{"id":"https://openalex.org/W7127610955","doi":"https://doi.org/10.7717/peerj-cs.3589","title":"A secure cross-domain federated learning scheme based on blockchain fair payment","display_name":"A secure cross-domain federated learning scheme based on blockchain fair payment","publication_year":2026,"publication_date":"2026-02-04","ids":{"openalex":"https://openalex.org/W7127610955","doi":"https://doi.org/10.7717/peerj-cs.3589"},"language":"en","primary_location":{"id":"doi:10.7717/peerj-cs.3589","is_oa":true,"landing_page_url":"https://doi.org/10.7717/peerj-cs.3589","pdf_url":null,"source":{"id":"https://openalex.org/S4210178049","display_name":"PeerJ Computer Science","issn_l":"2376-5992","issn":["2376-5992"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320104","host_organization_name":"PeerJ, Inc.","host_organization_lineage":["https://openalex.org/P4310320104"],"host_organization_lineage_names":["PeerJ, Inc."],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PeerJ Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.7717/peerj-cs.3589","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124982720","display_name":"Qiuxian Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119635","display_name":"Kaili University","ror":"https://ror.org/02hzqbc55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119635"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiuxian Li","raw_affiliation_strings":["School of Big Data Engineering, Kaili University, Kaili, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Big Data Engineering, Kaili University, Kaili, China","institution_ids":["https://openalex.org/I4210119635"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062523327","display_name":"Dawen Xia","orcid":"https://orcid.org/0000-0002-0151-9643"},"institutions":[{"id":"https://openalex.org/I4210119635","display_name":"Kaili University","ror":"https://ror.org/02hzqbc55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119635"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dawen Xia","raw_affiliation_strings":["School of Big Data Engineering, Kaili University, Kaili, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Big Data Engineering, Kaili University, Kaili, China","institution_ids":["https://openalex.org/I4210119635"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125096854","display_name":"Youliang Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youliang Tian","raw_affiliation_strings":["College of Computer Science and Technology, Guizhou University, Guiyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Guizhou University, Guiyang, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123758857","display_name":"Quanxing Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119635","display_name":"Kaili University","ror":"https://ror.org/02hzqbc55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119635"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quanxing Zhou","raw_affiliation_strings":["School of Big Data Engineering, Kaili University, Kaili, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Big Data Engineering, Kaili University, Kaili, China","institution_ids":["https://openalex.org/I4210119635"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1395,"currency":"USD","value_usd":1395},"apc_paid":{"value":1395,"currency":"USD","value_usd":1395},"fwci":13.3698,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.97888523,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"12","issue":null,"first_page":"e3589","last_page":"e3589"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9527000188827515,"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":0.9527000188827515,"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/T10237","display_name":"Cryptography and Data Security","score":0.011800000444054604,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.004900000058114529,"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/federated-learning","display_name":"Federated