{"id":"https://openalex.org/W4406138570","doi":"https://doi.org/10.48550/arxiv.2501.02182","title":"AdaMixup: A Dynamic Defense Framework for Membership Inference Attack Mitigation","display_name":"AdaMixup: A Dynamic Defense Framework for Membership Inference Attack Mitigation","publication_year":2025,"publication_date":"2025-01-04","ids":{"openalex":"https://openalex.org/W4406138570","doi":"https://doi.org/10.48550/arxiv.2501.02182"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2501.02182","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2501.02182","pdf_url":"https://arxiv.org/pdf/2501.02182","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2501.02182","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100383008","display_name":"Ying Chen","orcid":"https://orcid.org/0000-0001-7379-5025","observed_orcids":["https://orcid.org/0000-0001-7379-5025","https://orcid.org/0000-0002-1620-9904"]},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chen, Ying","raw_affiliation_strings":["University of Connecticut"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Connecticut","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chen, Jiajing","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chen, Jiajing","raw_affiliation_strings":["Courant Institute , New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Courant Institute , New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060920806","display_name":"Yijie Weng","orcid":"https://orcid.org/0009-0000-4858-2829","observed_orcids":["https://orcid.org/0009-0000-4858-2829"]},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weng, Yijie","raw_affiliation_strings":["Robert H. Smith School of Business , University of Maryland College Park , College Park"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robert H. Smith School of Business , University of Maryland College Park , College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chang, ChiaHua","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chang, ChiaHua","raw_affiliation_strings":["Metropolitan College , Department of Computer science , Boston University e"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Metropolitan College , Department of Computer science , Boston University e","institution_ids":["https://openalex.org/I111088046"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yu, Dezhi","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I2803209242","display_name":"University of California System","ror":"https://ror.org/00pjdza24","country_code":"US","type":"education","lineage":["https://openalex.org/I2803209242"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu, Dezhi","raw_affiliation_strings":["School of Information , University of California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information , University of California","institution_ids":["https://openalex.org/I2803209242"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046029248","display_name":"Guanbiao Lin","orcid":"https://orcid.org/0000-0002-7372-7345","observed_orcids":["https://orcid.org/0000-0002-7372-7345"]},"institutions":[{"id":"https://openalex.org/I2803209242","display_name":"University of California System","ror":"https://ror.org/00pjdza24","country_code":"US","type":"education","lineage":["https://openalex.org/I2803209242"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lin, Guanbiao","raw_affiliation_strings":["School of Information , University of California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information , University of California","institution_ids":["https://openalex.org/I2803209242"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.836899995803833,"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":0.836899995803833,"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":0.1624000072479248,"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/T11424","display_name":"Security and Verification in Computing","score":9.999999747378752e-05,"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/membership-inference-attacks","display_name":"membership inference attacks","score":0.8629999756813049},{"id":"https://openalex.org/keywords/mixup-data-augmentation","display_name":"mixup augmentation","score":0.8009999990463257},{"id":"https://openalex.org/keywords/data-privacy","display_name":"data privacy","score":0.5669999718666077},{"id":"https://openalex.org/keywords/training-data-leakage","display_name":"training data leakage","score":0.5239999890327454},{"id":"https://openalex.org/keywords/deep-learning-privacy","display_name":"deep learning privacy","score":0.5550000071525574},{"id":"https://openalex.org/keywords/model-robustness","display_name":"model robustness","score":0.6309999823570251}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.671654224395752},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.5330575704574585},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47148463129997253},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.3616674542427063},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.344274640083313},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15020963549613953}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2501.02182","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2501.02182","pdf_url":"https://arxiv.org/pdf/2501.02182","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2501.02182","doi":"https://doi.org/10.48550/arxiv.2501.02182","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2501.02182","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2501.02182","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2501.02182","pdf_url":"https://arxiv.org/pdf/2501.02182","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4406138570.pdf","grobid_xml":"https://content.openalex.org/works/W4406138570.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Membership":[0],"inference":[1,59,97],"attacks":[2,60,98],"have":[3],"emerged":[4],"as":[5],"a":[6,22,42,101],"significant":[7],"privacy":[8,76,118],"concern":[9],"in":[10,127],"the":[11,28,33,54,64,74,93,122],"training":[12,29,129],"of":[13,27,95],"deep":[14],"learning":[15],"models,":[16],"where":[17],"attackers":[18],"can":[19],"infer":[20],"whether":[21],"data":[23,117],"point":[24],"was":[25],"part":[26],"set":[30],"based":[31],"on":[32],"model's":[34,55,75],"outputs.":[35],"To":[36],"address":[37],"this":[38],"challenge,":[39],"we":[40],"propose":[41],"novel":[43],"defense":[44],"mechanism,":[45],"AdaMixup.":[46],"AdaMixup":[47,90],"employs":[48],"adaptive":[49],"mixup":[50,65,128],"techniques":[51],"to":[52],"enhance":[53],"robustness":[56],"against":[57],"membership":[58,96],"by":[61],"dynamically":[62],"adjusting":[63],"strategy":[66],"during":[67],"training.":[68],"This":[69,110],"method":[70],"not":[71],"only":[72],"improves":[73],"protection":[77,119],"but":[78],"also":[79],"maintains":[80],"high":[81],"performance.":[82],"Experimental":[83],"results":[84],"across":[85],"multiple":[86],"datasets":[87],"demonstrate":[88],"that":[89],"significantly":[91],"reduces":[92],"risk":[94],"while":[99],"achieving":[100],"favorable":[102],"trade-off":[103],"between":[104],"defensive":[105],"efficiency":[106],"and":[107,120],"model":[108],"accuracy.":[109],"research":[111],"provides":[112],"an":[113],"effective":[114],"solution":[115],"for":[116,124],"lays":[121],"groundwork":[123],"future":[125],"advancements":[126],"methods.":[130]},"counts_by_year":[],"updated_date":"2026-10-07T09:51:55.459714","created_date":"2025-01-08T00:00:00"}