{"id":"https://openalex.org/W4221104046","doi":"https://doi.org/10.1145/3517820","title":"SignDS-FL: Local Differentially Private Federated Learning with Sign-based Dimension Selection","display_name":"SignDS-FL: Local Differentially Private Federated Learning with Sign-based Dimension Selection","publication_year":2022,"publication_date":"2022-03-22","ids":{"openalex":"https://openalex.org/W4221104046","doi":"https://doi.org/10.1145/3517820"},"language":"en","primary_location":{"id":"doi:10.1145/3517820","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3517820","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3517820","source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3517820","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100765610","display_name":"Xue Jiang","orcid":"https://orcid.org/0000-0002-4959-9910"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Xue Jiang","raw_affiliation_strings":["Technical University of Munich, Garching, Germany"],"raw_orcid":"https://orcid.org/0000-0002-4959-9910","affiliations":[{"raw_affiliation_string":"Technical University of Munich, Garching, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102141512","display_name":"Xuebing Zhou","orcid":"https://orcid.org/0000-0001-6883-3453"},"institutions":[{"id":"https://openalex.org/I4210129353","display_name":"Huawei Technologies (Germany)","ror":"https://ror.org/038cdme44","country_code":"DE","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210129353"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Xuebing Zhou","raw_affiliation_strings":["Huawei Technologies D\u00fcsseldorf GmbH, Munich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies D\u00fcsseldorf GmbH, Munich, Germany","institution_ids":["https://openalex.org/I4210129353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063714878","display_name":"Jens Gro\u00dfklags","orcid":"https://orcid.org/0000-0003-1093-1282"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jens Grossklags","raw_affiliation_strings":["Technical University of Munich, Garching, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Munich, Garching, Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.4931,"has_fulltext":true,"cited_by_count":21,"citation_normalized_percentile":{"value":0.90470668,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"13","issue":"5","first_page":"1","last_page":"22"},"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/T10237","display_name":"Cryptography and Data Security","score":0.9623000025749207,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9610000252723694,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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":0.8605608344078064},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.8299499750137329},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.6470158100128174},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5490531921386719},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.504531979560852},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4685531556606293},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3861933946609497}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8605608344078064},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.8299499750137329},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6470158100128174},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5490531921386719},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.504531979560852},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4685531556606293},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3861933946609497},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3517820","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3517820","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3517820","source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3517820","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3517820","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3517820","source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4221104046.pdf","grobid_xml":"https://content.openalex.org/works/W4221104046.grobid-xml"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W1512098439","https://openalex.org/W1544327602","https://openalex.org/W1993116423","https://openalex.org/W2013823004","https://openalex.org/W2053637704","https://openalex.org/W2100659887","https://openalex.org/W2124612670","https://openalex.org/W2147800946","https://openalex.org/W2245160765","https://openalex.org/W2421389337","https://openalex.org/W2473418344","https://openalex.org/W2590796488","https://openalex.org/W2602856279","https://openalex.org/W2604738573","https://openalex.org/W2750384547","https://openalex.org/W2792345738","https://openalex.org/W2902114605","https://openalex.org/W2904190483","https://openalex.org/W2905444686","https://openalex.org/W2913668833","https://openalex.org/W2930