{"id":"https://openalex.org/W4408325515","doi":"https://doi.org/10.1109/globecom52923.2024.10901499","title":"A Representation Learning Induced Property Inference Attack on Machine Learning Models for E-Health","display_name":"A Representation Learning Induced Property Inference Attack on Machine Learning Models for E-Health","publication_year":2024,"publication_date":"2024-12-08","ids":{"openalex":"https://openalex.org/W4408325515","doi":"https://doi.org/10.1109/globecom52923.2024.10901499"},"language":"en","primary_location":{"id":"doi:10.1109/globecom52923.2024.10901499","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom52923.2024.10901499","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2024 - 2024 IEEE Global Communications Conference","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/A5068555922","display_name":"Moomal Bukhari","orcid":null},"institutions":[{"id":"https://openalex.org/I114395901","display_name":"University of Nebraska\u2013Lincoln","ror":"https://ror.org/043mer456","country_code":"US","type":"education","lineage":["https://openalex.org/I114395901"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Moomal Bukhari","raw_affiliation_strings":["University of Nebraska-Lincoln,School of Computing,Lincoln,NE,USA,68588"],"affiliations":[{"raw_affiliation_string":"University of Nebraska-Lincoln,School of Computing,Lincoln,NE,USA,68588","institution_ids":["https://openalex.org/I114395901"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066232342","display_name":"Asif Iqbal","orcid":"https://orcid.org/0000-0002-4657-4451"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Asif Iqbal","raw_affiliation_strings":["National University of Singapore,Department of Electrical and Computer Engineering,Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore,Department of Electrical and Computer Engineering,Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008664923","display_name":"Muhammad Naveed Aman","orcid":"https://orcid.org/0000-0002-4629-7589"},"institutions":[{"id":"https://openalex.org/I114395901","display_name":"University of Nebraska\u2013Lincoln","ror":"https://ror.org/043mer456","country_code":"US","type":"education","lineage":["https://openalex.org/I114395901"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Muhammad Naveed Aman","raw_affiliation_strings":["University of Nebraska-Lincoln,School of Computing,Lincoln,NE,USA,68588"],"affiliations":[{"raw_affiliation_string":"University of Nebraska-Lincoln,School of Computing,Lincoln,NE,USA,68588","institution_ids":["https://openalex.org/I114395901"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041189303","display_name":"Biplab Sikdar","orcid":"https://orcid.org/0000-0002-0084-4647"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Biplab Sikdar","raw_affiliation_strings":["National University of Singapore,Department of Electrical and Computer Engineering,Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore,Department of Electrical and Computer Engineering,Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5068555922"],"corresponding_institution_ids":["https://openalex.org/I114395901"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25996331,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2828","last_page":"2833"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.8903999924659729,"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":0.8903999924659729,"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":0.8435999751091003,"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/property","display_name":"Property (philosophy)","score":0.6678209900856018},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6553465723991394},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6549559235572815},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5881600379943848},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5836150050163269},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5729003548622131}],"concepts":[{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.6678209900856018},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6553465723991394},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6549559235572815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5881600379943848},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5836150050163269},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5729003548622131},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"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:10.1109/globecom52923.2024.10901499","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom52923.2024.10901499","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2024 - 2024 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320698","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2535690855","https://openalex.org/W2757528734","https://openalex.org/W2897830718","https://openalex.org/W2962835266","https://openalex.org/W3043638540","https://openalex.org/W3122816307","https://openalex.org/W4205228770","https://openalex.org/W4392956768","https://openalex.org/W6712751967","https://openalex.org/W6748382702","https://openalex.org/W6795882884"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Privacy":[0],"concerns":[1],"have":[2],"become":[3],"increasingly":[4],"prominent":[5],"as":[6,35],"machine":[7],"learning":[8],"(ML)":[9],"models":[10,37],"are":[11,38],"adopted":[12],"in":[13,30,58,128,157],"an":[14],"increasing":[15],"number":[16,198],"of":[17,21,26,51,71,117,122,199],"sectors.":[18],"The":[19],"potential":[20],"unintended":[22],"or":[23],"malicious":[24],"exposure":[25],"sensitive":[27],"data,":[28],"especially":[29],"E-Health":[31],"solutions,":[32],"has":[33,183],"increased":[34],"these":[36],"shared":[39],"and":[40,60,133,142,195],"deployed":[41],"more":[42],"broadly.":[43],"In":[44],"order":[45],"to":[46,76,113,163],"highlight":[47],"the":[48,72,78,83,114,143,149,158,169,178],"important":[49],"problem":[50,116],"property":[52,91,101,173],"inference":[53,92,102,174],"attacks,":[54],"which":[55],"can":[56,152,188],"result":[57],"privacy":[59],"data":[61,131,136,194],"confidentiality":[62],"breaches,":[63],"this":[64],"study":[65],"focuses":[66],"on":[67,90,94,139],"inferring":[68,118],"global":[69],"characteristics":[70],"underlying":[73,155],"datasets":[74,146],"used":[75],"train":[77],"ML":[79,95],"models.":[80,201],"Building":[81],"upon":[82],"intriguing":[84],"work":[85],"by":[86],"Ateniese":[87],"et":[88],"al.":[89],"attacks":[93,175],"models,":[96],"we":[97],"present":[98],"a":[99,110,196],"novel":[100],"attack":[103,151,180],"using":[104],"Variational":[105],"Auto-Encoders":[106],"(VAEs).":[107],"VAEs":[108],"offer":[109],"strong":[111],"answer":[112],"difficult":[115],"dataset":[119,160],"attributes":[120],"because":[121],"their":[123],"reputation":[124],"for":[125],"being":[126],"successful":[127],"modeling":[129],"complex":[130],"distributions":[132],"producing":[134],"synthetic":[135],"samples.":[137],"Experiments":[138],"three":[140],"healthcare":[141],"US":[144],"census":[145],"show":[147],"that":[148,177],"proposed":[150,179],"effectively":[153],"reveal":[154],"patterns":[156],"training":[159,193],"with":[161,168,191],"up":[162],"94.29%":[164],"accuracy.":[165],"A":[166],"comparison":[167],"popular":[170],"meta-classifier":[171],"based":[172],"shows":[176],"not":[181],"only":[182],"better":[184],"success":[185],"rate,":[186],"but":[187],"do":[189],"so":[190],"half":[192],"smaller":[197],"shadow":[200]},"counts_by_year":[],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}
