{"id":"https://openalex.org/W4416513627","doi":"https://doi.org/10.1109/tifs.2025.3636019","title":"Detecting Masquerade Attacks in Controller Area Networks Using Graph Machine Learning","display_name":"Detecting Masquerade Attacks in Controller Area Networks Using Graph Machine Learning","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416513627","doi":"https://doi.org/10.1109/tifs.2025.3636019"},"language":null,"primary_location":{"id":"doi:10.1109/tifs.2025.3636019","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tifs.2025.3636019","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/tifs.2025.3636019","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062587761","display_name":"William Marfo","orcid":"https://orcid.org/0009-0003-0631-2750"},"institutions":[{"id":"https://openalex.org/I164936912","display_name":"The University of Texas at El Paso","ror":"https://ror.org/04d5vba33","country_code":"US","type":"education","lineage":["https://openalex.org/I164936912"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William Marfo","raw_affiliation_strings":["Department of Computer Science, The University of Texas at El Paso, El Paso, TX, USA","Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA"],"raw_orcid":"https://orcid.org/0009-0003-0631-2750","affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Texas at El Paso, El Paso, TX, USA","institution_ids":["https://openalex.org/I164936912"]},{"raw_affiliation_string":"Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA","institution_ids":["https://openalex.org/I164936912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025254339","display_name":"Pablo Moriano","orcid":"https://orcid.org/0000-0002-1822-8885"},"institutions":[{"id":"https://openalex.org/I1289243028","display_name":"Oak Ridge National Laboratory","ror":"https://ror.org/01qz5mb56","country_code":"US","type":"facility","lineage":["https://openalex.org/I1289243028","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I4210159294"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pablo Moriano","raw_affiliation_strings":["Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA"],"raw_orcid":"https://orcid.org/0000-0002-1822-8885","affiliations":[{"raw_affiliation_string":"Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA","institution_ids":["https://openalex.org/I1289243028"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065745202","display_name":"Deepak K. Tosh","orcid":"https://orcid.org/0000-0001-8492-1066"},"institutions":[{"id":"https://openalex.org/I164936912","display_name":"The University of Texas at El Paso","ror":"https://ror.org/04d5vba33","country_code":"US","type":"education","lineage":["https://openalex.org/I164936912"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deepak K. Tosh","raw_affiliation_strings":["Department of Computer Science, The University of Texas at El Paso, El Paso, TX, USA","Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA"],"raw_orcid":"https://orcid.org/0000-0001-8492-1066","affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Texas at El Paso, El Paso, TX, USA","institution_ids":["https://openalex.org/I164936912"]},{"raw_affiliation_string":"Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA","institution_ids":["https://openalex.org/I164936912"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041037945","display_name":"Shirley Moore","orcid":"https://orcid.org/0009-0009-1351-2797"},"institutions":[{"id":"https://openalex.org/I164936912","display_name":"The University of Texas at El Paso","ror":"https://ror.org/04d5vba33","country_code":"US","type":"education","lineage":["https://openalex.org/I164936912"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shirley V. Moore","raw_affiliation_strings":["Department of Computer Science, The University of Texas at El Paso, El Paso, TX, USA","Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Texas at El Paso, El Paso, TX, USA","institution_ids":["https://openalex.org/I164936912"]},{"raw_affiliation_string":"Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA","institution_ids":["https://openalex.org/I164936912"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9173,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.74943487,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"20","issue":null,"first_page":"13127","last_page":"13142"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.5680000185966492,"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"}},"topics":[{"id":"https://openalex.org/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.5680000185966492,"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/T10917","display_name":"Smart Grid Security and Resilience","score":0.19030000269412994,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.036400001496076584,"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":0.6507999897003174},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6107000112533569},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4226999878883362},{"id":"https://openalex.org/keywords/denial-of-service-attack","display_name":"Denial-of-service attack","score":0.3772999942302704},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.36480000615119934},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.3492000102996826},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.3199999928474426}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8707000017166138},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.6507999897003174},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6107000112533569},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5181000232696533},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49779999256134033},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4226999878883362},{"id":"https://openalex.org/C38822068","wikidata":"https://www.wikidata.org/wiki/Q131406","display_name":"Denial-of-service