926105","https://openalex.org/W2963629772","https://openalex.org/W2963881987","https://openalex.org/W2970606380","https://openalex.org/W2977090839","https://openalex.org/W2979637109","https://openalex.org/W2981759742","https://openalex.org/W2989670708","https://openalex.org/W2990138404","https://openalex.org/W2995022099","https://openalex.org/W3015636663","https://openalex.org/W3016931901","https://openalex.org/W3021654819","https://openalex.org/W3024959708","https://openalex.org/W3027749727","https://openalex.org/W3037913917","https://openalex.org/W3091476023","https://openalex.org/W3103245149","https://openalex.org/W3106378891","https://openalex.org/W3109094166","https://openalex.org/W3127057363","https://openalex.org/W3184192107","https://openalex.org/W3215939271","https://openalex.org/W4205228770","https://openalex.org/W4220928404","https://openalex.org/W4230280967","https://openalex.org/W4289107582","https://openalex.org/W4297853509","https://openalex.org/W6733793881"],"related_works":["https://openalex.org/W3038283795","https://openalex.org/W2604501336","https://openalex.org/W2734500670","https://openalex.org/W2558166297","https://openalex.org/W2315671126","https://openalex.org/W798507144","https://openalex.org/W2964481303","https://openalex.org/W1751413323","https://openalex.org/W2571704763","https://openalex.org/W408992594"],"abstract_inverted_index":{"Federated":[0,68],"Learning":[1,69],"(FL)":[2],"[":[3,97,170,200],"31":[4],"]":[5,99],"is":[6,286],"a":[7,59,101,223,250,260],"decentralized":[8],"learning":[9],"mechanism":[10],"that":[11,30,104,211,304],"has":[12,64],"attracted":[13],"increasing":[14],"attention":[15],"due":[16],"to":[17,67,70,125,188,259],"its":[18],"achievements":[19],"in":[20,198,257],"computational":[21],"efficiency":[22],"and":[23,49,75,119,147,216,234,292,313],"privacy":[24,73,78,145,176],"preservation.":[25],"However,":[26,80,131],"recent":[27],"research":[28],"highlights":[29],"the":[31,45,50,106,122,127,132,142,163,175,179,189,194,220,269,280,309],"original":[32],"FL":[33],"framework":[34,103,133,221,247,285,306],"may":[35,134],"still":[36,135],"reveal":[37],"sensitive":[38],"information":[39],"of":[40,62,92,141,165,225,266,283],"clients\u2019":[41],"local":[42,47,117],"data":[43],"from":[44,85,137],"exchanged":[46],"updates":[48],"global":[51],"model":[52,93,149,214],"parameters.":[53],"Local":[54],"Differential":[55],"Privacy":[56],"(LDP),":[57],"as":[58],"rigorous":[60],"definition":[61],"privacy,":[63],"been":[65],"applied":[66],"provide":[71],"formal":[72],"guarantees":[74],"prevent":[76],"potential":[77],"leakage.":[79],"previous":[81,310],"LDP-FL":[82,311],"solutions":[83,312],"suffer":[84,136],"considerable":[86],"utility":[87,138],"loss":[88,139,256,282],"with":[89,168,228],"an":[90,156,205,315],"increase":[91],"dimensionality.":[94],"Recent":[95],"work":[96],"29":[98,171,201],"proposed":[100],"two-stage":[102],"mitigates":[105],"dimension-dependency":[107],"problem":[108],"by":[109,183],"first":[110],"selecting":[111],"one":[112],"\u201cimportant\u201d":[113],"dimension":[114,123,166],"for":[115,178,268],"each":[116],"update":[118],"then":[120],"perturbing":[121],"value":[124,180],"construct":[126],"sparse":[128],"privatized":[129],"update.":[130],"because":[140],"insufficient":[143],"per-stage":[144],"budget":[146],"slow":[148],"convergence.":[150],"In":[151],"this":[152],"article,":[153],"we":[154,203],"propose":[155,204],"improved":[157],"framework,":[158],"SignDS-FL":[159],",":[160],"which":[161],"shares":[162],"concept":[164],"selection":[167,196],"Reference":[169,199],"],":[172,202],"but":[173],"saves":[174],"cost":[177],"perturbation":[181],"stage":[182],"assigning":[184],"random":[185],"sign":[186],"values":[187],"selected":[190],"dimensions.":[191],"Besides":[192],"using":[193],"single-dimension":[195],"algorithms":[197],"Exponential":[206],"Mechanism-based":[207],"Multi-Dimension":[208],"Selection":[209],"algorithm":[210],"further":[212],"improves":[213],"convergence":[215],"accuracy.":[217],"We":[218],"evaluate":[219],"on":[222,243,277],"number":[224],"real-world":[226],"datasets":[227],"both":[229],"simple":[230],"logistic":[231,240],"regression":[232,241],"models":[233,242],"deep":[235,274],"neural":[236,275],"networks.":[237],"For":[238,272],"training":[239,273],"structured":[244],"datasets,":[245,279],"our":[246,284,305],"yields":[248],"only":[249,295],"\\(":[251,261,289,296],"\\sim":[252,262],"\\)":[253,263,291,298],"1%\u20132%":[254],"accuracy":[255,267,281],"comparison":[258],"5%\u201315%":[264],"decrease":[265],"baseline":[270],"methods.":[271],"networks":[276],"image":[278],"less":[287],"than":[288],"8\\%":[290],"at":[293],"best":[294],"2\\%":[297],".":[299],"Extensive":[300],"experimental":[301],"results":[302],"show":[303],"significantly":[307],"outperforms":[308],"enjoys":[314],"advanced":[316],"utility-privacy":[317],"balance.":[318]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
