{"id":"https://openalex.org/W2989658861","doi":"https://doi.org/10.1109/itsc.2019.8917354","title":"Automatic Driver Identification from In-Vehicle Network Logs","display_name":"Automatic Driver Identification from In-Vehicle Network Logs","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2989658861","doi":"https://doi.org/10.1109/itsc.2019.8917354","mag":"2989658861"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2019.8917354","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2019.8917354","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1911.09508","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022261435","display_name":"Mina Remeli","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mina Remeli","raw_affiliation_strings":["CrySyS Lab, BME-HIT, Hungary","CrySyS Lab, BME-HIT,Hungary"],"affiliations":[{"raw_affiliation_string":"CrySyS Lab, BME-HIT, Hungary","institution_ids":[]},{"raw_affiliation_string":"CrySyS Lab, BME-HIT,Hungary","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013637193","display_name":"Szilvia Lesty\u00e1n","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Szilvia Lestyan","raw_affiliation_strings":["CrySyS Lab, BME-HIT, Hungary","CrySyS Lab, BME-HIT,Hungary"],"affiliations":[{"raw_affiliation_string":"CrySyS Lab, BME-HIT, Hungary","institution_ids":[]},{"raw_affiliation_string":"CrySyS Lab, BME-HIT,Hungary","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047386875","display_name":"Gergely \u00c1cs","orcid":"https://orcid.org/0000-0003-4437-0110"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gergely Acs","raw_affiliation_strings":["CrySyS Lab, BME-HIT, Hungary","CrySyS Lab, BME-HIT,Hungary"],"affiliations":[{"raw_affiliation_string":"CrySyS Lab, BME-HIT, Hungary","institution_ids":[]},{"raw_affiliation_string":"CrySyS Lab, BME-HIT,Hungary","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002026615","display_name":"Gergely Bicz\u00f3k","orcid":"https://orcid.org/0000-0002-3891-3855"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gergely Biczok","raw_affiliation_strings":["CrySyS Lab, BME-HIT, Hungary","CrySyS Lab, BME-HIT,Hungary"],"affiliations":[{"raw_affiliation_string":"CrySyS Lab, BME-HIT, Hungary","institution_ids":[]},{"raw_affiliation_string":"CrySyS Lab, BME-HIT,Hungary","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5022261435"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16616338,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1150","last_page":"1157"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9987999796867371,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9976999759674072,"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/computer-science","display_name":"Computer science","score":0.6928737759590149},{"id":"https://openalex.org/keywords/profiling","display_name":"Profiling (computer programming)","score":0.5911415815353394},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5222897529602051},{"id":"https://openalex.org/keywords/brake","display_name":"Brake","score":0.48129358887672424},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.43620336055755615},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.42269080877304077},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25201064348220825},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.2276969850063324},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.18146160244941711}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6928737759590149},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.5911415815353394},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5222897529602051},{"id":"https://openalex.org/C2780999251","wikidata":"https://www.wikidata.org/wiki/Q17022503","display_name":"Brake","level":2,"score":0.48129358887672424},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.43620336055755615},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.42269080877304077},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25201064348220825},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.2276969850063324},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.18146160244941711},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/itsc.2019.8917354","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2019.8917354","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1911.09508","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.09508","pdf_url":"https://arxiv.org/pdf/1911.09508","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2989658861","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1911.09508v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1911.09508","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1911.09508","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1911.09508","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.09508","pdf_url":"https://arxiv.org/pdf/1911.09508","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2989658861.pdf","grobid_xml":"https://content.openalex.org/works/W2989658861.