{"id":"https://openalex.org/W4318242821","doi":"https://doi.org/10.1109/tmi.2023.3239391","title":"Do Gradient Inversion Attacks Make Federated Learning Unsafe?","display_name":"Do Gradient Inversion Attacks Make Federated Learning Unsafe?","publication_year":2023,"publication_date":"2023-01-24","ids":{"openalex":"https://openalex.org/W4318242821","doi":"https://doi.org/10.1109/tmi.2023.3239391","pmid":"https://pubmed.ncbi.nlm.nih.gov/37021996"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2023.3239391","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2023.3239391","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5028525720","display_name":"Ali Hatamizadeh","orcid":"https://orcid.org/0000-0002-5349-1996"},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ali Hatamizadeh","raw_affiliation_strings":["NVIDIA, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108868459","display_name":"Hongxu Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongxu Yin","raw_affiliation_strings":["NVIDIA, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066945976","display_name":"Pavlo Molchanov","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pavlo Molchanov","raw_affiliation_strings":["NVIDIA, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002997328","display_name":"Andriy Myronenko","orcid":"https://orcid.org/0000-0001-8713-7031"},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andriy Myronenko","raw_affiliation_strings":["NVIDIA, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100461989","display_name":"Wenqi Li","orcid":"https://orcid.org/0000-0003-1081-2830"},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenqi Li","raw_affiliation_strings":["NVIDIA, Santa Clara, CA, USA"],"raw_orcid":"https://orcid.org/0000-0003-1081-2830","affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014336548","display_name":"Prerna Dogra","orcid":"https://orcid.org/0000-0002-1842-1968"},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Prerna Dogra","raw_affiliation_strings":["NVIDIA, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066604966","display_name":"Andrew Feng","orcid":"https://orcid.org/0000-0002-1675-745X"},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew Feng","raw_affiliation_strings":["NVIDIA, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031887767","display_name":"Mona G. Flores","orcid":"https://orcid.org/0000-0002-7362-3044"},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mona G Flores","raw_affiliation_strings":["NVIDIA, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056503617","display_name":"Jan Kautz","orcid":"https://orcid.org/0000-0002-8830-429X"},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jan Kautz","raw_affiliation_strings":["NVIDIA, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052339079","display_name":"Daguang Xu","orcid":"https://orcid.org/0000-0002-4621-881X"},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daguang Xu","raw_affiliation_strings":["NVIDIA, Santa Clara, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-4621-881X","affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043710204","display_name":"Holger R. Roth","orcid":"https://orcid.org/0000-0002-3662-8743"},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Holger R. Roth","raw_affiliation_strings":["NVIDIA, Santa Clara, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-3662-8743","affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210127875"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210127875"],"apc_list":null,"apc_paid":null,"fwci":15.5843,"has_fulltext":false,"cited_by_count":119,"citation_normalized_percentile":{"value":0.99394608,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"42","issue":"7","first_page":"2044","last_page":"2056"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9980999827384949,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.9469000101089478,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8191094398498535},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.6637694239616394},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.6635886430740356},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.6470421552658081},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.5453041791915894},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5330342650413513},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4835643470287323},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.4822978973388672},{"id":"https://openalex.org/keywords/leakage","display_name":"Leakage (economics)","score":0.4640568494796753},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45287004113197327},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4510939121246338},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4380664527416229},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4198530614376068},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.39731937646865845},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.10102453827857971}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8191094398498535},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6637694239616394},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.6635886430740356},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.6470421552658081},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.5453041791915894},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5330342650413513},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4835643470287323},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.4822978973388672},{"id":"https://openalex.org/C2777042071","wikidata":"https://www.wikidata.org/wiki/Q6509304","display_name":"Leakage (economics)","level":2,"score":0.4640568494796753},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45287004113197327},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4510939121246338},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4380664527416229},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4198530614376068},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.39731937646865845},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.10102453827857971},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","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},{"id":"https://openalex.org/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008490","descriptor_name":"Medical