{"id":"https://openalex.org/W4280534256","doi":"https://doi.org/10.1093/comjnl/bxac080","title":"Evaluating Membership Inference Through Adversarial Robustness","display_name":"Evaluating Membership Inference Through Adversarial Robustness","publication_year":2022,"publication_date":"2022-08-24","ids":{"openalex":"https://openalex.org/W4280534256","doi":"https://doi.org/10.1093/comjnl/bxac080"},"language":"en","primary_location":{"id":"doi:10.1093/comjnl/bxac080","is_oa":false,"landing_page_url":"https://doi.org/10.1093/comjnl/bxac080","pdf_url":null,"source":{"id":"https://openalex.org/S44643521","display_name":"The Computer Journal","issn_l":"0010-4620","issn":["0010-4620","1460-2067"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Computer Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/10072/429965","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032216635","display_name":"Zhaoxi Zhang","orcid":"https://orcid.org/0000-0002-3813-2776"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoxi Zhang","raw_affiliation_strings":["School of Computer and Information Science , Southwest University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Information Science , Southwest University","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015011245","display_name":"Leo Yu Zhang","orcid":"https://orcid.org/0000-0001-9330-2662"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Leo Yu Zhang","raw_affiliation_strings":["School of Information Technology , Deakin University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology , Deakin University","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082273658","display_name":"Xufei Zheng","orcid":"https://orcid.org/0000-0001-8294-8863"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xufei Zheng","raw_affiliation_strings":["School of Computer and Information Science , Southwest University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Information Science , Southwest University","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057919167","display_name":"Bilal Abbasi","orcid":null},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Bilal Hussain Abbasi","raw_affiliation_strings":["School of Information Technology , Deakin University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology , Deakin University","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081287468","display_name":"Shengshan Hu","orcid":"https://orcid.org/0000-0003-0042-9045"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengshan Hu","raw_affiliation_strings":["School of Cyber Science and Engineering , Huazhong University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering , Huazhong University of Science and Technology","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5082273658"],"corresponding_institution_ids":["https://openalex.org/I142108993"],"apc_list":{"value":2635,"currency":"GBP","value_usd":3232},"apc_paid":null,"fwci":2.2195,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.89353847,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"65","issue":"11","first_page":"2969","last_page":"2978"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9883000254631042,"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/inference","display_name":"Inference","score":0.8148305416107178},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.8090630769729614},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7973372936248779},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.694870114326477},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6834673285484314},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6768120527267456},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6327184438705444},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46423664689064026},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.45082589983940125},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44015786051750183},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0716836154460907}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.8148305416107178},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8090630769729614},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7973372936248779},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.694870114326477},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6834673285484314},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6768120527267456},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6327184438705444},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46423664689064026},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.45082589983940125},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44015786051750183},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0716836154460907},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1093/comjnl/bxac080","is_oa":false,"landing_page_url":"https://doi.org/10.1093/comjnl/bxac080","pdf_url":null,"source":{"id":"https://openalex.org/S44643521","display_name":"The