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W119403003","https://openalex.org/W1463623766","https://openalex.org/W1584662422","https://openalex.org/W1606251440","https://openalex.org/W1821462560","https://openalex.org/W1836465849","https://openalex.org/W1965578057","https://openalex.org/W1972441921","https://openalex.org/W2064675550","https://openalex.org/W2068997453","https://openalex.org/W2124776405","https://openalex.org/W2154579312","https://openalex.org/W2194775991","https://openalex.org/W2201092681","https://openalex.org/W2286343943","https://openalex.org/W2306394264","https://openalex.org/W2330720123","https://openalex.org/W2551393996","https://openalex.org/W2553915786","https://openalex.org/W2555077524","https://openalex.org/W2604623014","https://openalex.org/W2761751533","https://openalex.org/W2892035503","https://openalex.org/W2911978475","https://openalex.org/W2916772464","https://openalex.org/W2962826786","https://openalex.org/W2963535483","https://openalex.org/W2963833878","https://openalex.org/W2964092202","https://openalex.org/W6636171097","https://openalex.org/W6638523607","https://openalex.org/W6638667902","https://openalex.org/W6682751323","https://openalex.org/W6687630728","https://openalex.org/W6698169118","https://openalex.org/W6744483486","https://openalex.org/W6753422357","https://openalex.org/W6754957482"],"related_works":["https://openalex.org/W2989755930","https://openalex.org/W572858067","https://openalex.org/W2803333205","https://openalex.org/W2907398461","https://openalex.org/W2990645718","https://openalex.org/W2071628512","https://openalex.org/W2886897536","https://openalex.org/W2988306923","https://openalex.org/W2141884302","https://openalex.org/W3189448978","https://openalex.org/W2951450524","https://openalex.org/W643199873","https://openalex.org/W2774386491","https://openalex.org/W58220988","https://openalex.org/W2587996560","https://openalex.org/W2556886968","https://openalex.org/W3158951035","https://openalex.org/W2613874925","https://openalex.org/W2844984323","https://openalex.org/W2792091003"],"abstract_inverted_index":{"Data":[0],"generated":[1],"by":[2,53],"cars":[3,11],"is":[4,47,147],"growing":[5],"at":[6],"an":[7,184],"unprecedented":[8],"scale.":[9],"As":[10],"gradually":[12],"become":[13],"part":[14],"of":[15,18,27,34,37,45,59,78,99,144,167,186],"the":[16,25,32,35,41,57,76,82,88,97,100,109,121,142,157],"Internet":[17],"Things":[19],"(IoT)":[20],"ecosystem,":[21],"several":[22,70],"stakeholders":[23],"discover":[24],"value":[26],"in-vehicle":[28,83],"network":[29,84],"logs":[30],"containing":[31],"measurements":[33],"multitude":[36],"sensors":[38],"deployed":[39],"within":[40,136],"car.":[42],"This":[43],"wealth":[44],"data":[46,85],"also":[48],"expected":[49],"to":[50,64],"be":[51,176],"exploitable":[52],"third":[54],"parties":[55],"for":[56],"purpose":[58],"profiling":[60],"drivers":[61,169,182],"in":[62],"order":[63],"provide":[65],"personalized,":[66],"valueadded":[67],"services.":[68],"Although":[69],"prior":[71],"works":[72],"have":[73],"successfully":[74],"demonstrated":[75],"feasibility":[77],"driver":[79,101,145,174],"re-identification":[80],"using":[81],"captured":[86],"on":[87,164],"vehicle's":[89,110],"CAN":[90,122,137,158],"(Controller":[91],"Area":[92],"Network)":[93],"bus,":[94],"they":[95],"inferred":[96],"identity":[98,146],"only":[102],"from":[103,120,180],"known":[104],"sensor":[105],"signals":[106],"(such":[107],"as":[108],"speed,":[111],"brake":[112],"pedal":[113],"position,":[114],"steering":[115],"wheel":[116],"angle,":[117],"etc.)":[118],"extracted":[119],"messages.":[123],"However,":[124],"car":[125],"manufacturers":[126],"intentionally":[127],"do":[128],"not":[129],"reveal":[130],"exact":[131],"signal":[132],"location":[133],"and":[134,170,178],"semantics":[135],"logs.":[138],"We":[139,160],"show":[140,171],"that":[141,172],"inference":[143],"possible":[148],"even":[149],"with":[150,183],"off-the-shelf":[151],"machine":[152],"learning":[153],"techniques":[154],"without":[155],"reverse-engineering":[156],"protocol.":[159],"demonstrate":[161],"our":[162],"approach":[163],"a":[165,173],"dataset":[166],"33":[168],"can":[175],"re-identified":[177],"distinguished":[179],"other":[181],"accuracy":[185],"75-85%.":[187]},"counts_by_year":[],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}