Informatics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008490","descriptor_name":"Medical Informatics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008490","descriptor_name":"Medical Informatics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008490","descriptor_name":"Medical Informatics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D018907","descriptor_name":"Privacy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018907","descriptor_name":"Privacy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018907","descriptor_name":"Privacy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018907","descriptor_name":"Privacy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/tmi.2023.3239391","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2023.3239391","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:37021996","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37021996","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on medical imaging","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":81,"referenced_works":["https://openalex.org/W1836465849","https://openalex.org/W1873763122","https://openalex.org/W2051267297","https://openalex.org/W2053637704","https://openalex.org/W2108598243","https://openalex.org/W2133665775","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2473418344","https://openalex.org/W2591882872","https://openalex.org/W2611650229","https://openalex.org/W2767079719","https://openalex.org/W2897230576","https://openalex.org/W2912213068","https://openalex.org/W2949619619","https://openalex.org/W2963446712","https://openalex.org/W2963506795","https://openalex.org/W2964162474","https://openalex.org/W2970408908","https://openalex.org/W2979637109","https://openalex.org/W3006555759","https://openalex.org/W3012501605","https://openalex.org/W3013068160","https://openalex.org/W3013277995","https://openalex.org/W3033511014","https://openalex.org/W3034957837","https://openalex.org/W3038022836","https://openalex.org/W3038932755","https://openalex.org/W3043303805","https://openalex.org/W3045674654","https://openalex.org/W3048252189","https://openalex.org/W3086590218","https://openalex.org/W3088370288","https://openalex.org/W3091267000","https://openalex.org/W3098488418","https://openalex.org/W3101156210","https://openalex.org/W3103323991","https://openalex.org/W3128304793","https://openalex.org/W3129603732","https://openalex.org/W3135057764","https://openalex.org/W3165750456","https://openalex.org/W3172312230","https://openalex.org/W3175192640","https://openalex.org/W3176741412","https://openalex.org/W3193581700","https://openalex.org/W3199945025","https://openalex.org/W3200636593","https://openalex.org/W3200840849","https://openalex.org/W4226082367","https://openalex.org/W4287670603","https://openalex.org/W4287720355","https://openalex.org/W4287822453","https://openalex.org/W4288346602","https://openalex.org/W4289117554","https://openalex.org/W4294106961","https://openalex.org/W4299283926","https://openalex.org/W4307323645","https://openalex.org/W4318619660","https://openalex.org/W4393547791","https://openalex.org/W6638667902","https://openalex.org/W6697006807","https://openalex.org/W6728757088","https://openalex.org/W6755616390","https://openalex.org/W6757288671","https://openalex.org/W6759238902","https://openalex.org/W6763192249","https://openalex.org/W6764838729","https://openalex.org/W6768735801","https://openalex.org/W6771536673","https://openalex.org/W6773817997","https://openalex.org/W6773976177","https://openalex.org/W6775482175","https://openalex.org/W6775563089","https://openalex.org/W6780438843","https://openalex.org/W6780897730","https://openalex.org/W6782269965","https://openalex.org/W6785686501","https://openalex.org/W6789305514","https://openalex.org/W6801274487","https://openalex.org/W6803014478","https://openalex.org/W6846254380"],"related_works":["https://openalex.org/W4366307888","https://openalex.org/W4286971788","https://openalex.org/W3199340467","https://openalex.org/W3157608626","https://openalex.org/W3132132958","https://openalex.org/W4322580403","https://openalex.org/W3193217249","https://openalex.org/W4321612632","https://openalex.org/W4280591108","https://openalex.org/W3021849752"],"abstract_inverted_index":{"Federated":[0],"learning":[1],"(FL)":[2],"allows":[3],"the":[4,38,50,56,71,79,84,133],"collaborative":[5],"training":[6,59,81],"of":[7,31,40,52,58,123],"AI":[8],"models":[9],"without":[10],"needing":[11],"to":[12,105],"share":[13],"raw":[14],"data.":[15,60],"This":[16],"capability":[17],"makes":[18],"it":[19],"especially":[20],"interesting":[21],"for":[22,97],"healthcare":[23],"applications":[24],"where":[25,78],"patient":[26],"and":[27,89,107,129,143],"data":[28,110,125],"privacy":[29],"is":[30,116],"utmost":[32],"concern.":[33],"However,":[34],"recent":[35],"works":[36,96],"on":[37,147],"inversion":[39],"deep":[41],"neural":[42],"networks":[43],"from":[44],"model":[45,144],"gradients":[46],"raised":[47],"concerns":[48],"about":[49],"security":[51],"FL":[53,76,128],"in":[54,70,75,112,127],"preventing":[55],"leakage":[57,111,126],"In":[61],"this":[62],"work,":[63],"we":[64,101],"show":[65],"that":[66,95],"these":[67],"attacks":[68],"presented":[69],"literature":[72],"are":[73],"impractical":[74],"use-cases":[77],"clients'":[80],"involves":[82],"updating":[83],"Batch":[85],"Normalization":[86],"(BN)":[87],"statistics":[88],"provide":[90],"a":[91,117],"new":[92,103],"baseline":[93],"attack":[94],"such":[98,139],"scenarios.":[99],"Furthermore,":[100],"present":[102],"ways":[104],"measure":[106],"visualize":[108],"potential":[109],"FL.":[113],"Our":[114],"work":[115],"step":[118],"towards":[119],"establishing":[120],"reproducible":[121],"methods":[122],"measuring":[124],"could":[130],"help":[131],"determine":[132],"optimal":[134],"tradeoffs":[135],"between":[136],"privacy-preserving":[137],"techniques,":[138],"as":[140],"differential":[141],"privacy,":[142],"accuracy":[145],"based":[146],"quantifiable":[148],"metrics.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":21},{"year":2025,"cited_by_count":58},{"year":2024,"cited_by_count":27},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-20T07:56:41.581041","created_date":"2025-10-10T00:00:00"}