{"id":"https://openalex.org/W4400646148","doi":"https://doi.org/10.1109/iv55156.2024.10588451","title":"Post-correlation Identification of GNSS Spoofing based on Spiking Neural Network","display_name":"Post-correlation Identification of GNSS Spoofing based on Spiking Neural Network","publication_year":2024,"publication_date":"2024-06-02","ids":{"openalex":"https://openalex.org/W4400646148","doi":"https://doi.org/10.1109/iv55156.2024.10588451"},"language":"en","primary_location":{"id":"doi:10.1109/iv55156.2024.10588451","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iv55156.2024.10588451","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Intelligent Vehicles Symposium (IV)","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/A5100420074","display_name":"Siqi Wang","orcid":"https://orcid.org/0000-0002-4911-141X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siqi Wang","raw_affiliation_strings":["Beijing Jiaotong University,School of Automation and Intelligence,Beijing,China,100044"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University,School of Automation and Intelligence,Beijing,China,100044","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107910334","display_name":"Jiang Liu","orcid":"https://orcid.org/0000-0001-5687-360X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiang Liu","raw_affiliation_strings":["Beijing Jiaotong University,Frontiers Science Center for Smart High-Speed Railway System,Beijing,China,100044"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University,Frontiers Science Center for Smart High-Speed Railway System,Beijing,China,100044","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100636115","display_name":"Baigen Cai","orcid":"https://orcid.org/0000-0002-6440-005X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bai-Gen Cai","raw_affiliation_strings":["Beijing Jiaotong University,School of Automation and Intelligence,Beijing,China,100044"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University,School of Automation and Intelligence,Beijing,China,100044","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068836948","display_name":"Debiao Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126311","display_name":"Beijing Transportation Research Center","ror":"https://ror.org/03pydk223","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210126311"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"De-Biao Lu","raw_affiliation_strings":["Beijing Engineering Research Center of EMC and GNSS Technology for Rail Transportation,Beijing,China,100044"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Engineering Research Center of EMC and GNSS Technology for Rail Transportation,Beijing,China,100044","institution_ids":["https://openalex.org/I4210126311"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3248","last_page":"3254"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10655","display_name":"GNSS positioning and interference","score":0.9520000219345093,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10655","display_name":"GNSS positioning and interference","score":0.9520000219345093,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/gnss-applications","display_name":"GNSS applications","score":0.9319949746131897},{"id":"https://openalex.org/keywords/spoofing-attack","display_name":"Spoofing attack","score":0.6476030349731445},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6211825609207153},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6072076559066772},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.562322735786438},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4902539551258087},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3742150068283081},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.2371455729007721},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.16347554326057434},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.14517179131507874},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11372685432434082}],"concepts":[{"id":"https://openalex.org/C14279187","wikidata":"https://www.wikidata.org/wiki/Q5514012","display_name":"GNSS applications","level":3,"score":0.9319949746131897},{"id":"https://openalex.org/C167900197","wikidata":"https://www.wikidata.org/wiki/Q11081100","display_name":"Spoofing attack","level":2,"score":0.6476030349731445},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6211825609207153},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6072076559066772},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.562322735786438},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4902539551258087},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3742150068283081},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.2371455729007721},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.16347554326057434},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.14517179131507874},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11372685432434082},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv55156.2024.10588451","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iv55156.2024.10588451","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"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/W1557560302","https://openalex.org/W2621278445","https://openalex.org/W2917307480","https://openalex.org/W2984844508","https://openalex.org/W3097607538","https://openalex.org/W3158153532","https://openalex.org/W3170540448","https://openalex.org/W3195956058","https://openalex.org/W3202875595","https://openalex.org/W4291800938","https://openalex.org/W4300980424","https://openalex.org/W4306922751","https://openalex.org/W4312670159","https://openalex.org/W4318320887","https://openalex.org/W4386453762","https://openalex.org/W4387400903","https://openalex.org/W4403428004","https://openalex.org/W6735954763","https://openalex.org/W6738885829","https://openalex.org/W6796939779","https://openalex.org/W6844652965"],"related_works":["https://openalex.org/W3095455901","https://openalex.org/W4312670159","https://openalex.org/W3126564540","https://openalex.org/W2968223354","https://openalex.org/W3008363920","https://openalex.org/W2088717005","https://openalex.org/W3206448138","https://openalex.org/W4319430861","https://openalex.org/W3200530419","https://openalex.org/W4379876618"],"abstract_inverted_index":{"The":[0,122],"spoofing":[1,25,42,79,128,160],"attack":[2,26,43,129],"would":[3],"be":[4],"a":[5,45,65],"serious":[6],"threat":[7],"to":[8,125,155],"location-based":[9],"applications":[10],"based":[11,83],"on":[12,84],"Global":[13],"Navigation":[14],"Satellite":[15],"System":[16],"(GNSS).":[17],"To":[18],"mitigate":[19],"the":[20,24,29,38,41,49,72,85,88,96,100,106,112,117,127,134,139,144,156,159,163,172],"negative":[21],"effect":[22],"of":[23,40,58,150,158],"that":[27,143],"makes":[28],"GNSS":[30,78,101],"receiver":[31,102],"obtain":[32],"fake":[33],"and":[34,95,116,136,165,171],"misleading":[35],"positioning":[36],"information,":[37],"identification":[39,80,153],"is":[44,51,64,69,82,130,148],"significant":[46],"step":[47],"before":[48],"countermeasure":[50],"adopted.":[52],"In":[53],"this":[54],"paper,":[55],"considering":[56],"constraints":[57],"existing":[59],"methods,":[60],"SpoofSpike":[61,118,145],"network,":[62],"which":[63],"novel":[66],"post-correlation":[67],"solution":[68,108,147],"proposed":[70],"using":[71,138],"Spiking":[73],"Neural":[74,174],"Network":[75,175],"(SNN).":[76],"This":[77],"scheme":[81],"differences":[86],"between":[87],"practically":[89],"measured":[90],"Cross":[91],"Ambiguity":[92],"Functions":[93],"(CAFs)":[94],"predicted":[97],"one":[98],"in":[99],"information":[103],"processing.":[104],"Under":[105],"overall":[107],"architecture,":[109],"details":[110],"about":[111],"spiking":[113],"neuron":[114],"model":[115],"network":[119],"are":[120],"given.":[121],"decision-making":[123],"mechanism":[124],"identify":[126],"analyzed.":[131],"Results":[132],"from":[133],"test":[135],"comparisons":[137],"TEXBAT":[140],"datasets":[141],"illustrate":[142],"network-based":[146],"capable":[149],"realizing":[151],"effective":[152],"according":[154],"comparison":[157],"score":[161],"with":[162],"threshold,":[164],"it":[166],"outperforms":[167],"other":[168],"SNN-based":[169],"models":[170],"Artificial":[173],"(ANN)":[176],"counterpart.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
