{"id":"https://openalex.org/W2137443981","doi":"https://doi.org/10.1145/1141277.1141417","title":"Towards value disclosure analysis in modeling general databases","display_name":"Towards value disclosure analysis in modeling general databases","publication_year":2006,"publication_date":"2006-04-23","ids":{"openalex":"https://openalex.org/W2137443981","doi":"https://doi.org/10.1145/1141277.1141417","mag":"2137443981"},"language":"en","primary_location":{"id":"doi:10.1145/1141277.1141417","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1141277.1141417","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2006 ACM symposium on Applied computing","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/A5008463509","display_name":"Xintao Wu","orcid":"https://orcid.org/0000-0002-2823-3063"},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xintao Wu","raw_affiliation_strings":["University of North Carolina at Charlotte","University of North Carolina at Charlotte*"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Charlotte","institution_ids":["https://openalex.org/I102149020"]},{"raw_affiliation_string":"University of North Carolina at Charlotte*","institution_ids":["https://openalex.org/I102149020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055813479","display_name":"Songtao Guo","orcid":"https://orcid.org/0000-0001-6741-4871"},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Songtao Guo","raw_affiliation_strings":["University of North Carolina at Charlotte","University of North Carolina at Charlotte*"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Charlotte","institution_ids":["https://openalex.org/I102149020"]},{"raw_affiliation_string":"University of North Carolina at Charlotte*","institution_ids":["https://openalex.org/I102149020"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045050946","display_name":"Yingjiu Li","orcid":"https://orcid.org/0000-0001-8256-6988"},"institutions":[{"id":"https://openalex.org/I79891267","display_name":"Singapore Management University","ror":"https://ror.org/050qmg959","country_code":"SG","type":"education","lineage":["https://openalex.org/I79891267"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yingjiu Li","raw_affiliation_strings":["Singapore Management University"],"affiliations":[{"raw_affiliation_string":"Singapore Management University","institution_ids":["https://openalex.org/I79891267"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008463509"],"corresponding_institution_ids":["https://openalex.org/I102149020"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1301379,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"617","last_page":"621"},"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":0.9901000261306763,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.983299970626831,"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/categorical-variable","display_name":"Categorical variable","score":0.8570556044578552},{"id":"https://openalex.org/keywords/confidentiality","display_name":"Confidentiality","score":0.8523310422897339},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7519322037696838},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.566818356513977},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45627278089523315},{"id":"https://openalex.org/keywords/data-transformation","display_name":"Data transformation","score":0.4439229369163513},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4181232452392578},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.41067802906036377},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.38869509100914},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.370789498090744},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.24175778031349182},{"id":"https://openalex.org/keywords/data-warehouse","display_name":"Data warehouse","score":0.09750121831893921}],"concepts":[{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.8570556044578552},{"id":"https://openalex.org/C71745522","wikidata":"https://www.wikidata.org/wiki/Q2476929","display_name":"Confidentiality","level":2,"score":0.8523310422897339},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7519322037696838},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.566818356513977},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45627278089523315},{"id":"https://openalex.org/C150670458","wikidata":"https://www.wikidata.org/wiki/Q4272815","display_name":"Data transformation","level":3,"score":0.4439229369163513},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4181232452392578},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.41067802906036377},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.38869509100914},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.370789498090744},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.24175778031349182},{"id":"https://openalex.org/C135572916","wikidata":"https://www.wikidata.org/wiki/Q193351","display_name":"Data warehouse","level":2,"score":0.09750121831893921},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1141277.1141417","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1141277.1141417","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2006 ACM symposium on Applied computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7200000286102295}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1505246359","https://openalex.org/W1559017230","https://openalex.org/W1996582596","https://openalex.org/W2062235982","https://openalex.org/W2100440346","https://openalex.org/W2112440119","https://openalex.org/W2113427031","https://openalex.org/W2128906841","https://openalex.org/W2154520446","https://openalex.org/W2164341199","https://openalex.org/W4248358572"],"related_works":["https://openalex.org/W1492261612","https://openalex.org/W2374519217","https://openalex.org/W2012941781","https://openalex.org/W2159704347","https://openalex.org/W2156949561","https://openalex.org/W2393271921","https://openalex.org/W2089133691","https://openalex.org/W2586460527","https://openalex.org/W2041526955","https://openalex.org/W2755827507"],"abstract_inverted_index":{"The":[0],"issue":[1],"of":[2,24,34,78,84,90,116,118],"confidentiality":[3,23],"and":[4,22,86,109],"privacy":[5,21],"in":[6,13,19,114,144],"general":[7],"databases":[8,72],"has":[9],"become":[10],"increasingly":[11],"prominent":[12],"recent":[14],"years.":[15],"A":[16],"key":[17],"element":[18],"preserving":[20],"sensitive":[25],"data":[26,79,132],"is":[27,42,66,101,126,142],"the":[28,32,60,119,123,127],"ability":[29],"to":[30,102,130],"evaluate":[31],"extent":[33],"all":[35,47,135],"potential":[36,112],"disclosure":[37,57,92,113],"for":[38,46,133],"such":[39],"data.":[40],"This":[41],"one":[43],"major":[44],"challenge":[45],"existing":[48],"perturbation":[49],"or":[50,62,96],"transformation":[51],"based":[52],"approaches":[53],"as":[54],"they":[55],"conduct":[56],"analysis":[58,93],"on":[59,94],"perturbed":[61,95],"transformed":[63,97],"data,":[64,98],"which":[65,138],"too":[67],"large,":[68],"considering":[69],"many":[70],"organizational":[71],"typically":[73],"contain":[74],"a":[75,81],"huge":[76],"amount":[77],"with":[80],"large":[82],"number":[83],"categorical":[85],"numerical":[87],"attributes.":[88],"Instead":[89],"conducting":[91],"our":[99],"approach":[100],"build":[103],"an":[104],"approximate":[105],"statistical":[106],"model":[107,120,124],"first":[108],"analyze":[110],"various":[111],"terms":[115],"parameters":[117],"built.":[121],"As":[122],"learned":[125],"only":[128],"means":[129],"generate":[131],"release,":[134],"confidential":[136],"information":[137],"snoopers":[139],"can":[140],"derive":[141],"contained":[143],"those":[145],"parameters.":[146]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}