{"id":"https://openalex.org/W3117198571","doi":"https://doi.org/10.1109/icct50939.2020.9295828","title":"An Effective Data Filtering Scheme Based on Context in VANETs","display_name":"An Effective Data Filtering Scheme Based on Context in VANETs","publication_year":2020,"publication_date":"2020-10-28","ids":{"openalex":"https://openalex.org/W3117198571","doi":"https://doi.org/10.1109/icct50939.2020.9295828","mag":"3117198571"},"language":"en","primary_location":{"id":"doi:10.1109/icct50939.2020.9295828","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icct50939.2020.9295828","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 20th International Conference on Communication Technology (ICCT)","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/A5070452591","display_name":"Gaoyuan Xiong","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gaoyuan Xiong","raw_affiliation_strings":["College of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100331492","display_name":"Dongmei Zhang","orcid":"https://orcid.org/0000-0003-2497-3678"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongmei Zhang","raw_affiliation_strings":["College of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033496069","display_name":"Jieyao Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jieyao Xu","raw_affiliation_strings":["College of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.7157,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.66466624,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"752","last_page":"756"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9994999766349792,"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":0.9994999766349792,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9973000288009644,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9945999979972839,"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/computer-science","display_name":"Computer science","score":0.7941175699234009},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.717668354511261},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5863720178604126},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3348621428012848},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0895121693611145}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7941175699234009},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.717668354511261},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5863720178604126},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3348621428012848},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0895121693611145},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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":1,"locations":[{"id":"doi:10.1109/icct50939.2020.9295828","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icct50939.2020.9295828","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 20th International Conference on Communication Technology (ICCT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.6100000143051147,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1526820147","https://openalex.org/W1977680444","https://openalex.org/W1985719683","https://openalex.org/W1995064428","https://openalex.org/W2031795630","https://openalex.org/W2060422862","https://openalex.org/W2100975384","https://openalex.org/W2144182447","https://openalex.org/W2148685209","https://openalex.org/W2232624943","https://openalex.org/W2297788108","https://openalex.org/W2305409997","https://openalex.org/W2349814691","https://openalex.org/W2490763308","https://openalex.org/W2498575077","https://openalex.org/W2538524215","https://openalex.org/W2883738719","https://openalex.org/W2902192032","https://openalex.org/W2905176164","https://openalex.org/W2961463448","https://openalex.org/W6689600853"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W2350741829","https://openalex.org/W2530322880"],"abstract_inverted_index":{"Vehicular":[0],"ad":[1],"hoc":[2],"networks(VANETs)":[3],"ensure":[4],"the":[5,9,25,107,120],"road":[6,18],"safety":[7],"by":[8,124],"continuous":[10],"information":[11],"interaction":[12],"among":[13],"nodes":[14,16],"and":[15,49,59,70],"to":[17,62],"side":[19],"units":[20],"(RSUs).":[21],"Therefore,":[22],"filtering":[23,39],"out":[24],"received":[26],"bogus":[27,65,100,113],"data":[28,38,66,71,94,101,114],"becomes":[29],"an":[30,36],"urgent":[31],"problem.":[32],"In":[33],"this":[34],"paper,":[35],"effective":[37],"scheme":[40,53,121],"(EDFS)":[41],"based":[42,67],"on":[43,68,77],"context":[44,69],"for":[45],"VANETs":[46],"is":[47,86,122],"proposed":[48,52],"evaluated.":[50],"The":[51,117],"comprehensively":[54],"uses":[55],"outlier":[56],"detection":[57],"method":[58],"clustering":[60],"algorithm":[61],"detect":[63],"general":[64],"characteristics,":[72],"which":[73],"does":[74],"not":[75],"rely":[76],"other":[78],"third-party":[79],"infrastructure":[80],"(such":[81],"as":[82,115],"RSU).":[83],"Besides,":[84],"EDFS":[85],"capable":[87],"of":[88,109,112,119],"resisting":[89],"Sybil":[90],"attack":[91],"using":[92],"density-based":[93],"mining":[95],"methods,":[96],"it":[97],"ensured":[98],"that":[99],"can":[102],"be":[103],"effectively":[104],"filtered":[105],"in":[106],"presence":[108],"large":[110],"amounts":[111],"well.":[116],"effectiveness":[118],"proved":[123],"experiments.":[125]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}