learning","score":0.7930999994277954},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.7443000078201294},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.6991999745368958},{"id":"https://openalex.org/keywords/reputation","display_name":"Reputation","score":0.6697999835014343},{"id":"https://openalex.org/keywords/blockchain","display_name":"Blockchain","score":0.5321999788284302},{"id":"https://openalex.org/keywords/cryptography","display_name":"Cryptography","score":0.46209999918937683},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.40459999442100525},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.36070001125335693}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.830299973487854},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.7930999994277954},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.7443000078201294},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.6991999745368958},{"id":"https://openalex.org/C48798503","wikidata":"https://www.wikidata.org/wiki/Q877546","display_name":"Reputation","level":2,"score":0.6697999835014343},{"id":"https://openalex.org/C2779687700","wikidata":"https://www.wikidata.org/wiki/Q20514253","display_name":"Blockchain","level":2,"score":0.5321999788284302},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.46209999918937683},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.44369998574256897},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.40459999442100525},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.36070001125335693},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3555999994277954},{"id":"https://openalex.org/C108710211","wikidata":"https://www.wikidata.org/wiki/Q11538","display_name":"Mathematical proof","level":2,"score":0.34389999508857727},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30250000953674316},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.30059999227523804},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2962000072002411},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C2776384856","wikidata":"https://www.wikidata.org/wiki/Q17145767","display_name":"Trust management (information system)","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C145097563","wikidata":"https://www.wikidata.org/wiki/Q1148747","display_name":"Payment","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C10511746","wikidata":"https://www.wikidata.org/wiki/Q899388","display_name":"Data security","level":3,"score":0.27410000562667847},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C177225278","wikidata":"https://www.wikidata.org/wiki/Q192674","display_name":"Factoring","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C24138899","wikidata":"https://www.wikidata.org/wiki/Q17141258","display_name":"Instance-based learning","level":3,"score":0.26100000739097595},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.25209999084472656},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.25110000371932983}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.7717/peerj-cs.3589","is_oa":true,"landing_page_url":"https://doi.org/10.7717/peerj-cs.3589","pdf_url":null,"source":{"id":"https://openalex.org/S4210178049","display_name":"PeerJ Computer Science","issn_l":"2376-5992","issn":["2376-5992"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320104","host_organization_name":"PeerJ, Inc.","host_organization_lineage":["https://openalex.org/P4310320104"],"host_organization_lineage_names":["PeerJ, Inc."],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PeerJ Computer Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:f48e9db4eb4c4f52b75c5c249258a3b6","is_oa":true,"landing_page_url":"https://doaj.org/article/f48e9db4eb4c4f52b75c5c249258a3b6","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":"PeerJ Computer Science, Vol 12, p e3589 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.7717/peerj-cs.3589","is_oa":true,"landing_page_url":"https://doi.org/10.7717/peerj-cs.3589","pdf_url":null,"source":{"id":"https://openalex.org/S4210178049","display_name":"PeerJ Computer Science","issn_l":"2376-5992","issn":["2376-5992"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320104","host_organization_name":"PeerJ, Inc.","host_organization_lineage":["https://openalex.org/P4310320104"],"host_organization_lineage_names":["PeerJ, Inc."],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PeerJ Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1835868686","display_name":null,"funder_award_id":"YTH-PT202501","funder_id":"https://openalex.org/F8933595257","funder_display_name":"Kaili University"},{"id":"https://openalex.org/G8774308883","display_name":null,"funder_award_id":"62462013, U23B2024, and 62272123","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F8933595257","display_name":"Kaili