Computer Journal","issn_l":"0010-4620","issn":["0010-4620","1460-2067"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Computer Journal","raw_type":"journal-article"},{"id":"pmh:oai:research-repository.griffith.edu.au:10072/429965","is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/429965","pdf_url":null,"source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal article"}],"best_oa_location":{"id":"pmh:oai:research-repository.griffith.edu.au:10072/429965","is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/429965","pdf_url":null,"source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6600000262260437,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W2010365091","https://openalex.org/W2099384706","https://openalex.org/W2111547563","https://openalex.org/W2327501763","https://openalex.org/W2535690855","https://openalex.org/W2559463885","https://openalex.org/W2750384547","https://openalex.org/W2758333670","https://openalex.org/W2790664081","https://openalex.org/W2795435272","https://openalex.org/W2905097561","https://openalex.org/W2930926105","https://openalex.org/W2963857521","https://openalex.org/W2966342255","https://openalex.org/W2986622401","https://openalex.org/W3015735225","https://openalex.org/W3033777149","https://openalex.org/W3102455230","https://openalex.org/W3103245149","https://openalex.org/W3112311055","https://openalex.org/W3118608800","https://openalex.org/W3206937959","https://openalex.org/W3214437258","https://openalex.org/W4234552385","https://openalex.org/W4328028508","https://openalex.org/W6638523607","https://openalex.org/W6743688258","https://openalex.org/W6769910962","https://openalex.org/W6787972765","https://openalex.org/W6794755128"],"related_works":["https://openalex.org/W3208723233","https://openalex.org/W4293054861","https://openalex.org/W4286890323","https://openalex.org/W3208304128","https://openalex.org/W4379255972","https://openalex.org/W4221145470","https://openalex.org/W3187331432","https://openalex.org/W2597787948","https://openalex.org/W4307654699","https://openalex.org/W4280534256"],"abstract_inverted_index":{"Abstract":[0],"The":[1,213],"usage":[2,53],"of":[3,24,35,39,54,94,111,122,125,144,173,178,219],"deep":[4,40,71],"learning":[5,41,72],"is":[6,18,43,222],"being":[7,19],"escalated":[8],"in":[9,21,29,64,73],"many":[10],"applications.":[11,33],"Due":[12],"to":[13,31,44,51,70,88,97,109],"its":[14,116],"outstanding":[15],"performance,":[16],"it":[17],"used":[20,87],"a":[22,92,151],"variety":[23],"security":[25],"and":[26,61,115,164],"privacy-sensitive":[27],"areas":[28],"addition":[30],"conventional":[32],"One":[34],"the":[36,52,74,98,120,142,171,179,195,217],"key":[37],"aspects":[38],"efficacy":[42],"have":[45],"abundant":[46],"data.":[47],"This":[48,103],"trait":[49],"leads":[50],"data":[55,95,113],"which":[56,63],"can":[57,85,104],"be":[58,86,105],"highly":[59],"sensitive":[60],"private,":[62],"turn":[65],"causes":[66],"wariness":[67],"with":[68,107,194],"regard":[69,108],"general":[75],"public.":[76],"Membership":[77],"inference":[78,134,199],"attacks":[79,135],"are":[80],"considered":[81],"lethal":[82],"as":[83],"they":[84],"figure":[89],"out":[90],"whether":[91],"piece":[93],"belongs":[96],"training":[99,112],"dataset":[100],"or":[101],"not.":[102],"problematic":[106],"leakage":[110],"information":[114],"characteristics.":[117],"To":[118],"highlight":[119],"significance":[121],"these":[123],"types":[124],"attacks,":[126],"we":[127],"propose":[128],"an":[129],"enhanced":[130],"methodology":[131],"for":[132,215],"membership":[133,198],"based":[136],"on":[137,159],"adversarial":[138,145,181],"robustness,":[139],"by":[140],"adjusting":[141],"directions":[143],"perturbations":[146],"through":[147,190],"label":[148],"smoothing":[149],"under":[150],"white-box":[152],"setting.":[153],"We":[154],"evaluate":[155],"our":[156,174,192,201],"proposed":[157,202],"method":[158,175,183,203],"three":[160],"datasets:":[161],"Fashion-MNIST,":[162],"CIFAR-10":[163],"CIFAR-100.":[165],"Our":[166],"experimental":[167],"results":[168,218],"reveal":[169],"that":[170,177],"performance":[172,207],"surpasses":[176],"existing":[180],"robustness-based":[182],"when":[184,208],"attacking":[185,209],"normally":[186],"trained":[187,211],"models.":[188,212],"Additionally,":[189],"comparing":[191],"technique":[193],"state-of-the-art":[196],"metric-based":[197],"methods,":[200],"also":[204],"shows":[205],"better":[206],"adversarially":[210],"code":[214],"reproducing":[216],"this":[220],"work":[221],"available":[223],"at":[224],"https://github.com/plll4zzx/Evaluating-Membership-Inference-Through-Adversarial-Robustness.":[225]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
