{"id":"https://openalex.org/W4402123838","doi":"https://doi.org/10.1109/lsp.2024.3453200","title":"Mutual Gradient Inversion: Unveiling Privacy Risks of Federated Learning on Multi-Modal Signals","display_name":"Mutual Gradient Inversion: Unveiling Privacy Risks of Federated Learning on Multi-Modal Signals","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4402123838","doi":"https://doi.org/10.1109/lsp.2024.3453200"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2024.3453200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2024.3453200","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},"type":"article","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/A5100362316","display_name":"Xuan Liu","orcid":"https://orcid.org/0000-0002-6194-4588"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Xuan Liu","raw_affiliation_strings":["Hong Kong Polytechnic University, Hong Kong, SAR, China"],"affiliations":[{"raw_affiliation_string":"Hong Kong Polytechnic University, Hong Kong, SAR, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015843783","display_name":"Siqi Cai","orcid":"https://orcid.org/0000-0001-7978-8475"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siqi Cai","raw_affiliation_strings":["Wuhan University of Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013965758","display_name":"Renjie He","orcid":"https://orcid.org/0000-0003-2191-1121"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Renjie He","raw_affiliation_strings":["University of Sydney, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"University of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062853168","display_name":"Jingling Yuan","orcid":"https://orcid.org/0000-0001-7924-8620"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingling Yuan","raw_affiliation_strings":["Wuhan University of Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100362316"],"corresponding_institution_ids":["https://openalex.org/I14243506"],"apc_list":null,"apc_paid":null,"fwci":0.7724,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.76110692,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"31","issue":null,"first_page":"2745","last_page":"2749"},"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":0.9965000152587891,"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":0.9945999979972839,"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":0.6685070991516113},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.6614215970039368},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.657829999923706},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.49672847986221313},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.45294684171676636},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3945583701133728},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3099175691604614}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6685070991516113},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.6614215970039368},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.657829999923706},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.49672847986221313},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.45294684171676636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3945583701133728},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3099175691604614},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2024.3453200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2024.3453200","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W2473418344","https://openalex.org/W2533598788","https://openalex.org/W2619383789","https://openalex.org/W2750384547","https://openalex.org/W2963433607","https://openalex.org/W2970408908","https://openalex.org/W3016632787","https://openalex.org/W3021654819","https://openalex.org/W3027749727","https://openalex.org/W3106378891","https://openalex.org/W3118608800","https://openalex.org/W3123459983","https://openalex.org/W3158675315","https://openalex.org/W3213758553","https://openalex.org/W4283220690","https://openalex.org/W4285605911","https://openalex.org/W4295806247","https://openalex.org/W4313639536","https://openalex.org/W4379013917","https://openalex.org/W4379116546","https://openalex.org/W4382318921","https://openalex.org/W4389352407","https://openalex.org/W4390871834","https://openalex.org/W4396949298"],"related_works":["https://openalex.org/W2466816617","https://openalex.org/W1970834875","https://openalex.org/W842936808","https://openalex.org/W3174028392","https://openalex.org/W2000517284","https://openalex.org/W2365318811","https://openalex.org/W2136503713","https://openalex.org/W2375330620","https://openalex.org/W2363755581","https://openalex.org/W2378091429"],"abstract_inverted_index":{"Federated":[0],"Learning":[1],"(FL)":[2],"preserves":[3],"privacy":[4,131,138],"by":[5,100],"training":[6],"a":[7,67],"global":[8],"model":[9],"via":[10],"gradient":[11,52,89,125],"exchange":[12],"between":[13,109],"the":[14,43,87,128,136],"parameter":[15],"server":[16],"and":[17,36,92,134],"local":[18,31],"clients":[19,32],"rather":[20],"than":[21],"raw":[22],"data":[23,39,62,73,115,132,144],"sharing.":[24],"Edge":[25],"devices":[26],"with":[27,96,142],"sensors":[28],"serve":[29],"as":[30],"receiving":[33],"multimodal":[34,38,72,97,114],"signals":[35],"contributing":[37],"for":[40],"training.":[41],"Despite":[42],"privacy-centric":[44],"design":[45],"of":[46,130],"FL,":[47],"it":[48],"remains":[49],"vulnerable":[50],"to":[51,112,146],"leakage":[53,139],"attacks.":[54],"However,":[55],"existing":[56],"studies":[57],"predominantly":[58],"focus":[59],"on":[60],"single-modality":[61,124,147],"recovery":[63,133],"from":[64,116],"gradients,":[65],"leaving":[66],"critical":[68],"research":[69],"void":[70],"in":[71,127],"scenarios.":[74],"In":[75],"this":[76],"letter,":[77],"we":[78],"propose":[79],"<italic":[80],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[81],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">MGIS:":[82],"Mutual":[83],"Gradient":[84],"Inversion":[85],"Strategy</i>,":[86],"first":[88],"inversion":[90],"attack":[91],"defense":[93],"paradigm":[94],"dealing":[95],"data.":[98,148],"Inspired":[99],"knowledge":[101],"distillation,":[102],"MGIS":[103,122],"utilizes":[104],"common":[105],"information":[106],"(e.g.,":[107],"labels)":[108],"different":[110],"modalities":[111],"extract":[113],"gradients.":[117],"Experimental":[118],"results":[119],"demonstrate":[120],"that":[121],"outperforms":[123],"attacks":[126],"quality":[129],"highlight":[135],"increased":[137],"risk":[140],"associated":[141],"multi-modality":[143],"compared":[145]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}