{"id":"https://openalex.org/W4381744430","doi":"https://doi.org/10.1109/cscwd57460.2023.10152831","title":"MIA-FedDL: A Membership Inference Attack against Federated Distillation Learning","display_name":"MIA-FedDL: A Membership Inference Attack against Federated Distillation Learning","publication_year":2023,"publication_date":"2023-05-24","ids":{"openalex":"https://openalex.org/W4381744430","doi":"https://doi.org/10.1109/cscwd57460.2023.10152831"},"language":"en","primary_location":{"id":"doi:10.1109/cscwd57460.2023.10152831","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd57460.2023.10152831","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 26th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","raw_type":"proceedings-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/A5104133804","display_name":"Siqi Liu","orcid":"https://orcid.org/0009-0007-9656-3930"},"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":"Siqi Liu","raw_affiliation_strings":["Southeast University,Nanjing,China","Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Southeast University,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100605495","display_name":"Fang Dong","orcid":"https://orcid.org/0000-0001-6770-326X"},"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":"Fang Dong","raw_affiliation_strings":["Southeast University,Nanjing,China","Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Southeast University,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5104133804"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":0.3503,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63768012,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1148","last_page":"1153"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9855999946594238,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9855999946594238,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9609000086784363,"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/T10270","display_name":"Blockchain Technology Applications and Security","score":0.9293000102043152,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.7539253234863281},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6433765292167664},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.4619157314300537},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42384645342826843},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36758747696876526},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.32107654213905334},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.07122203707695007}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7539253234863281},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6433765292167664},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.4619157314300537},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42384645342826843},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36758747696876526},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.32107654213905334},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.07122203707695007},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cscwd57460.2023.10152831","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd57460.2023.10152831","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 26th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7799999713897705,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320311649","display_name":"Ministry of Education","ror":"https://ror.org/036nq5137"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Federated":[0,30],"learning,":[1],"which":[2],"gathers":[3],"the":[4,23,41,99,120,133],"model":[5],"parameters":[6],"of":[7,27,39,60,122,135],"numerous":[8],"IoT":[9],"devices":[10],"without":[11,125],"accessing":[12],"user":[13,140],"data,":[14],"is":[15,66],"used":[16],"to":[17,69],"train":[18],"high-quality":[19],"models":[20],"and":[21,25,65,102,138],"enhance":[22],"quantity":[24],"quality":[26],"available":[28],"data.":[29],"distillation":[31,88,96,145],"learning":[32,46,57,89,97],"strategies":[33],"are":[34],"suggested":[35],"as":[36],"a":[37,79,86,106,113],"means":[38],"addressing":[40],"difficulties":[42],"associated":[43],"with":[44],"federated":[45,56,87,95,144],"in":[47,85,98,143],"Non-IID":[48,100],"environment.":[49],"However,":[50],"recent":[51],"research":[52],"has":[53],"demonstrated":[54],"that":[55,116],"falls":[58],"short":[59],"providing":[61],"complete":[62],"privacy":[63,121,141],"protection":[64],"still":[67],"open":[68],"malevolent":[70],"attackers\u2019":[71],"inference":[72,83,108],"attacks.":[73],"In":[74],"this":[75],"paper,":[76],"we":[77,104],"investigate":[78],"malicious":[80,114],"attacker\u2019s":[81],"membership":[82,107],"attack":[84,109],"context.":[90],"We":[91],"initially":[92],"concentrate":[93],"on":[94],"environment,":[101],"then":[103],"propose":[105],"technique":[110],"started":[111],"by":[112],"client":[115],"can":[117],"successfully":[118],"infer":[119],"other":[123],"clients":[124],"getting":[126],"more":[127],"information.":[128],"Comprehensive":[129],"experimental":[130],"results":[131],"show":[132],"effectiveness":[134],"our":[136],"MIA-FedDL":[137],"quantify":[139],"leakage":[142],"learning.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}