{"id":"https://openalex.org/W4386260712","doi":"https://doi.org/10.1109/infocom53939.2023.10228895","title":"FedSDG-FS: Efficient and Secure Feature Selection for Vertical Federated Learning","display_name":"FedSDG-FS: Efficient and Secure Feature Selection for Vertical Federated Learning","publication_year":2023,"publication_date":"2023-05-17","ids":{"openalex":"https://openalex.org/W4386260712","doi":"https://doi.org/10.1109/infocom53939.2023.10228895"},"language":"en","primary_location":{"id":"doi:10.1109/infocom53939.2023.10228895","is_oa":false,"landing_page_url":"https://doi.org/10.1109/infocom53939.2023.10228895","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","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/A5000173131","display_name":"Anran Li","orcid":"https://orcid.org/0000-0002-3592-4153"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Anran Li","raw_affiliation_strings":["Nanyang Technological University,Singapore","Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University,Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083082430","display_name":"Hongyi Peng","orcid":"https://orcid.org/0000-0002-2720-2628"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Hongyi Peng","raw_affiliation_strings":["Nanyang Technological University,Singapore","Alibaba-NTU Singapore Joint Research Institute & Alibaba Group","Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University,Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Alibaba-NTU Singapore Joint Research Institute & Alibaba Group","institution_ids":[]},{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100322320","display_name":"Lan Zhang","orcid":"https://orcid.org/0000-0003-1004-8588"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lan Zhang","raw_affiliation_strings":["University of Science and Technology of China,China","Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, China","University of Science and Technology of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China,China","institution_ids":["https://openalex.org/I126520041"]},{"raw_affiliation_string":"Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, China","institution_ids":[]},{"raw_affiliation_string":"University of Science and Technology of China, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114973731","display_name":"Jiahui Huang","orcid":"https://orcid.org/0009-0004-7444-0436"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahui Huang","raw_affiliation_strings":["University of Science and Technology of China,China","University of Science and Technology of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China,China","institution_ids":["https://openalex.org/I126520041"]},{"raw_affiliation_string":"University of Science and Technology of China, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046141922","display_name":"Qing Guo","orcid":"https://orcid.org/0000-0003-4209-5469"},"institutions":[{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]},{"id":"https://openalex.org/I4210161496","display_name":"A*STAR Graduate Academy","ror":"https://ror.org/059yjzn93","country_code":"SG","type":"education","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210161496"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Qing Guo","raw_affiliation_strings":["A*STAR,Center for Frontier AI Research (CFAR),Singapore","Center for Frontier AI Research (CFAR), A*STAR, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"A*STAR,Center for Frontier AI Research (CFAR),Singapore","institution_ids":["https://openalex.org/I4210161496"]},{"raw_affiliation_string":"Center for Frontier AI Research (CFAR), A*STAR, Singapore","institution_ids":["https://openalex.org/I115228651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064069283","display_name":"Han Yu","orcid":"https://orcid.org/0000-0001-6893-8650"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Han Yu","raw_affiliation_strings":["Nanyang Technological University,Singapore","Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University,Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100355692","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0001-7300-9215"},"institutions":[{"id":"https://openalex.org/I1328775524","display_name":"Zhejiang Sci-Tech University","ror":"https://ror.org/03893we55","country_code":"CN","type":"education","lineage":["https://openalex.org/I1328775524"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Liu","raw_affiliation_strings":["Zhejiang Sci-Tech University,China","Zhejiang Sci-Tech University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang Sci-Tech University,China","institution_ids":["https://openalex.org/I1328775524"]},{"raw_affiliation_string":"Zhejiang Sci-Tech University, China","institution_ids":["https://openalex.org/I1328775524"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.426,"has_fulltext":false,"cited_by_count":49,"citation_normalized_percentile":{"value":0.98806813,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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":1.0,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9954000115394592,"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":0.9817000031471252,"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/computer-science","display_name":"Computer science","score":0.824059784412384},{"id":"https://openalex.org/keywords/homomorphic-encryption","display_name":"Homomorphic