{"id":"https://openalex.org/W7134853638","doi":"https://doi.org/10.48550/arxiv.2603.07992","title":"SI-ChainFL: Shapley-Incentivized Secure Federated Learning for High-Speed Rail Data Sharing","display_name":"SI-ChainFL: Shapley-Incentivized Secure Federated Learning for High-Speed Rail Data Sharing","publication_year":2026,"publication_date":"2026-03-09","ids":{"openalex":"https://openalex.org/W7134853638","doi":"https://doi.org/10.48550/arxiv.2603.07992"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.07992","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128687886","display_name":"Mingjie Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Mingjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031355220","display_name":"Cheng Dai","orcid":"https://orcid.org/0000-0002-4853-8278"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dai, Cheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128670885","display_name":"Fei Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Fei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128650298","display_name":"Xin Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106707877","display_name":"Kaoru Ota","orcid":"https://orcid.org/0000-0002-3382-1652"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ota, Kaoru","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110693799","display_name":"Mianxiong Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Mianxiong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128649284","display_name":"Bing Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Bing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2687734,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.29670000076293945,"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"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.29670000076293945,"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/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.19030000269412994,"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/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.05990000069141388,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/federated-learning","display_name":"Federated learning","score":0.5813000202178955},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5386000275611877},{"id":"https://openalex.org/keywords/data-sharing","display_name":"Data sharing","score":0.52920001745224},{"id":"https://openalex.org/keywords/protocol","display_name":"Protocol (science)","score":0.4706000089645386},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.460099995136261},{"id":"https://openalex.org/keywords/shapley-value","display_name":"Shapley value","score":0.4571000039577484},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.44920000433921814},{"id":"https://openalex.org/keywords/incentive","display_name":"Incentive","score":0.4415000081062317},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4219000041484833}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7797999978065491},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.5813000202178955},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5386000275611877},{"id":"https://openalex.org/C2779965156","wikidata":"https://www.wikidata.org/wiki/Q5227350","display_name":"Data sharing","level":3,"score":0.52920001745224},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.4706000089645386},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.460099995136261},{"id":"https://openalex.org/C199022921","wikidata":"https://www.wikidata.org/wiki/Q240046","display_name":"Shapley value","level":3,"score":0.4571000039577484},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.44920000433921814},{"id":"https://openalex.org/C29122968","wikidata":"https://www.wikidata.org/wiki/Q1414816","display_name":"Incentive","level":2,"score":0.4415000081062317},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4219000041484833},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.39640000462532043},{"id":"https://openalex.org/C165136773","wikidata":"https://www.wikidata.org/wiki/Q1363179","display_name":"Single point of failure","level":2,"score":0.385699987411499},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.35429999232292175},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.34209999442100525},{"id":"https://openalex.org/C153517567","wikidata":"https://www.wikidata.org/wiki/Q26090","display_name":"Mechanism design","level":2,"score":0.32409998774528503},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3221000134944916},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.313400000333786},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.3034000098705292},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29809999465942383},{"id":"https://openalex.org/C2992444157","wikidata":"https://www.wikidata.org/wiki/Q775079","display_name":"Single point","level":3,"score":0.29750001430511475},{"id":"https://openalex.org/C534932454","wikidata":"https://www.wikidata.org/wiki/Q161410","display_name":"Peer-to-peer","level":2,"score":0.2948000133037567},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.28850001096725464},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.2879999876022339},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.28679999709129333},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C126831891","wikidata":"https://www.wikidata.org/wiki/Q221673","display_name":"Host (biology)","level":2,"score":0.2635999917984009}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.07992","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.07992","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.07992","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.07992","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"high-speed":[1],"rail":[2],"(HSR)":[3],"systems,":[4],"federated":[5],"learning":[6],"(FL)":[7],"enables":[8,129],"cross-departmental":[9],"flow":[10,146],"prediction":[11],"without":[12],"sharing":[13],"raw":[14],"data.":[15],"However,":[16],"existing":[17],"schemes":[18],"suffer":[19],"from":[20],"two":[21],"key":[22],"limitations:":[23],"(1)":[24],"insufficient":[25],"incentives,":[26],"leading":[27],"to":[28,98,117,124],"free-riding":[29],"and":[30,33,48,82,128,131,140,143],"model":[31],"poisoning;":[32],"(2)":[34],"centralized":[35],"aggregation,":[36,111],"which":[37],"introduces":[38],"a":[39,46,69,91,105,144],"single":[40],"point":[41],"of":[42],"failure.":[43],"We":[44],"propose":[45],"secure":[47,132],"efficient":[49,130],"framework":[50],"SI-ChainFL":[51],"that":[52,73,149],"addresses":[53],"these":[54],"issues":[55],"by":[56],"combining":[57],"contribution-aware":[58],"incentives":[59],"with":[60],"decentralized":[61,110],"aggregation.":[62,134],"First,":[63],"we":[64,88,103],"quantify":[65],"client":[66,95],"contributions":[67],"using":[68],"Shapley":[70,100,118],"value":[71],"metric":[72],"jointly":[74],"considers":[75],"rare-event":[76],"utility,":[77],"data":[78,80],"diversity,":[79],"quality,":[81],"timeliness.":[83],"To":[84],"reduce":[85],"computational":[86],"overhead,":[87],"further":[89,169],"develop":[90],"rare":[92],"positive":[93],"driven":[94],"clustering":[96],"strategy":[97],"accelerate":[99],"estimation.":[101],"Moreover,":[102],"design":[104,121],"blockchain-based":[106],"consensus":[107],"protocol":[108],"for":[109],"where":[112],"aggregation":[113],"eligibility":[114],"is":[115],"tied":[116],"incentives.":[119],"This":[120],"motivates":[122],"clients":[123,157],"submit":[125],"high-quality":[126],"updates":[127],"global":[133],"Experiments":[135],"on":[136,174],"MNIST,":[137],"CIFAR":[138,141],"10":[139],"100,":[142],"HSR":[145],"dataset":[147],"show":[148],"SI":[150],"ChainFL":[151],"remains":[152],"effective":[153],"under":[154],"90%":[155],"malicious":[156],"in":[158],"PA":[159],"attacks,":[160],"achieving":[161],"14.12%":[162],"higher":[163],"accuracy":[164],"than":[165],"RAGA.":[166],"Theoretical":[167],"analysis":[168],"guarantees":[170],"an":[171],"upper":[172],"bound":[173],"performance":[175]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-11T00:00:00"}