{"id":"https://openalex.org/W2982753995","doi":"https://doi.org/10.1145/3358331.3358396","title":"Naive Bayes Classification based on Differential Privacy","display_name":"Naive Bayes Classification based on Differential Privacy","publication_year":2019,"publication_date":"2019-10-17","ids":{"openalex":"https://openalex.org/W2982753995","doi":"https://doi.org/10.1145/3358331.3358396","mag":"2982753995"},"language":"en","primary_location":{"id":"doi:10.1145/3358331.3358396","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3358331.3358396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 International Conference on Artificial Intelligence and Advanced Manufacturing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5006741633","display_name":"Wenru Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenru Tang","raw_affiliation_strings":["School of Computer Science, Shaanxi Normal University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Shaanxi Normal University, Xi'an, China","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101915853","display_name":"Yihui Zhou","orcid":"https://orcid.org/0009-0002-0368-9547"},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yihui Zhou","raw_affiliation_strings":["School of Computer Science, Shaanxi Normal University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Shaanxi Normal University, Xi'an, China","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071761891","display_name":"Zhenqiang Wu","orcid":"https://orcid.org/0000-0002-7860-5208"},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenqiang Wu","raw_affiliation_strings":["School of Computer Science, Shaanxi Normal University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Shaanxi Normal University, Xi'an, China","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031106735","display_name":"Laifeng Lu","orcid":"https://orcid.org/0000-0001-9472-8913"},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Laifeng Lu","raw_affiliation_strings":["School of Mathematics and Information Science, Shaanxi Normal University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Information Science, Shaanxi Normal University, Xi'an, China","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035089546","display_name":"Mingshuang Li","orcid":"https://orcid.org/0000-0002-4651-212X"},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingshuang Li","raw_affiliation_strings":["School of Computer Science, Shaanxi Normal University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Shaanxi Normal University, Xi'an, China","institution_ids":["https://openalex.org/I88830068"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I88830068"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"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/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/T11045","display_name":"Privacy, Security, and Data Protection","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10237","display_name":"Cryptography and Data Security","score":0.9794999957084656,"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":0.8451615571975708},{"id":"https://openalex.org/keywords/laplace-distribution","display_name":"Laplace distribution","score":0.6929062604904175},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6467199325561523},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5764013528823853},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.5615226626396179},{"id":"https://openalex.org/keywords/laplaces-method","display_name":"Laplace's method","score":0.5474229454994202},{"id":"https://openalex.org/keywords/laplace-transform","display_name":"Laplace transform","score":0.5411130785942078},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5406733155250549},{"id":"https://openalex.org/keywords/log-normal-distribution","display_name":"Log-normal distribution","score":0.5350056886672974},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5284481048583984},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5164570808410645},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.49432373046875},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4296635389328003},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.41589587926864624},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37632134556770325},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3586278557777405},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3012389540672302},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20856747031211853},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.20510941743850708},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.08282965421676636},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07777923345565796}],"concepts":[{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.8451615571975708},{"id":"https://openalex.org/C183057437","wikidata":"https://www.wikidata.org/wiki/Q671617","display_name":"Laplace distribution","level":3,"score":0.6929062604904175},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6467199325561523},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5764013528823853},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.5615226626396179},{"id":"https://openalex.org/C22243797","wikidata":"https://www.wikidata.org/wiki/Q2058297","display_name":"Laplace's method","level":3,"score":0.5474229454994202},{"id":"https://openalex.org/C97937538","wikidata":"https://www.wikidata.org/wiki/Q199691","display_name":"Laplace transform","level":2,"score":0.5411130785942078},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5406733155250549},{"id":"https://openalex.org/C151620405","wikidata":"https://www.wikidata.org/wiki/Q826116","display_name":"Log-normal distribution","level":2,"score":0.5350056886672974},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5284481048583984},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5164570808410645},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.49432373046875},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4296635389328003},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.41589587926864624},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37632134556770325},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3586278557777405},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3012389540672302},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20856747031211853},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.20510941743850708},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.08282965421676636},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07777923345565796},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3358331.3358396","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3358331.3358396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 International Conference on Artificial Intelligence and Advanced Manufacturing","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":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1557833142","https://openalex.org/W1923767230","https://openalex.org/W2001238748","https://openalex.org/W2075291208","https://openalex.org/W2128906841","https://openalex.org/W2170031059","https://openalex.org/W2267666116","https://openalex.org/W2293934387","https://openalex.org/W2403112189","https://openalex.org/W2598406783","https://openalex.org/W2751455202","https://openalex.org/W2782545421","https://openalex.org/W2783409582","https://openalex.org/W2797291398","https://openalex.org/W2803952841","https://openalex.org/W2911978475","https://openalex.org/W4248358572"],"related_works":["https://openalex.org/W4385694606","https://openalex.org/W3091150767","https://openalex.org/W2254375831","https://openalex.org/W4297752560","https://openalex.org/W2995171315","https://openalex.org/W4312054394","https://openalex.org/W4385945597","https://openalex.org/W192568510","https://openalex.org/W2613625026","https://openalex.org/W4281746901"],"abstract_inverted_index":{"Data":[0],"mining":[1,41],"has":[2],"a":[3,52],"wide":[4],"range":[5],"of":[6,21,26,32],"applications":[7],"in":[8,23],"the":[9,18,24,37,42,45,69,79,89,94],"real":[10],"world.":[11],"However,":[12],"it":[13,30],"is":[14,31],"possible":[15],"to":[16,35,68,78,92,117],"disclose":[17],"private":[19],"information":[20],"users":[22],"process":[25],"data":[27],"mining.":[28],"Therefore,":[29],"great":[33],"significance":[34],"protect":[36],"users'":[38],"privacy":[39],"while":[40],"knowledge":[43],"behind":[44],"data.":[46],"In":[47],"this":[48],"paper,":[49],"we":[50,64,74,103],"propose":[51],"Naive":[53],"Bayes":[54],"classification":[55],"method":[56],"based":[57],"on":[58],"differential":[59],"privacy.":[60],"For":[61,71,100],"nominal":[62],"attributes,":[63,73,102],"add":[65,75],"Laplace":[66,76],"noise":[67,77],"count.":[70],"numerical":[72,101],"mean,":[80],"standard":[81],"deviation,":[82],"and":[83,86,97,113],"scale":[84],"parameter,":[85],"then":[87],"use":[88],"noisy":[90],"parameters":[91],"calculate":[93],"prior":[95],"probability":[96],"conditional":[98],"probability.":[99],"assume":[104],"that":[105],"they":[106],"follow":[107],"Gaussian,":[108],"Laplace,":[109],"or":[110],"lognormal":[111],"distribution,":[112],"apply":[114],"our":[115],"algorithms":[116],"compare":[118],"utilities.":[119]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}