{"id":"https://openalex.org/W4221138558","doi":"https://doi.org/10.48550/arxiv.2201.04211","title":"Reducing Noise Level in Differential Privacy through Matrix Masking","display_name":"Reducing Noise Level in Differential Privacy through Matrix Masking","publication_year":2022,"publication_date":"2022-01-11","ids":{"openalex":"https://openalex.org/W4221138558","doi":"https://doi.org/10.48550/arxiv.2201.04211"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2201.04211","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2201.04211","pdf_url":"https://arxiv.org/pdf/2201.04211","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2201.04211","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030382613","display_name":"A. Adam Ding","orcid":"https://orcid.org/0000-0003-1397-2442","observed_orcids":["https://orcid.org/0000-0003-1397-2442"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, A. Adam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101531627","display_name":"Samuel Shangwu Wu","orcid":"https://orcid.org/0000-0003-2684-436X","observed_orcids":["https://orcid.org/0000-0003-2684-436X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Samuel S.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015570934","display_name":"Guanhong Miao","orcid":"https://orcid.org/0000-0002-8083-7032","observed_orcids":["https://orcid.org/0000-0002-8083-7032"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Miao, Guanhong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5006184530","display_name":"Shigang Chen","orcid":"https://orcid.org/0000-0001-7867-7765","observed_orcids":["https://orcid.org/0000-0001-7867-7765","https://orcid.org/0000-0002-2269-9671"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Shigang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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/T11614","display_name":"Cloud Data Security Solutions","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/differential-privacy","display_name":"differential privacy","score":0.9990000128746033},{"id":"https://openalex.org/keywords/gaussian-mechanism","display_name":"Gaussian mechanism","score":0.6909999847412109},{"id":"https://openalex.org/keywords/noise-variance-reduction","display_name":"noise variance reduction","score":0.8190000057220459},{"id":"https://openalex.org/keywords/epsilon-delta-differential-privacy","display_name":"(\u03b5, \u03b4)-differential privacy","score":0.9459999799728394},{"id":"https://openalex.org/keywords/big-data-privacy","display_name":"big data privacy","score":0.8140000104904175},{"id":"https://openalex.org/keywords/privacy-utility-trade-off","display_name":"privacy-utility trade-off","score":0.6510000228881836},{"id":"https://openalex.org/keywords/data-protection","display_name":"data protection","score":0.3889999985694885}],"concepts":[{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.9048256874084473},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.61641526222229},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.577745258808136},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5447538495063782},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5133129954338074},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4960494935512543},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.48022183775901794},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.471938818693161},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4606288969516754},{"id":"https://openalex.org/C64812099","wikidata":"https://www.wikidata.org/wiki/Q176604","display_name":"Random matrix","level":3,"score":0.4584576189517975},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.43444395065307617},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3683167099952698},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.19270843267440796},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12395045161247253},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.07137757539749146},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","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},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2201.04211","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2201.04211","pdf_url":"https://arxiv.org/pdf/2201.04211","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2201.04211","doi":"https://doi.org/10.48550/arxiv.2201.04211","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2201.04211","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2201.04211","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2201.04211","pdf_url":"https://arxiv.org/pdf/2201.04211","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7162705058","https://openalex.org/W4400975132","https://openalex.org/W3158160082","https://openalex.org/W2990741518","https://openalex.org/W7162691626","https://openalex.org/W4417288481","https://openalex.org/W4417095173","https://openalex.org/W4221146027","https://openalex.org/W4386057506","https://openalex.org/W4392412869"],"abstract_inverted_index":{"Differential":[0],"privacy":[1,15,38,112],"schemes":[2],"have":[3],"been":[4],"widely":[5],"adopted":[6],"in":[7,57,65],"recent":[8],"years":[9],"to":[10,34,61,94,102],"address":[11],"issues":[12],"of":[13,53,85,128],"data":[14,26,67,115],"protection.":[16],"We":[17,42],"propose":[18],"a":[19],"new":[20],"Gaussian":[21,59],"scheme":[22,60],"combining":[23],"with":[24],"another":[25],"protection":[27],"technique,":[28],"called":[29],"random":[30],"orthogonal":[31],"matrix":[32,47],"masking,":[33],"achieve":[35,62,95],"$(\\varepsilon,":[36,63,96],"\u03b4)$-differential":[37],"(DP)":[39],"more":[40,119],"efficiently.":[41],"prove":[43],"that":[44],"the":[45,51,58,77,82,89,109,126],"additional":[46],"masking":[48],"significantly":[49,124],"reduces":[50],"rate":[52],"noise":[54,92,107],"variance":[55,93],"required":[56,90],"\u03b4)-$DP":[64],"big":[66],"setting.":[68],"Specifically,":[69],"when":[70],"$\\varepsilon":[71],"\\to":[72],"0$,":[73,75],"$\u03b4\\to":[74],"and":[76],"sample":[78],"size":[79],"$n$":[80],"exceeds":[81],"number":[83],"$p$":[84],"attributes":[86],"by":[87],"$(n-p)=O(ln(1/\u03b4))$,":[88],"additive":[91],"\u03b4)$-DP":[97],"is":[98],"reduced":[99],"from":[100],"$O(ln(1/\u03b4)/\\varepsilon^2)$":[101],"$O(1/\\varepsilon)$.":[103],"With":[104],"much":[105,118],"less":[106],"added,":[108],"resulting":[110],"differential":[111,131],"protected":[113],"pseudo":[114],"sets":[116],"allow":[117],"accurate":[120],"inferences,":[121],"thus":[122],"can":[123],"improve":[125],"scope":[127],"application":[129],"for":[130],"privacy.":[132]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-09-24T07:57:37.273135","created_date":"2022-04-03T00:00:00"}