University","ror":"https://ror.org/02hzqbc55"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2783522756","https://openalex.org/W2991448185","https://openalex.org/W3088396143","https://openalex.org/W3122023385","https://openalex.org/W3129336662","https://openalex.org/W3168496996","https://openalex.org/W3176582776","https://openalex.org/W3185309611","https://openalex.org/W3199107099","https://openalex.org/W4206936477","https://openalex.org/W4220954463","https://openalex.org/W4225987247","https://openalex.org/W4281621656","https://openalex.org/W4285121820","https://openalex.org/W4294653533","https://openalex.org/W4313389135","https://openalex.org/W4318619660","https://openalex.org/W4395680579","https://openalex.org/W6911801421","https://openalex.org/W6922593631"],"related_works":[],"abstract_inverted_index":{"Background":[0],"Cross-domain":[1],"federated":[2,29,61,145,182,293],"learning":[3,8,30,62,146,183],"is":[4,150,157,164,241,257,305],"an":[5],"innovative":[6],"machine":[7],"paradigm":[9],"that":[10,174],"allows":[11],"data":[12,25,37,114,249,304],"owners":[13],"from":[14,47],"different":[15],"domains":[16],"to":[17,107,123,274],"collaboratively":[18],"train":[19],"a":[20,58,82,195],"shared":[21],"model":[22],"while":[23,184],"preserving":[24],"privacy.":[26],"However,":[27],"cross-domain":[28,60,292],"also":[31,185],"faces":[32],"numerous":[33],"challenges,":[34],"such":[35,101],"as":[36,102],"and":[38,44,74,86,104,111,115,127,136,138,189,209,269,276,289],"system":[39],"heterogeneity,":[40],"client":[41,80],"reputation":[42,77,83,234],"management,":[43],"potential":[45],"threats":[46],"malicious":[48],"attackers.":[49],"Methods":[50],"To":[51],"address":[52],"these":[53],"issues,":[54],"this":[55],"article":[56],"proposes":[57],"secure":[59],"scheme":[63,71,96,132,177,281],"based":[64,90],"on":[65,91,133,200],"blockchain":[66,103],"fair":[67,88],"payment.":[68],"The":[69,170,279,302],"proposed":[70,131,176,232,280],"effectively":[72],"evaluates":[73],"updates":[75],"the":[76,95,109,125,130,175,179,192,201,219,231,254,266,284],"of":[78,113,119,129,181,198,228,291],"each":[79],"through":[81],"management":[84],"mechanism":[85],"allocates":[87],"rewards":[89],"their":[92],"contributions.":[93],"Additionally,":[94],"employs":[97],"advanced":[98],"cryptographic":[99],"technologies":[100],"zero-knowledge":[105],"proofs":[106],"ensure":[108],"security":[110],"fairness":[112,128,188,290],"transactions.":[116],"A":[117],"series":[118],"experiments":[120],"are":[121,140,272],"conducted":[122,141],"evaluate":[124],"performance":[126,180],"multiple":[134],"datasets":[135],"models,":[137],"comparisons":[139],"with":[142],"other":[143],"mainstream":[144],"algorithms.":[147],"MNIST":[148,202],"Dataset":[149,156,163],"available":[151,158,165,306],"at:":[152,307],"https://www.kaggle.com/datasets/hojjatk/mnist-dataset":[153],".":[154,161,168,309],"Fashion-MNIST":[155],"at":[159,166],"https://github.com/zalandoresearch/fashion-mnist":[160],"CIFAR-10":[162],"https://www.cs.toronto.edu/~kriz/cifar.html":[167],"Results":[169],"experimental":[171,303],"results":[172],"demonstrate":[173],"ensures":[178],"maintaining":[186],"its":[187,296],"security.":[190],"Specifically,":[191],"method":[193,235],"achieves":[194],"test":[196],"accuracy":[197,255],"97%":[199],"dataset,":[203,221],"outperforming":[204],"Federated":[205,214],"Averaging":[206,212],"(FedAvg)":[207],"(95%)":[208],"Stochastic":[210],"Controlled":[211],"for":[213],"Learning":[215],"(SCAFFOLD)":[216],"(96%).":[217],"On":[218],"FEMNIST":[220],"it":[222],"attains":[223],"89%":[224],"accuracy.":[225],"In":[226],"terms":[227],"convergence":[229,286],"speed,":[230,287],"optimization-based":[233],"converges":[236],"in":[237,299],"26":[238],"rounds,":[239],"which":[240],"faster":[242],"than":[243,259],"baseline":[244],"methods":[245],"(28\u201332":[246],"rounds).":[247],"Under":[248],"tampering":[250],"attacks":[251],"(50-client":[252],"scenario),":[253],"drop":[256],"less":[258],"3%,":[260],"showing":[261],"strong":[262],"robustness.":[263],"For":[264],"fairness,":[265],"trust":[267],"difference":[268,271],"reward":[270],"reduced":[273],"0.10":[275],"0.08,":[277],"respectively.":[278],"significantly":[282],"improves":[283],"accuracy,":[285],"robustness,":[288],"learning,":[294],"advancing":[295],"practical":[297],"deployment":[298],"real-world":[300],"scenarios.":[301],"https://zenodo.org/records/15210778":[308]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-08-29T07:29:34.045763","created_date":"2026-02-06T00:00:00"}