{"id":"https://openalex.org/W3127521468","doi":"https://doi.org/10.1109/access.2021.3055209","title":"Anomaly Detection and Attack Classification for Train Real-Time Ethernet","display_name":"Anomaly Detection and Attack Classification for Train Real-Time Ethernet","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3127521468","doi":"https://doi.org/10.1109/access.2021.3055209","mag":"3127521468"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3055209","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3055209","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2021.3055209","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025053795","display_name":"Ruifeng Duo","orcid":"https://orcid.org/0000-0002-1665-7897"},"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":"Ruifeng Duo","raw_affiliation_strings":["School of Electrical Engineering, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1665-7897","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081793085","display_name":"Xiaobo Nie","orcid":"https://orcid.org/0000-0002-8444-3751"},"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":"Xiaobo Nie","raw_affiliation_strings":["School of Electrical Engineering, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8444-3751","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103149734","display_name":"Ning Yang","orcid":"https://orcid.org/0000-0003-4388-2691"},"institutions":[{"id":"https://openalex.org/I4210141966","display_name":"China Academy of Railway Sciences","ror":"https://ror.org/051wv2j09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210141966"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Yang","raw_affiliation_strings":["Locomotive and Car Research Institute, China Academy of Railway Sciences Corporation Ltd., Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4388-2691","affiliations":[{"raw_affiliation_string":"Locomotive and Car Research Institute, China Academy of Railway Sciences Corporation Ltd., Beijing, China","institution_ids":["https://openalex.org/I4210141966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035734831","display_name":"Chuan Yue","orcid":"https://orcid.org/0000-0001-9847-149X"},"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":"Chuan Yue","raw_affiliation_strings":["School of Electrical Engineering, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100641866","display_name":"Yongxiang Wang","orcid":"https://orcid.org/0000-0003-4195-3468"},"institutions":[{"id":"https://openalex.org/I4210141966","display_name":"China Academy of Railway Sciences","ror":"https://ror.org/051wv2j09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210141966"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongxiang Wang","raw_affiliation_strings":["Locomotive and Car Research Institute, China Academy of Railway Sciences Corporation Ltd., Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4195-3468","affiliations":[{"raw_affiliation_string":"Locomotive and Car Research Institute, China Academy of Railway Sciences Corporation Ltd., Beijing, China","institution_ids":["https://openalex.org/I4210141966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.8481,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.93340203,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"22528","last_page":"22541"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9998000264167786,"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":0.9983999729156494,"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/T10917","display_name":"Smart Grid Security and Resilience","score":0.9973000288009644,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.8054622411727905},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7153133153915405},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.6845760941505432},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5126703977584839},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5109350085258484},{"id":"https://openalex.org/keywords/ethernet","display_name":"Ethernet","score":0.5063482522964478},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.44147029519081116},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.42784395813941956},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35154345631599426},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32206815481185913},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.15407070517539978}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8054622411727905},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7153133153915405},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.6845760941505432},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5126703977584839},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5109350085258484},{"id":"https://openalex.org/C172173386","wikidata":"https://www.wikidata.org/wiki/Q79984","display_name":"Ethernet","level":2,"score":0.5063482522964478},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.44147029519081116},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.42784395813941956},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35154345631599426},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32206815481185913},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.15407070517539978},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3055209","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3055209","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:851b8a010b1048ed85685bf17be08750","is_oa":true,"landing_page_url":"https://doaj.org/article/851b8a010b1048ed85685bf17be08750","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 