{"id":"https://openalex.org/W3167193423","doi":"https://doi.org/10.1145/3447548.3467444","title":"Defending Privacy Against More Knowledgeable Membership Inference Attackers","display_name":"Defending Privacy Against More Knowledgeable Membership Inference Attackers","publication_year":2021,"publication_date":"2021-08-13","ids":{"openalex":"https://openalex.org/W3167193423","doi":"https://doi.org/10.1145/3447548.3467444","mag":"3167193423"},"language":"en","primary_location":{"id":"doi:10.1145/3447548.3467444","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining","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/A5113067973","display_name":"Yu Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yu Yin","raw_affiliation_strings":["Zhejiang University, Hang Zhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hang Zhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100451997","display_name":"Ke Chen","orcid":"https://orcid.org/0000-0002-3062-0900"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Chen","raw_affiliation_strings":["Zhejiang University, Hang Zhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hang Zhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103017455","display_name":"Lidan Shou","orcid":"https://orcid.org/0000-0001-8062-8356"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lidan Shou","raw_affiliation_strings":["Zhejiang University, Hang Zhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hang Zhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005160651","display_name":"Gang Chen","orcid":"https://orcid.org/0000-0002-3173-8812"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Chen","raw_affiliation_strings":["Zhejiang University, Hang Zhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hang Zhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5113067973"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":1.1199,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.81990144,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2026","last_page":"2036"},"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":0.9997000098228455,"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":0.9927999973297119,"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/adversary","display_name":"Adversary","score":0.8260594010353088},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7855246067047119},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6669038534164429},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6545268893241882},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.5409378409385681},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.49549543857574463},{"id":"https://openalex.org/keywords/black-box","display_name":"Black box","score":0.4840373396873474},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4410233199596405},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.4402260184288025},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.42252278327941895},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4095214903354645},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3339417576789856},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2400205433368683},{"id":"https://openalex.org/keywords/law","display_name":"Law","score":0.15989470481872559}],"concepts":[{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.8260594010353088},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7855246067047119},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6669038534164429},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6545268893241882},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.5409378409385681},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.49549543857574463},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.4840373396873474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4410233199596405},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.4402260184288025},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.42252278327941895},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4095214903354645},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3339417576789856},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2400205433368683},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.15989470481872559},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3447548.3467444","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W159308319","https://openalex.org/W1552847225","https://openalex.org/W1570212550","https://openalex.org/W1873763122","https://openalex.org/W2011039300","https://openalex.org/W2051267297","https://openalex.org/W2109135024","https://openalex.org/W2110091014","https://openalex.org/W2119874464","https://openalex.org/W2131953535","https://openalex.org/W2136891251","https://openalex.org/W2337093093","https://openalex.org/W2535690855","https://openalex.org/W2595056910","https://openalex.org/W2757528734","https://openalex.org/W2765407302","https://openalex.org/W2795435272","https://openalex.org/W2798657499","https://openalex.org/W2884943453","https://openalex.org/W2903389359","https://openalex.org/W2949819354","https://openalex.org/W2951357534","https://openalex.org/W2952604841","https://openalex.org/W2963378725","https://openalex.org/W2963456518","https://openalex.org/W2983140679","https://openalex.org/W3008580825","https://openalex.org/W3010177353","https://openalex.org/W3018763859","https://openalex.org/W3104406626","https://openalex.org/W3118608800","https://openalex.org/W3137695714","https://openalex.org/W3155551741"],"related_works":["https://openalex.org/W2368605798","https://openalex.org/W2518037665","https://openalex.org/W2348524959","https://openalex.org/W2368049389","https://openalex.org/W2384861574","https://openalex.org/W2952704802","https://openalex.org/W4294565801","https://openalex.org/W2142306706","https://openalex.org/W2477036161","https://openalex.org/W308652608"],"abstract_inverted_index":{"Membership":[0],"Inference":[1],"Attack":[2],"(MIA)":[3],"in":[4,23],"deep":[5],"learning":[6],"is":[7,22,83,166,196],"a":[8,19,24,38,41,113,171],"common":[9],"form":[10],"of":[11,33,56,67,74,123,131,148,193,219],"privacy":[12,75,104,122,225],"attack":[13],"which":[14,99],"aims":[15],"to":[16,63,89,103,202,232],"infer":[17],"whether":[18],"data":[20],"sample":[21],"target":[25,58,97,124],"classifier's":[26],"training":[27],"dataset":[28],"or":[29,40],"not.":[30],"Previous":[31],"studies":[32],"MIA":[34,227],"typically":[35],"tackle":[36],"either":[37],"black-box":[39],"white-box":[42],"adversary":[43,153,207],"model,":[44],"assuming":[45],"an":[46,87,136],"attacker":[47,88,112],"not":[48],"knowing":[49],"(or":[50],"knowing)":[51],"the":[52,57,64,68,72,91,96,128,132,145,149,163],"structure":[53],"and":[54,121,126,158,160,174,188,212,228],"parameters":[55],"classifier":[59],"while":[60],"having":[61],"access":[62],"confidence":[65],"vector":[66],"query":[69],"output.":[70],"With":[71],"popularity":[73],"protection":[76],"methods":[77],"such":[78,111],"as":[79,135],"differential":[80],"privacy,":[81],"it":[82,198],"increasingly":[84],"easier":[85],"for":[86,119,151,223],"obtain":[90],"defense":[92,133,177,234],"method":[93,134],"adopted":[94],"by":[95],"classifier,":[98,125],"poses":[100],"extra":[101],"challenge":[102],"protection.":[105],"In":[106],"this":[107],"paper,":[108],"we":[109,169],"name":[110],"crystal-box":[114],"adversary.":[115],"We":[116,139],"present":[117],"definitions":[118],"utility":[120,187],"formulate":[127],"design":[129],"goal":[130],"optimization":[137,150,164],"problem.":[138],"also":[140],"conduct":[141],"theoretical":[142],"analysis":[143],"on":[144],"respective":[146],"forms":[147],"three":[152,176,206],"models,":[154,208],"namely":[155,209],"black-box,":[156,210],"white-box,":[157,211],"crystal-box,":[159,213],"prove":[161],"that":[162,197],"problem":[165,173],"NP-hard.":[167],"Thereby":[168],"solve":[170],"surrogate":[172],"propose":[175],"methods,":[178],"which,":[179],"if":[180],"used":[181,201],"together,":[182],"can":[183,199],"make":[184],"trade-off":[185],"between":[186],"privacy.":[189],"A":[190],"notable":[191],"advantage":[192],"our":[194,220],"approach":[195,222],"be":[200],"resist":[203],"attacks":[204],"from":[205],"simultaneously.":[214],"Evaluation":[215],"results":[216],"show":[217],"effectiveness":[218],"proposed":[221],"defending":[224],"against":[226],"better":[229],"performance":[230],"compared":[231],"previous":[233],"methods.":[235]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4}],"updated_date":"2026-03-26T15:22:09.906841","created_date":"2025-10-10T00:00:00"}