attack","level":3,"score":0.3772999942302704},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.36480000615119934},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35679998993873596},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.3492000102996826},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.2957000136375427},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2542000114917755},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.251800000667572},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2025.3636019","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tifs.2025.3636019","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/tifs.2025.3636019","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tifs.2025.3636019","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G203625172","display_name":null,"funder_award_id":"DE--AC05--00OR22725","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G8033190234","display_name":"DE-FE0032089, NEW AWARD, 5G INTEGRATED EDGE COMPUTING PLATFORM FOR EFFICIENT COMPONENT MONITORING IN COAL-FIRED POWER PLANTS","funder_award_id":"DEFE0032089","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"}],"funders":[{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320338287","display_name":"Oak Ridge National Laboratory","ror":"https://ror.org/01qz5mb56"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1536719639","https://openalex.org/W2148143831","https://openalex.org/W2153624566","https://openalex.org/W2158698691","https://openalex.org/W2295598076","https://openalex.org/W2506734067","https://openalex.org/W2739928414","https://openalex.org/W2897929592","https://openalex.org/W2907492528","https://openalex.org/W2948384692","https://openalex.org/W2955396105","https://openalex.org/W2962756421","https://openalex.org/W2979202956","https://openalex.org/W3007940922","https://openalex.org/W3014212182","https://openalex.org/W3017478614","https://openalex.org/W3081862970","https://openalex.org/W3091724539","https://openalex.org/W3169251294","https://openalex.org/W3175018059","https://openalex.org/W3189306419","https://openalex.org/W3195279647","https://openalex.org/W3205578151","https://openalex.org/W3217196210","https://openalex.org/W4220842203","https://openalex.org/W4221052500","https://openalex.org/W4281397359","https://openalex.org/W4284881100","https://openalex.org/W4320002750","https://openalex.org/W4322625299","https://openalex.org/W4323966584","https://openalex.org/W4362654523","https://openalex.org/W4366377785","https://openalex.org/W4381389897","https://openalex.org/W4385656664","https://openalex.org/W4386450116","https://openalex.org/W4389794090","https://openalex.org/W4391097714","https://openalex.org/W4392693989","https://openalex.org/W4393150251","https://openalex.org/W4396867449","https://openalex.org/W4400762160","https://openalex.org/W4407272598","https://openalex.org/W4408324953"],"related_works":[],"abstract_inverted_index":{"Modern":[0],"vehicles":[1],"rely":[2],"on":[3,180],"a":[4,84,165,203],"myriad":[5],"of":[6,105,120,170,187,198],"electronic":[7],"control":[8],"units":[9],"(ECUs)":[10],"interconnected":[11],"via":[12],"controller":[13],"area":[14],"networks":[15],"(CANs)":[16],"for":[17,87],"critical":[18],"operations.":[19],"Despite":[20],"their":[21,75],"ubiquitous":[22],"use":[23],"and":[24,58,136,167,176,215],"reliability,":[25],"CANs":[26],"are":[27],"susceptible":[28],"to":[29,68,74,157,202],"sophisticated":[30],"cyberattacks,":[31],"particularly":[32],"masquerade":[33,89,121,199],"attacks,":[34],"which":[35],"inject":[36],"false":[37],"data":[38],"that":[39,102,125,205],"mimic":[40],"legitimate":[41],"messages":[42],"at":[43],"the":[44,92,103,118,181,185,195],"expected":[45],"frequency.":[46],"These":[47],"attacks":[48,90,200],"pose":[49],"severe":[50],"risks":[51],"such":[52],"as":[53,131,210],"unintended":[54],"acceleration,":[55],"brake":[56],"deactivation,":[57],"rogue":[59],"steering.":[60],"Traditional":[61],"intrusion":[62],"detection":[63,119,150,196],"systems":[64],"(IDS)":[65],"often":[66],"struggle":[67],"detect":[69],"these":[70],"subtle":[71],"intrusions":[72],"due":[73],"seamless":[76],"integration":[77,104],"into":[78],"normal":[79],"traffic.":[80],"This":[81],"paper":[82],"introduces":[83],"novel":[85],"framework":[86],"detecting":[88],"in":[91,194],"CAN":[93,115,128,171],"bus":[94,129],"using":[95,158],"graph":[96,107],"machine":[97],"learning":[98],"(ML).":[99],"We":[100,123],"hypothesize":[101],"shallow":[106],"embeddings":[108],"with":[109,140],"time":[110,145],"series":[111],"features":[112,160,208],"derived":[113],"from":[114,144],"frames":[116,130],"enhances":[117],"attacks.":[122],"show":[124],"by":[126,212],"representing":[127],"message":[132],"sequence":[133],"graphs":[134],"(MSGs)":[135],"enriching":[137],"each":[138],"node":[139],"contextual":[141],"statistical":[142],"attributes":[143],"series,":[146],"we":[147],"can":[148],"enhance":[149],"capabilities":[151],"across":[152],"various":[153],"attack":[154],"patterns":[155],"compared":[156,201],"graph-based":[159,207],"only.":[161],"Our":[162],"method":[163],"ensures":[164],"comprehensive":[166],"dynamic":[168],"analysis":[169],"frame":[172],"interactions,":[173],"improving":[174],"robustness":[175],"efficiency.":[177],"Extensive":[178],"experiments":[179],"ROAD":[182],"dataset":[183],"validate":[184],"effectiveness":[186],"our":[188],"approach,":[189],"demonstrating":[190],"statistically":[191],"significant":[192],"improvements":[193],"rates":[197],"baseline":[204],"uses":[206],"only":[209],"confirmed":[211],"Mann-Whitney":[213],"U":[214],"Kolmogorov-Smirnov":[216],"tests":[217],"(p<":[218],"0.05).":[219]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-11-23T00:00:00"}