22528-22541 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3055209","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3055209","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.75,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W34688585","https://openalex.org/W1502922572","https://openalex.org/W1618905105","https://openalex.org/W1781712231","https://openalex.org/W1814370559","https://openalex.org/W1967376128","https://openalex.org/W1975415766","https://openalex.org/W1995443851","https://openalex.org/W1997037234","https://openalex.org/W2110403674","https://openalex.org/W2129629259","https://openalex.org/W2131060714","https://openalex.org/W2191006491","https://openalex.org/W2290883490","https://openalex.org/W2326324325","https://openalex.org/W2558639397","https://openalex.org/W2598684549","https://openalex.org/W2732383329","https://openalex.org/W2888898286","https://openalex.org/W2896487165","https://openalex.org/W2901719563","https://openalex.org/W2912178498","https://openalex.org/W2979590797","https://openalex.org/W2997258927","https://openalex.org/W3094219804","https://openalex.org/W3214373139","https://openalex.org/W6636501900","https://openalex.org/W6638526675","https://openalex.org/W6649655730","https://openalex.org/W6676949578","https://openalex.org/W6730268709","https://openalex.org/W6735304853","https://openalex.org/W6803782233"],"related_works":["https://openalex.org/W2357468538","https://openalex.org/W1577110157","https://openalex.org/W2355007334","https://openalex.org/W2390009783","https://openalex.org/W4254602698","https://openalex.org/W2394461323","https://openalex.org/W2349441905","https://openalex.org/W2361044160","https://openalex.org/W1483130311","https://openalex.org/W3120792425"],"abstract_inverted_index":{"Real-time":[0],"Ethernet":[1,28,175,293],"has":[2,254],"been":[3],"applied":[4],"to":[5,53,112,186,195,315,322],"train":[6,39,55,66,173,291],"control":[7],"and":[8,19,76,102,137,139,149,163,166,212,224,245,327],"management":[9],"system":[10,71,289],"(TCMS)":[11],"of":[12,26,34,118,170,200,208,217,259,263,290,301,320,363],"250km/h":[13],"Fuxing":[14],"Electric":[15],"Multiple":[16],"Units":[17],"(EMUs)":[18],"some":[20],"urban":[21],"rail":[22],"vehicles.":[23],"The":[24,95,197],"openness":[25],"the":[27,38,54,82,114,121,145,157,167,171,180,190,201,209,218,231,235,242,250,260,264,268,280,286,296,306,309,318,331,338,346,356,361],"communication":[29,40,56,67],"protocol":[30],"poses":[31],"a":[32,47,65,255],"risk":[33],"intrusion":[35,69,147,181,287,342],"attacks":[36,321],"on":[37,59,73,90,129,241,249,336,352],"network.":[41],"It":[42],"is,":[43],"therefore,":[44],"necessary":[45],"that":[46,207,216,285],"safety":[48],"protection":[49],"technology":[50],"is":[51,79,153,271],"introduced":[52],"network":[57,68],"based":[58,72,89,128,335,351],"real-time":[60,174,292],"Ethernet.":[61],"In":[62],"this":[63],"paper,":[64],"detection":[70,75,87,148,182,191,288,300,333,343],"anomaly":[74,86,332],"attack":[77,125,150,232,348],"classification":[78,126,138,151,257,269,349],"proposed.":[80],"Firstly,":[81],"paper":[83,122],"built":[84,123,146],"an":[85],"model":[88,152,298,311,334,340],"support":[91],"vector":[92,99,105],"machines":[93,100,106],"(SVM).":[94],"particle":[96],"swarm":[97],"optimization-support":[98],"(PSO-SVM),":[101],"genetic":[103],"algorithm-support":[104],"(GA-SVM)":[107],"optimization":[108],"algorithms":[109],"are":[110,133,227],"used":[111,314],"optimize":[113],"kernel":[115],"function":[116],"parameters":[117],"SVM.":[119],"Secondly,":[120],"two":[124],"models":[127,226],"random":[130],"forest.":[131],"They":[132],"iterative":[134],"dichotomiser3":[135],"(ID3)":[136],"regression":[140],"tree":[141],"(CART).":[142],"And":[143,345],"then,":[144],"tested":[154],"by":[155],"using":[156],"public":[158],"data":[159,164,168,261],"set":[160,169],"knowledge":[161],"discovery":[162],"mining-99(KDD-99)":[165],"simulation":[172],"test":[176,251],"bench.":[177],"PSO-SVM":[178,202],"improves":[179,189,341],"accuracy":[183,192,240,248,258],"from":[184,193],"90.3%":[185,194],"95.75%,":[187],"GA-SVM":[188,210,297],"95.85%.":[196],"training":[198,243,265],"time":[199,270],"algorithm":[203,237,350],"was":[204],"higher":[205,214],"than":[206,215],"algorithm,":[211],"much":[213],"SVM,":[219,337],"without":[220],"optimization.":[221],"Both":[222],"ID3":[223,236,253,275],"CART":[225,310,353],"verified":[228],"valid":[229],"in":[230],"classification,":[233],"while":[234,359],"obtained":[238],"100%":[239],"set,":[244,252],"only":[246],"32.89%":[247],"poor":[256],"outside":[262],"set.":[266],"Also,":[267],"very":[272],"long":[273],"for":[274,299],"compared":[276],"with":[277,330],"CART.":[278],"So":[279],"comprehensive":[281],"experimental":[282],"results":[283],"show":[284],"can":[294,312,354],"use":[295],"abnormal":[302],"data.":[303],"After":[304],"passing":[305],"normal":[307],"data,":[308],"be":[313],"distinguish":[316],"between":[317],"types":[319],"better":[323],"complete":[324],"subsequent":[325],"responses":[326],"operations.":[328],"Compared":[329],"proposed":[339,347],"accuracy.":[344],"improve":[355],"computing":[357],"speed":[358],"ensuring":[360],"precision":[362],"classification.":[364]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":5}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}