[148],"recall,":[149],"and$\\mathbf{F":[150],"1}$score":[151],"metrics.":[152],"A":[153],"comparison":[154],"is":[155],"made":[156],"five":[158],"state-of-the-art":[159],"AD":[161],"algorithms.":[162],"Experimental":[163],"results":[164],"demonstrate":[165],"both":[167],"V2XFormer":[168],"TV2XFormer":[170,181],"outperform":[171],"competing":[173],"algorithms,":[174],"achieving":[175],"highest$\\mathbf{F":[177],"1}$scores":[178],"(1.0).":[179],"Furthermore,":[180],"exhibits":[182],"notable":[183],"robustness":[184],"generalizability":[186],"environments.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}