{"id":"https://openalex.org/W7124319652","doi":"https://doi.org/10.1007/s44443-025-00426-3","title":"Privacy-preserving transfer learning via one-time encrypted data filtering","display_name":"Privacy-preserving transfer learning via one-time encrypted data filtering","publication_year":2026,"publication_date":"2026-01-15","ids":{"openalex":"https://openalex.org/W7124319652","doi":"https://doi.org/10.1007/s44443-025-00426-3"},"language":"en","primary_location":{"id":"doi:10.1007/s44443-025-00426-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44443-025-00426-3","pdf_url":null,"source":{"id":"https://openalex.org/S2764955546","display_name":"Journal of King Saud University - Computer and Information Sciences","issn_l":"1319-1578","issn":["1319-1578","2213-1248"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of King Saud University Computer and Information Sciences","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1007/s44443-025-00426-3","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123072416","display_name":"Chao Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chao Xu","raw_affiliation_strings":["Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123059784","display_name":"Yun Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Wang","raw_affiliation_strings":["Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5123072416"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":{"value":1350,"currency":"USD","value_usd":1350},"apc_paid":{"value":1350,"currency":"USD","value_usd":1350},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06713018,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"38","issue":"2","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":0.8873000144958496,"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":0.8873000144958496,"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":0.08229999989271164,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.00839999970048666,"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/encryption","display_name":"Encryption","score":0.6514000296592712},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6200000047683716},{"id":"https://openalex.org/keywords/homomorphic-encryption","display_name":"Homomorphic encryption","score":0.5986999869346619},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.4487999975681305},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.44749999046325684},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.415800005197525},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4092000126838684},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.40290001034736633}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8125},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.6514000296592712},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6200000047683716},{"id":"https://openalex.org/C158338273","wikidata":"https://www.wikidata.org/wiki/Q2154943","display_name":"Homomorphic encryption","level":3,"score":0.5986999869346619},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49459999799728394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4876999855041504},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.4487999975681305},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.44749999046325684},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4336000084877014},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.415800005197525},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4138000011444092},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4092000126838684},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.40290001034736633},{"id":"https://openalex.org/C557945733","wikidata":"https://www.wikidata.org/wiki/Q389772","display_name":"Data transmission","level":2,"score":0.36959999799728394},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3628000020980835},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3549000024795532},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.35370001196861267},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.32519999146461487},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2847000062465668},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.26109999418258667}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44443-025-00426-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44443-025-00426-3","pdf_url":null,"source":{"id":"https://openalex.org/S2764955546","display_name":"Journal of King Saud University - Computer and Information Sciences","issn_l":"1319-1578","issn":["1319-1578","2213-1248"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of King Saud University Computer and Information