{"id":"https://openalex.org/W4310902650","doi":"https://doi.org/10.1109/itw54588.2022.9965819","title":"Seeded Database Matching Under Noisy Column Repetitions","display_name":"Seeded Database Matching Under Noisy Column Repetitions","publication_year":2022,"publication_date":"2022-11-01","ids":{"openalex":"https://openalex.org/W4310902650","doi":"https://doi.org/10.1109/itw54588.2022.9965819"},"language":"en","primary_location":{"id":"doi:10.1109/itw54588.2022.9965819","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itw54588.2022.9965819","pdf_url":null,"source":{"id":"https://openalex.org/S4363606450","display_name":"2022 IEEE Information Theory Workshop (ITW)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Information Theory Workshop (ITW)","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/A5035079995","display_name":"Serhat Bakirtas","orcid":"https://orcid.org/0000-0001-6192-9006"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Serhat Bakirtas","raw_affiliation_strings":["NYU Tandon School of Engineering"],"affiliations":[{"raw_affiliation_string":"NYU Tandon School of Engineering","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084526367","display_name":"Elza Erkip","orcid":"https://orcid.org/0000-0001-8718-8648"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Elza Erkip","raw_affiliation_strings":["NYU Tandon School of Engineering"],"affiliations":[{"raw_affiliation_string":"NYU Tandon School of Engineering","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5035079995"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8315,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.74585219,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"386","last_page":"391"},"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":0.9991000294685364,"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":0.9947999715805054,"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/obfuscation","display_name":"Obfuscation","score":0.9059700965881348},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7928673624992371},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.7773381471633911},{"id":"https://openalex.org/keywords/column","display_name":"Column (typography)","score":0.685706377029419},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6446354389190674},{"id":"https://openalex.org/keywords/logarithm","display_name":"Logarithm","score":0.5548014640808105},{"id":"https://openalex.org/keywords/synchronization","display_name":"Synchronization (alternating current)","score":0.5507201552391052},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5155889391899109},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4630435109138489},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.39966267347335815},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15083187818527222},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.09798172116279602},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08906707167625427}],"concepts":[{"id":"https://openalex.org/C40305131","wikidata":"https://www.wikidata.org/wiki/Q2616305","display_name":"Obfuscation","level":2,"score":0.9059700965881348},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7928673624992371},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.7773381471633911},{"id":"https://openalex.org/C2780551164","wikidata":"https://www.wikidata.org/wiki/Q2306599","display_name":"Column (typography)","level":3,"score":0.685706377029419},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6446354389190674},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.5548014640808105},{"id":"https://openalex.org/C2778562939","wikidata":"https://www.wikidata.org/wiki/Q1298791","display_name":"Synchronization (alternating current)","level":3,"score":0.5507201552391052},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5155889391899109},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4630435109138489},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.39966267347335815},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15083187818527222},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.09798172116279602},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08906707167625427},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itw54588.2022.9965819","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itw54588.2022.9965819","pdf_url":null,"source":{"id":"https://openalex.org/S4363606450","display_name":"2022 IEEE Information Theory Workshop (ITW)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Information Theory Workshop (ITW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6299999952316284,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"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/W68542029","https://openalex.org/W1975937116","https://openalex.org/W2052858361","https://openalex.org/W2103012681","https://openalex.org/W2125396897","https://openalex.org/W2135930857","https://openalex.org/W2195256693","https://openalex.org/W2478708596","https://openalex.org/W2557607105","https://openalex.org/W2918516027","https://openalex.org/W2962832292","https://openalex.org/W2963143232","https://openalex.org/W2963365826","https://openalex.org/W2963551335","https://openalex.org/W2977090993","https://openalex.org/W3030897411","https://openalex.org/W3099827099","https://openalex.org/W3161217554","https://openalex.org/W3196815013","https://openalex.org/W4206709057","https://openalex.org/W4310902650","https://openalex.org/W4323521191","https://openalex.org/W6730185109","https://openalex.org/W6760396110","https://openalex.org/W6837877395"],"related_works":["https://openalex.org/W4224216661","https://openalex.org/W3210347767","https://openalex.org/W98994209","https://openalex.org/W67940504","https://openalex.org/W2066014542","https://openalex.org/W2024170198","https://openalex.org/W2152144666","https://openalex.org/W1819617256","https://openalex.org/W4308699695","https://openalex.org/W2596984206"],"abstract_inverted_index":{"The":[0],"re-identification":[1],"or":[2,52],"de-anonymization":[3],"of":[4,25,37,50,59,78,122,142,155],"users":[5],"from":[6,56],"anonymized":[7,156],"data":[8,15],"through":[9],"matching":[10,77,101,140,144],"with":[11],"publicly-available":[12],"correlated":[13],"user":[14],"has":[16],"raised":[17],"privacy":[18,42],"concerns,":[19],"leading":[20],"to":[21,29,118],"the":[22,38,48,57,76,113,120,138],"complementary":[23],"measure":[24],"obfuscation":[26,51,70],"in":[27,47,112],"addition":[28],"anonymization.":[30],"Recent":[31],"research":[32],"provides":[33],"a":[34,65,108],"fundamental":[35],"understanding":[36],"conditions":[39,98],"under":[40,80,145],"which":[41],"attacks":[43],"are":[44,102],"successful,":[45],"either":[46],"presence":[49],"synchronization":[53,72],"errors":[54,73],"stemming":[55],"sampling":[58],"time-indexed":[60,159],"databases.":[61],"This":[62],"paper":[63],"presents":[64],"unified":[66],"framework":[67],"considering":[68],"both":[69],"and":[71,74,88,93,149,157],"investigates":[75],"databases":[79],"noisy":[81,146],"column":[82,147],"repetitions.":[83],"By":[84],"devising":[85],"replica":[86],"detection":[87,91,121],"seeded":[89],"deletion":[90],"algorithms,":[92],"using":[94],"information-theoretic":[95],"tools,":[96],"sufficient":[97,132],"for":[99],"successful":[100],"derived.":[103],"It":[104,126],"is":[105,116,127,134],"shown":[106],"that":[107,130],"seed":[109],"size":[110,115],"logarithmic":[111],"row":[114],"enough":[117],"guarantee":[119],"all":[123],"deleted":[124],"columns.":[125],"also":[128],"proved":[129],"this":[131],"condition":[133],"necessary,":[135],"thus":[136],"characterizing":[137],"database":[139,143],"capacity":[141],"repetitions":[148],"providing":[150],"insights":[151],"on":[152],"privacy-preserving":[153],"publication":[154],"obfuscated":[158],"data.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}