{"id":"https://openalex.org/W2914662309","doi":"https://doi.org/10.1109/isit.2019.8849392","title":"A Concentration of Measure Approach to Database De-anonymization","display_name":"A Concentration of Measure Approach to Database De-anonymization","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2914662309","doi":"https://doi.org/10.1109/isit.2019.8849392","mag":"2914662309"},"language":"en","primary_location":{"id":"doi:10.1109/isit.2019.8849392","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2019.8849392","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1901.07655","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008196853","display_name":"Farhad Shirani","orcid":"https://orcid.org/0000-0003-1316-3899"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Farhad Shirani","raw_affiliation_strings":["Department of Electrical and Computer Engineering, New York University"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010950688","display_name":"Siddharth Garg","orcid":"https://orcid.org/0000-0002-6158-9512"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siddharth Garg","raw_affiliation_strings":["Department of Electrical and Computer Engineering, New York University"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084526367","display_name":"Elza Erkip","orcid":"https://orcid.org/0000-0001-8718-8648"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Elza Erkip","raw_affiliation_strings":["Department of Electrical and Computer Engineering, New York University"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, New York University","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008196853"],"corresponding_institution_ids":["https://openalex.org/I57206974"],"apc_list":null,"apc_paid":null,"fwci":0.2891,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.64529366,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2748","last_page":"2752"},"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/T10237","display_name":"Cryptography and Data Security","score":0.9994999766349792,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.996399998664856,"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/matching","display_name":"Matching (statistics)","score":0.7944086790084839},{"id":"https://openalex.org/keywords/converse","display_name":"Converse","score":0.6986620426177979},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.6782715916633606},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.6483354568481445},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6077443361282349},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.5389125943183899},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5172865390777588},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4884618818759918},{"id":"https://openalex.org/keywords/distributed-database","display_name":"Distributed database","score":0.47908884286880493},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30855658650398254},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.19713455438613892},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16594141721725464}],"concepts":[{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.7944086790084839},{"id":"https://openalex.org/C2776809875","wikidata":"https://www.wikidata.org/wiki/Q1375963","display_name":"Converse","level":2,"score":0.6986620426177979},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6782715916633606},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.6483354568481445},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6077443361282349},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.5389125943183899},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5172865390777588},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4884618818759918},{"id":"https://openalex.org/C70061542","wikidata":"https://www.wikidata.org/wiki/Q989016","display_name":"Distributed database","level":2,"score":0.47908884286880493},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30855658650398254},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.19713455438613892},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16594141721725464},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/isit.2019.8849392","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2019.8849392","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1901.07655","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1901.07655","pdf_url":"https://arxiv.org/pdf/1901.07655","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2914662309","is_oa":true,"landing_page_url":"https://arxiv.org/abs/1901.07655","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1901.07655","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1901.07655","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1901.07655","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1901.07655","pdf_url":"https://arxiv.org/pdf/1901.07655","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.49000000953674316,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2914662309.pdf","grobid_xml":"https://content.openalex.org/works/W2914662309.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W68542029","https://openalex.org/W1968250327","https://openalex.org/W1975937116","https://openalex.org/W2056339533","https://openalex.org/W2099111195","https://openalex.org/W2109426455","https://openalex.org/W2135930857","https://openalex.org/W2167492639","https://openalex.org/W2195256693","https://openalex.org/W2245073910","https://openalex.org/W2962748040","https://openalex.org/W2962832292","https://openalex.org/W2962991128","https://openalex.org/W2963365826","https://openalex.org/W2963551335","https://openalex.org/W2977090993","https://openalex.org/W3099827099"],"related_works":["https://openalex.org/W2977090993","https://openalex.org/W2467699249","https://openalex.org/W3122255490","https://openalex.org/W2918803565","https://openalex.org/W3089008123","https://openalex.org/W2510641838","https://openalex.org/W1498828284","https://openalex.org/W2113025056","https://openalex.org/W2964305832","https://openalex.org/W2774921216","https://openalex.org/W2952885232","https://openalex.org/W2964336134","https://openalex.org/W2185331285","https://openalex.org/W2912371996","https://openalex.org/W2807099274","https://openalex.org/W2468072979","https://openalex.org/W2921467752","https://openalex.org/W2012318340","https://openalex.org/W3034606471","https://openalex.org/W3006073215"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"matching":[3,48,83,94],"of":[4,31,39,74],"correlated":[5],"high-dimensional":[6],"databases":[7],"is":[8,14,23,59,84],"investigated.":[9],"A":[10],"stochastic":[11],"database":[12,21,47,78,102,114],"model":[13],"considered":[15],"where":[16],"the":[17,20,77,98,101],"correlation":[18],"among":[19],"entries":[22,79,103],"governed":[24],"by":[25],"an":[26],"arbitrary":[27],"joint":[28],"distribution.":[29],"Concentration":[30],"measure":[32],"theorems":[33],"such":[34],"as":[35,109,111],"typicality":[36],"and":[37,50,89,106],"laws":[38],"large":[40],"numbers":[41],"are":[42,64,95,104],"used":[43],"to":[44],"develop":[45],"a":[46,67,72],"scheme":[49],"derive":[51],"necessary":[52,88],"conditions":[53,63,91],"for":[54,80,92],"successful":[55],"matching.":[56],"Furthermore,":[57],"it":[58],"shown":[60],"that":[61],"these":[62],"tight":[65],"through":[66],"converse":[68],"result":[69],"which":[70,81],"characterizes":[71],"set":[73],"distributions":[75],"on":[76],"reliable":[82,93],"not":[85],"possible.":[86],"The":[87],"sufficient":[90],"evaluated":[96],"in":[97],"cases":[99],"when":[100],"independent":[105],"identically":[107],"distributed":[108],"well":[110],"under":[112],"Markovian":[113],"models.":[115]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-14T06:41:57.775601","created_date":"2025-10-10T00:00:00"}
