{"id":"https://openalex.org/W4415366927","doi":"https://doi.org/10.1109/isit63088.2025.11195545","title":"Auditing Privacy of Additive Noise Mechanisms Using Linear Predictive Models","display_name":"Auditing Privacy of Additive Noise Mechanisms Using Linear Predictive Models","publication_year":2025,"publication_date":"2025-06-22","ids":{"openalex":"https://openalex.org/W4415366927","doi":"https://doi.org/10.1109/isit63088.2025.11195545"},"language":null,"primary_location":{"id":"doi:10.1109/isit63088.2025.11195545","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit63088.2025.11195545","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Symposium on Information Theory (ISIT)","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/A5062056144","display_name":"Monica Welfert","orcid":"https://orcid.org/0000-0001-8439-5668"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Monica Welfert","raw_affiliation_strings":["Arizona State University,USA"],"affiliations":[{"raw_affiliation_string":"Arizona State University,USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031088681","display_name":"Nathan Stromberg","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nathan Stromberg","raw_affiliation_strings":["Arizona State University,USA"],"affiliations":[{"raw_affiliation_string":"Arizona State University,USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064392614","display_name":"Mario D\u00edaz","orcid":"https://orcid.org/0000-0002-9321-9815"},"institutions":[{"id":"https://openalex.org/I7868373","display_name":"International Institute for Strategic Studies","ror":"https://ror.org/03jzczt57","country_code":"US","type":"education","lineage":["https://openalex.org/I7868373"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mario Diaz","raw_affiliation_strings":["IIMAS,Mexico"],"affiliations":[{"raw_affiliation_string":"IIMAS,Mexico","institution_ids":["https://openalex.org/I7868373"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051190796","display_name":"James Melbourne","orcid":"https://orcid.org/0000-0002-1263-0961"},"institutions":[{"id":"https://openalex.org/I4210118279","display_name":"Mathematics Research Center","ror":null,"country_code":"MX","type":null,"lineage":["https://openalex.org/I4210118279"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"James Melbourne","raw_affiliation_strings":["CIMAT,Mexico"],"affiliations":[{"raw_affiliation_string":"CIMAT,Mexico","institution_ids":["https://openalex.org/I4210118279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065366998","display_name":"Lalitha Sankar","orcid":"https://orcid.org/0000-0001-8122-5444"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lalitha Sankar","raw_affiliation_strings":["Arizona State University,USA"],"affiliations":[{"raw_affiliation_string":"Arizona State University,USA","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5062056144"],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15408743,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.5741000175476074,"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":0.5741000175476074,"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/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.5162000060081482,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/audit","display_name":"Audit","score":0.7663000226020813},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5691999793052673},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5084999799728394},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4747999906539917},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.3880999982357025},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.38269999623298645},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.38040000200271606},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.3677000105381012}],"concepts":[{"id":"https://openalex.org/C199521495","wikidata":"https://www.wikidata.org/wiki/Q181487","display_name":"Audit","level":2,"score":0.7663000226020813},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5964999794960022},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5691999793052673},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5084999799728394},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4747999906539917},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4480000138282776},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39629998803138733},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3880999982357025},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.38269999623298645},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.38040000200271606},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.3677000105381012},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.3637000024318695},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.35280001163482666},{"id":"https://openalex.org/C6802819","wikidata":"https://www.wikidata.org/wiki/Q1072174","display_name":"Linear system","level":2,"score":0.3458000123500824},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.3353999853134155},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33070001006126404},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.33059999346733093},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3294999897480011},{"id":"https://openalex.org/C206654554","wikidata":"https://www.wikidata.org/wiki/Q5374247","display_name":"Empirical measure","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30809998512268066},{"id":"https://openalex.org/C166052673","wikidata":"https://www.wikidata.org/wiki/Q83021","display_name":"Empirical evidence","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C99221444","wikidata":"https://www.wikidata.org/wiki/Q1532069","display_name":"Private information retrieval","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.2831999957561493},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.2660999894142151},{"id":"https://openalex.org/C19619285","wikidata":"https://www.wikidata.org/wiki/Q196372","display_name":"Observational error","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.2538999915122986},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit63088.2025.11195545","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit63088.2025.11195545","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1179960849","display_name":null,"funder_award_id":"CIF-1901243,CIF-2007688,CIF-2312666,SCH-2205080","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1557486844","https://openalex.org/W1989151402","https://openalex.org/W2111616148","https://openalex.org/W2123469175","https://openalex.org/W2166116275","https://openalex.org/W2167136065","https://openalex.org/W2603702422","https://openalex.org/W2734457061","https://openalex.org/W2744172881","https://openalex.org/W2787894218","https://openalex.org/W2962793079","https://openalex.org/W2963062476","https://openalex.org/W2963608890","https://openalex.org/W2963634943","https://openalex.org/W2968437089","https://openalex.org/W2971533378","https://openalex.org/W2976849337","https://openalex.org/W3154109599","https://openalex.org/W3196446948","https://openalex.org/W3198266282","https://openalex.org/W3198460646","https://openalex.org/W4205228770","https://openalex.org/W4289655416","https://openalex.org/W4407461406","https://openalex.org/W4408181569"],"related_works":[],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,47,52,104],"privacy":[3,111],"auditing":[4,14,64,100,112],"framework":[5,101],"using":[6],"minimum":[7],"mean-squared":[8],"error":[9,54],"(MMSE)":[10],"estimation":[11],"and":[12,51,59,78,87],"linear":[13,63,82,98],"models.":[15,90],"Our":[16],"approach":[17],"provides":[18],"theoretical":[19,115],"lower":[20],"bounds":[21,38,70],"on":[22],"the":[23,43,76],"true":[24],"MMSE":[25,45],"of":[26,33,42,73],"inferring":[27],"sensitive":[28],"features":[29],"from":[30],"noisy":[31],"observations":[32],"other":[34],"correlated":[35],"features.":[36],"The":[37],"are":[39],"in":[40],"terms":[41],"empirical":[44,92],"under":[46],"restricted":[48],"hypothesis":[49],"class":[50],"decomposable":[53],"term":[55],"capturing":[56],"finite":[57],"sample":[58],"approximation":[60],"effects.":[61],"For":[62],"models,":[65],"we":[66,94],"derive":[67],"order-optimal":[68],"closed-form":[69],"for":[71,109],"classes":[72],"relationships":[74],"between":[75],"private":[77],"non-private":[79],"features,":[80],"including":[81],"mappings,":[83],"binary":[84],"symmetric":[85],"channels,":[86],"class-conditional":[88],"Gaussian":[89],"Through":[91],"evaluation,":[93],"demonstrate":[95],"that":[96,113],"our":[97],"model-based":[99],"serves":[102],"as":[103],"powerful":[105],"yet":[106],"tractable":[107],"tool":[108],"MMSE-based":[110],"balances":[114],"guarantees":[116],"with":[117],"practical":[118],"efficiency.":[119]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-21T00:00:00"}
