{"id":"https://openalex.org/W4281958761","doi":"https://doi.org/10.1109/noms54207.2022.9789771","title":"BoostGuard: Interpretable Misbehavior Detection in Vehicular Communication Networks","display_name":"BoostGuard: Interpretable Misbehavior Detection in Vehicular Communication Networks","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4281958761","doi":"https://doi.org/10.1109/noms54207.2022.9789771"},"language":"en","primary_location":{"id":"doi:10.1109/noms54207.2022.9789771","is_oa":false,"landing_page_url":"https://doi.org/10.1109/noms54207.2022.9789771","pdf_url":null,"source":{"id":"https://openalex.org/S4363605650","display_name":"NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium","raw_type":"proceedings-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/A5076125701","display_name":"Marwa Elsayed","orcid":"https://orcid.org/0000-0001-9906-5020"},"institutions":[{"id":"https://openalex.org/I129902397","display_name":"Dalhousie University","ror":"https://ror.org/01e6qks80","country_code":"CA","type":"education","lineage":["https://openalex.org/I129902397"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Marwa A. Elsayed","raw_affiliation_strings":["Dalhousie University,Faculty of Computer Science,Halifax,NS,Canada,B3H 4R2"],"affiliations":[{"raw_affiliation_string":"Dalhousie University,Faculty of Computer Science,Halifax,NS,Canada,B3H 4R2","institution_ids":["https://openalex.org/I129902397"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008462534","display_name":"A. Nur Zincir\u2010Heywood","orcid":"https://orcid.org/0000-0003-2796-7265"},"institutions":[{"id":"https://openalex.org/I129902397","display_name":"Dalhousie University","ror":"https://ror.org/01e6qks80","country_code":"CA","type":"education","lineage":["https://openalex.org/I129902397"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Nur Zincir-Heywood","raw_affiliation_strings":["Dalhousie University,Faculty of Computer Science,Halifax,NS,Canada,B3H 4R2"],"affiliations":[{"raw_affiliation_string":"Dalhousie University,Faculty of Computer Science,Halifax,NS,Canada,B3H 4R2","institution_ids":["https://openalex.org/I129902397"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5076125701"],"corresponding_institution_ids":["https://openalex.org/I129902397"],"apc_list":null,"apc_paid":null,"fwci":2.5779,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.90731947,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9927999973297119,"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":0.9927999973297119,"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":0.9902999997138977,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.979200005531311,"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/computer-science","display_name":"Computer science","score":0.7695797681808472},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3939768970012665},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3485836386680603}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7695797681808472},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3939768970012665},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3485836386680603}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/noms54207.2022.9789771","is_oa":false,"landing_page_url":"https://doi.org/10.1109/noms54207.2022.9789771","pdf_url":null,"source":{"id":"https://openalex.org/S4363605650","display_name":"NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5799999833106995}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2028397517","https://openalex.org/W2079085665","https://openalex.org/W2099005886","https://openalex.org/W2148143831","https://openalex.org/W2158647132","https://openalex.org/W2203968176","https://openalex.org/W2295598076","https://openalex.org/W2545176003","https://openalex.org/W2752449160","https://openalex.org/W2771179281","https://openalex.org/W2776458791","https://openalex.org/W2800112063","https://openalex.org/W2910871229","https://openalex.org/W2946217016","https://openalex.org/W2962853428","https://openalex.org/W2964314709","https://openalex.org/W2982952033","https://openalex.org/W2986229993","https://openalex.org/W3026549821","https://openalex.org/W3045657906","https://openalex.org/W3048207230","https://openalex.org/W3094692755","https://openalex.org/W3100121400","https://openalex.org/W3139312002","https://openalex.org/W7067914233"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Wireless":[0],"Communication":[1],"and":[2,35,51,123,142,173],"Artificial":[3],"Intelligence":[4],"are":[5,148],"at":[6],"the":[7,11,14,59,71],"heart":[8],"of":[9,106,110],"driving":[10],"evolution":[12],"in":[13],"transportation":[15],"industry.":[16],"Cooperative":[17],"Intelligent":[18],"Transportation":[19],"Systems":[20],"adopt":[21],"vehicle-to-vehicle":[22],"(V2V)":[23],"technology":[24,43],"to":[25,28,62,84,134],"allow":[26],"vehicles":[27],"exchange":[29],"real-time":[30],"information":[31],"about":[32],"speed,":[33],"heading,":[34],"location":[36],"wirelessly":[37],"with":[38,169],"their":[39],"surrounding":[40],"vehicles.":[41],"Such":[42],"has":[44],"remarkable":[45],"benefits":[46],"for":[47,99,139],"improving":[48],"vehicles\u2019":[49],"safety":[50,86],"awareness,":[52],"albeit":[53],"imposing":[54],"many":[55],"security":[56],"risks.":[57],"Despite":[58],"evolving":[60],"efforts":[61],"employ":[63],"authentication":[64],"mechanisms,":[65],"there":[66],"is":[67,74],"no":[68],"guarantee":[69],"that":[70,163],"exchanged":[72,103],"data":[73,80,102,120],"trustworthy.":[75],"Security":[76],"breaches":[77],"causing":[78],"falsified":[79,101],"can":[81],"aggressively":[82],"lead":[83],"severe":[85],"damages":[87],"within":[88],"vehicular":[89,115,157],"networks.":[90,116],"This":[91],"paper":[92],"proposes,":[93],"BoostGuard,":[94],"a":[95],"novel":[96],"interpretable":[97],"framework":[98],"detecting":[100,141],"as":[104],"part":[105],"five":[107],"different":[108],"types":[109],"position":[111],"forging":[112],"attacks":[113],"against":[114],"BoostGuard":[117],"mainly":[118],"adopts":[119],"science":[121],"principles":[122],"leverages":[124],"advanced":[125],"machine":[126],"learning":[127],"techniques":[128],"(i.e.,":[129],"boosting":[130],"decision":[131],"tree":[132],"ensemble)":[133],"boost":[135],"its":[136],"generalization":[137],"capabilities":[138],"precisely":[140],"classifying":[143],"attack":[144],"types.":[145],"Extensive":[146],"experiments":[147],"conducted":[149],"over":[150],"an":[151],"open-source":[152],"dataset,":[153],"reflecting":[154],"dynamic":[155],"real-world":[156],"environments.":[158],"The":[159],"evaluation":[160],"results":[161],"demonstrate":[162],"our":[164],"solution":[165],"outperforms":[166],"existing":[167],"solutions":[168],"high":[170],"detection":[171],"effectiveness":[172],"computational":[174],"time":[175],"efficiency.":[176]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}