{"id":"https://openalex.org/W4306317490","doi":"https://doi.org/10.1145/3511808.3557546","title":"An Empirical Study on the Membership Inference Attack against Tabular Data Synthesis Models","display_name":"An Empirical Study on the Membership Inference Attack against Tabular Data Synthesis Models","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306317490","doi":"https://doi.org/10.1145/3511808.3557546"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557546","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557546","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","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/A5018858017","display_name":"Jihyeon Hyeong","orcid":null},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jihyeon Hyeong","raw_affiliation_strings":["Northwestern University, Evanston, IL, USA"],"affiliations":[{"raw_affiliation_string":"Northwestern University, Evanston, IL, USA","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100612966","display_name":"Jayoung Kim","orcid":"https://orcid.org/0000-0003-2946-8478"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jayoung Kim","raw_affiliation_strings":["Yonsei University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067253588","display_name":"Noseong Park","orcid":"https://orcid.org/0000-0002-1268-840X"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Noseong Park","raw_affiliation_strings":["Yonsei University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010727123","display_name":"Sushil Jajodia","orcid":"https://orcid.org/0000-0003-3210-558X"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sushil Jajodia","raw_affiliation_strings":["George Mason University, Fairfax, VA, USA"],"affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5018858017"],"corresponding_institution_ids":["https://openalex.org/I111979921"],"apc_list":null,"apc_paid":null,"fwci":1.252,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.81939587,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4064","last_page":"4068"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9925000071525574,"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":0.9839000105857849,"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":0.800972044467926},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7361443042755127},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.617689847946167},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5681685209274292},{"id":"https://openalex.org/keywords/information-leakage","display_name":"Information leakage","score":0.5007472038269043},{"id":"https://openalex.org/keywords/attack-model","display_name":"Attack model","score":0.496631920337677},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4525033235549927},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4371710419654846},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4243602752685547},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40927913784980774},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3587656617164612},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3456663489341736},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.10729661583900452}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.800972044467926},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7361443042755127},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.617689847946167},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5681685209274292},{"id":"https://openalex.org/C2779201187","wikidata":"https://www.wikidata.org/wiki/Q2775060","display_name":"Information leakage","level":2,"score":0.5007472038269043},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.496631920337677},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4525033235549927},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4371710419654846},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4243602752685547},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40927913784980774},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3587656617164612},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3456663489341736},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.10729661583900452},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3511808.3557546","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557546","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1491523329","https://openalex.org/W1506806321","https://openalex.org/W2048463754","https://openalex.org/W2119067110","https://openalex.org/W2473418344","https://openalex.org/W2531563875","https://openalex.org/W2535690855","https://openalex.org/W2806276686","https://openalex.org/W2898851980","https://openalex.org/W2961396908","https://openalex.org/W2965527189","https://openalex.org/W3071470454","https://openalex.org/W3106873467","https://openalex.org/W4205228770","https://openalex.org/W4238395336","https://openalex.org/W4287704273","https://openalex.org/W4306317490","https://openalex.org/W6657138077","https://openalex.org/W6824583106"],"related_works":["https://openalex.org/W3038283795","https://openalex.org/W2604501336","https://openalex.org/W3206966921","https://openalex.org/W4296973715","https://openalex.org/W3093310219","https://openalex.org/W4387193529","https://openalex.org/W3101646702","https://openalex.org/W2801655275","https://openalex.org/W4214858327","https://openalex.org/W4383747975"],"abstract_inverted_index":{"Tabular":[0],"data":[1,38,50,64,101,110],"typically":[2],"contains":[3],"private":[4],"and":[5,25,52,120,124,152],"important":[6],"information;":[7],"thus,":[8],"precautions":[9],"must":[10],"be":[11],"taken":[12],"before":[13],"they":[14,45],"are":[15,65],"shared":[16],"with":[17],"others.":[18],"Although":[19],"several":[20],"methods":[21],"(e.g.,":[22],"differential":[23],"privacy":[24],"k-anonymity)":[26],"have":[27,41],"been":[28],"proposed":[29],"to":[30,67,81,140],"prevent":[31],"information":[32],"leakage,":[33],"in":[34,96],"recent":[35,55],"years,":[36],"tabular":[37,100,109],"synthesis":[39,85,111],"models":[40,61,112,157],"become":[42],"popular":[43,145],"because":[44],"can":[46,73,131,154,168],"well":[47,143],"trade-off":[48],"between":[49],"utility":[51],"privacy.":[53],"However,":[54],"research":[56],"has":[57],"shown":[58],"that":[59,126,165],"generative":[60],"for":[62],"image":[63],"susceptible":[66],"the":[68,92,97,127,156,159,175],"membership":[69,93,128],"inference":[70,94,129],"attack,":[71],"which":[72],"determine":[74],"whether":[75],"a":[76,83],"given":[77],"record":[78],"was":[79],"used":[80],"train":[82],"victim":[84],"model.":[86],"In":[87],"this":[88,171],"paper,":[89],"we":[90],"investigate":[91],"attack":[95,115,130],"context":[98],"of":[99],"synthesis.":[102],"We":[103,136],"conduct":[104,138],"experiments":[105,139],"on":[106],"4":[107],"state-of-the-art":[108],"under":[113],"two":[114,144],"scenarios":[116],"(i.e.,":[117],"one":[118,121],"black-box":[119],"white-box":[122],"attack),":[123],"find":[125],"seriously":[132],"jeopardize":[133],"these":[134],"models.":[135],"next":[137],"evaluate":[141],"how":[142],"differentially-private":[146],"deep":[147],"learning":[148],"training":[149],"algorithms,":[150],"DP-SGD":[151],"DP-GAN,":[153],"protect":[155],"against":[158],"attack.":[160],"Our":[161],"key":[162],"finding":[163],"is":[164],"both":[166],"algorithms":[167],"largely":[169],"alleviate":[170],"threat":[172],"by":[173],"sacrificing":[174],"generation":[176],"quality.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-10-10T00:00:00"}