Sciences","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:29c62a9271f149e1b87bf895dbde7716","is_oa":true,"landing_page_url":"https://doaj.org/article/29c62a9271f149e1b87bf895dbde7716","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":"Journal of King Saud University: Computer and Information Sciences, Vol 38, Iss 2 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44443-025-00426-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44443-025-00426-3","pdf_url":null,"source":{"id":"https://openalex.org/S2764955546","display_name":"Journal of King Saud University - Computer and Information Sciences","issn_l":"1319-1578","issn":["1319-1578","2213-1248"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of King Saud University Computer and Information Sciences","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5585548281669617,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W56544557","https://openalex.org/W1966731635","https://openalex.org/W2007339694","https://openalex.org/W2031533839","https://openalex.org/W2177209050","https://openalex.org/W2233233025","https://openalex.org/W2533800772","https://openalex.org/W2701059868","https://openalex.org/W2768174108","https://openalex.org/W2794974431","https://openalex.org/W2895865029","https://openalex.org/W2951013084","https://openalex.org/W2954732411","https://openalex.org/W3016473712","https://openalex.org/W3094502228","https://openalex.org/W3105274027","https://openalex.org/W3148280841","https://openalex.org/W3170178860","https://openalex.org/W3195598474","https://openalex.org/W3211008974","https://openalex.org/W4205350912","https://openalex.org/W4245119036","https://openalex.org/W4285284542","https://openalex.org/W4287817432","https://openalex.org/W4297683418","https://openalex.org/W4307823778","https://openalex.org/W4312463463"],"related_works":[],"abstract_inverted_index":{"Private":[0],"neural":[1],"network":[2],"training":[3,28,70,100,109,179],"on":[4,23,41,136],"encrypted":[5,69,149],"data":[6,150],"provides":[7],"strong":[8],"protection":[9],"for":[10,83,197],"user":[11],"identity":[12],"privacy.":[13],"However,":[14],"its":[15,194],"substantial":[16],"computational":[17,114],"overhead":[18],"hinders":[19],"practical":[20,195],"deployment,":[21],"particularly":[22],"large-scale":[24],"datasets":[25],"where":[26],"full":[27],"cycles":[29],"may":[30],"require":[31],"thousands":[32],"of":[33,129,191],"hours.":[34],"Current":[35],"FHE-based":[36,133],"privacy-preserving":[37,198],"approaches":[38],"predominantly":[39],"rely":[40],"transfer":[42,55],"learning,":[43],"which":[44],"appends":[45],"and":[46,111,157],"fine-tunes":[47],"new":[48,64],"classification":[49],"layers":[50],"atop":[51],"pre-trained":[52],"models.":[53],"Nevertheless,":[54],"learning":[56],"often":[57],"introduces":[58],"significant":[59],"redundancy":[60],"when":[61],"applied":[62],"to":[63,152,182],"datasets,":[65],"considerably":[66],"prolonging":[67],"the":[68,98,107,164],"process.":[71],"To":[72],"mitigate":[73],"this,":[74,137],"we":[75,138],"propose":[76],"a":[77,126,140,146,175,187],"simple":[78],"yet":[79],"efficient":[80],"FHE-compatible":[81],"algorithm":[82],"sample":[84,92,141],"importance":[85],"evaluation.":[86],"\u200b\u200bA":[87],"core":[88],"innovation":[89],"is":[90,94],"that":[91,144,171],"scoring":[93],"performed":[95],"exclusively":[96],"during":[97],"initial":[99],"epoch\u200b\u200b,":[101],"eliminating":[102],"repeated":[103],"full-dataset":[104],"evaluations":[105],"throughout":[106],"entire":[108],"cycle":[110],"drastically":[112],"reducing":[113,163],"overhead.":[115],"\u200b\u200bFurthermore,":[116],"our":[117,172],"evaluation":[118],"method":[119],"entirely":[120],"avoids":[121],"polynomial":[122],"homomorphic":[123],"evaluations\u200b\u200b,":[124],"circumventing":[125],"major":[127],"source":[128],"latency":[130],"in":[131,178],"existing":[132],"methods.":[134],"Building":[135],"design":[139],"reorganization":[142],"strategy":[143],"leverages":[145],"carefully":[147],"initialized":[148],"layout":[151],"rapidly":[153],"assemble":[154],"informative":[155],"samples":[156],"prune":[158],"redundant":[159],"ones,":[160],"thereby":[161],"substantially":[162],"effective":[165],"dataset":[166],"size.":[167],"Experimental":[168],"results":[169],"demonstrate":[170],"approach":[173],"achieves":[174],"30%":[176],"speedup":[177],"time":[180],"compared":[181],"state-of-the-art":[183],"methods,":[184],"with":[185],"only":[186],"marginal":[188],"accuracy":[189],"drop":[190],"0.6%,":[192],"highlighting":[193],"utility":[196],"machine":[199],"learning.":[200]},"counts_by_year":[],"updated_date":"2026-02-17T06:05:46.635709","created_date":"2026-01-16T00:00:00"}