encryption","score":0.70567387342453},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6562610268592834},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5840712189674377},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.5529001951217651},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.5390855669975281},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.537045419216156},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5236829519271851},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4742124378681183},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45000600814819336},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4398251175880432},{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.371682345867157},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.10103267431259155}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.824059784412384},{"id":"https://openalex.org/C158338273","wikidata":"https://www.wikidata.org/wiki/Q2154943","display_name":"Homomorphic encryption","level":3,"score":0.70567387342453},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6562610268592834},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5840712189674377},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.5529001951217651},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.5390855669975281},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.537045419216156},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5236829519271851},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4742124378681183},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45000600814819336},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4398251175880432},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.371682345867157},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.10103267431259155},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/infocom53939.2023.10228895","is_oa":false,"landing_page_url":"https://doi.org/10.1109/infocom53939.2023.10228895","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320320766","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W179458199","https://openalex.org/W1661405579","https://openalex.org/W2039666939","https://openalex.org/W2041779820","https://openalex.org/W2083528810","https://openalex.org/W2101267652","https://openalex.org/W2102201073","https://openalex.org/W2127658298","https://openalex.org/W2152799677","https://openalex.org/W2156483112","https://openalex.org/W2253609413","https://openalex.org/W2727102647","https://openalex.org/W2773194476","https://openalex.org/W2951059495","https://openalex.org/W2951732061","https://openalex.org/W2963828549","https://openalex.org/W2996786840","https://openalex.org/W3035089687","https://openalex.org/W3041966875","https://openalex.org/W3042785565","https://openalex.org/W3126353764","https://openalex.org/W3154335119","https://openalex.org/W3164712068","https://openalex.org/W3176798257","https://openalex.org/W3193972328","https://openalex.org/W3206845050","https://openalex.org/W4206504654","https://openalex.org/W4210968720","https://openalex.org/W4285404750","https://openalex.org/W4287704116","https://openalex.org/W4289533960","https://openalex.org/W4318619660","https://openalex.org/W4328006301","https://openalex.org/W6678992168","https://openalex.org/W6682557032","https://openalex.org/W6728757088","https://openalex.org/W6738768603","https://openalex.org/W6739891508","https://openalex.org/W6745499552","https://openalex.org/W6746388805","https://openalex.org/W6759872529","https://openalex.org/W6771884525","https://openalex.org/W6780910697","https://openalex.org/W6781119572","https://openalex.org/W6789707170"],"related_works":["https://openalex.org/W3204184292","https://openalex.org/W3176564347","https://openalex.org/W2355833770","https://openalex.org/W1985458517","https://openalex.org/W3031039437","https://openalex.org/W183202219","https://openalex.org/W3095877357","https://openalex.org/W2072565696","https://openalex.org/W4392660679","https://openalex.org/W2956355137"],"abstract_inverted_index":{"Vertical":[0],"Federated":[1,86],"Learning":[2],"(VFL)":[3],"enables":[4],"multiple":[5],"data":[6,20],"owners,":[7],"each":[8],"holding":[9],"a":[10,25,97,107,119,127],"different":[11],"subset":[12],"of":[13,19,57,67,96,106,169,173],"features":[14,59,69,175],"about":[15],"largely":[16],"overlapping":[17],"sets":[18],"sample(s),":[21],"to":[22,34,70,101],"jointly":[23],"train":[24],"useful":[26,68],"global":[27,180],"model.":[28],"Feature":[29,90],"selection":[30,172],"(FS)":[31],"is":[32,37],"important":[33],"VFL.":[35],"It":[36,94],"still":[38],"an":[39],"open":[40],"research":[41],"problem":[42],"as":[43,176,178],"existing":[44,165],"FS":[45],"works":[46],"designed":[47],"for":[48,76],"VFL":[49],"either":[50],"assumes":[51],"prior":[52,61],"knowledge":[53,62],"on":[54,63,133,154],"the":[55,64,85,104,147,150],"number":[56],"noisy":[58],"or":[60],"post-training":[65],"threshold":[66],"be":[71],"selected,":[72,110],"making":[73],"them":[74],"unsuitable":[75],"practical":[77],"applications.":[78],"To":[79,122],"bridge":[80],"this":[81],"gap,":[82],"we":[83,125],"propose":[84,126],"Stochastic":[87],"Dual-Gate":[88],"based":[89,132],"Selection":[91],"(FedSDG-FS)":[92],"approach.":[93],"consists":[95],"Gaussian":[98],"stochastic":[99],"dual-gate":[100],"efficiently":[102],"approximate":[103],"probability":[105],"feature":[108,128],"being":[109],"with":[111,141,182],"privacy":[112],"protection":[113],"through":[114],"Partially":[115],"Homomorphic":[116],"Encryption":[117],"without":[118],"trusted":[120],"third-party.":[121],"reduce":[123],"overhead,":[124],"importance":[129],"initialization":[130],"method":[131],"Gini":[134],"impurity,":[135],"which":[136],"can":[137],"accomplish":[138],"its":[139],"goals":[140],"only":[142],"two":[143],"parameter":[144],"transmissions":[145],"between":[146],"server":[148],"and":[149,157],"clients.":[151],"Extensive":[152],"experiments":[153],"both":[155],"synthetic":[156],"real-world":[158],"datasets":[159],"show":[160],"that":[161],"FedSDG-FS":[162],"significantly":[163],"outperforms":[164],"approaches":[166],"in":[167],"terms":[168],"achieving":[170],"accurate":[171],"high-quality":[174],"well":[177],"building":[179],"models":[181],"improved":[183],"performance.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}