{"id":"https://openalex.org/W4223972154","doi":"https://doi.org/10.1145/3508398.3519355","title":"A New Bound for Privacy Loss from Bayesian Posterior Sampling","display_name":"A New Bound for Privacy Loss from Bayesian Posterior Sampling","publication_year":2022,"publication_date":"2022-04-14","ids":{"openalex":"https://openalex.org/W4223972154","doi":"https://doi.org/10.1145/3508398.3519355"},"language":"en","primary_location":{"id":"doi:10.1145/3508398.3519355","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3508398.3519355","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twelfth ACM Conference on Data and Application Security and Privacy","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/A5083267250","display_name":"Xingyuan Zhao","orcid":"https://orcid.org/0000-0001-7974-7884"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xingyuan Zhao","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100453123","display_name":"Fang Liu","orcid":"https://orcid.org/0000-0003-3028-5927"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fang Liu","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5083267250"],"corresponding_institution_ids":["https://openalex.org/I107639228"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.02825663,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"346","last_page":"348"},"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/T11720","display_name":"Probability and Risk Models","score":0.9659000039100647,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10237","display_name":"Cryptography and Data Security","score":0.9613999724388123,"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/differential-privacy","display_name":"Differential privacy","score":0.9043309688568115},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.7369515299797058},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6796175837516785},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.583228588104248},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5567997097969055},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.499117374420166},{"id":"https://openalex.org/keywords/private-information-retrieval","display_name":"Private information retrieval","score":0.46544134616851807},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.4464763402938843},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.44426077604293823},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33171606063842773},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3240482211112976},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2779772877693176},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24512630701065063},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.11741578578948975}],"concepts":[{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.9043309688568115},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.7369515299797058},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6796175837516785},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.583228588104248},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5567997097969055},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.499117374420166},{"id":"https://openalex.org/C99221444","wikidata":"https://www.wikidata.org/wiki/Q1532069","display_name":"Private information retrieval","level":2,"score":0.46544134616851807},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.4464763402938843},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.44426077604293823},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33171606063842773},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3240482211112976},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2779772877693176},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24512630701065063},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.11741578578948975},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3508398.3519355","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3508398.3519355","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twelfth ACM Conference on Data and Application Security and Privacy","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1553111043","https://openalex.org/W2096870293","https://openalex.org/W2123820077","https://openalex.org/W2284973007","https://openalex.org/W3122751563","https://openalex.org/W4205228770","https://openalex.org/W4255574744","https://openalex.org/W6657138077"],"related_works":["https://openalex.org/W338126128","https://openalex.org/W2307316789","https://openalex.org/W4293455971","https://openalex.org/W3143560781","https://openalex.org/W1945159329","https://openalex.org/W2388036982","https://openalex.org/W4312206423","https://openalex.org/W2885788239","https://openalex.org/W1597455262","https://openalex.org/W4375958473"],"abstract_inverted_index":{"Differential":[0],"privacy":[1,9,18,54],"(DP)":[2],"is":[3,33,44],"a":[4,13],"state-of-the-art":[5],"concept":[6],"that":[7,91],"formalizes":[8],"guarantees.":[10],"We":[11,51],"derive":[12],"new":[14,31,59],"bound":[15,32,60],"for":[16,39],"the":[17,26,36,48,53,58,75,79],"loss":[19,55],"from":[20,67,86],"releasing":[21],"Bayesian":[22,41,68],"posterior":[23,93],"samples":[24],"in":[25,70],"setting":[27],"of":[28,78],"DP.":[29],"The":[30],"tighter":[34],"than":[35],"existing":[37],"bounds":[38],"common":[40],"models":[42,69],"and":[43,73],"also":[45],"consistent":[46],"with":[47],"likelihood":[49],"principle.":[50],"apply":[52],"quantified":[56],"by":[57],"to":[61,83],"release":[62],"differentially":[63],"private":[64],"synthetic":[65,80],"data":[66,81],"several":[71],"experiments":[72],"show":[74],"improved":[76],"utility":[77],"compared":[82],"those":[84],"generated":[85],"explicitly":[87],"designed":[88],"randomization":[89],"mechanisms":[90],"privatize":[92],"distributions.":[94]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
