{"id":"https://openalex.org/W2912085138","doi":"https://doi.org/10.1109/desec.2018.8625131","title":"Differentially Private Principal Component Analysis Over Horizontally Partitioned Data","display_name":"Differentially Private Principal Component Analysis Over Horizontally Partitioned Data","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2912085138","doi":"https://doi.org/10.1109/desec.2018.8625131","mag":"2912085138"},"language":"en","primary_location":{"id":"doi:10.1109/desec.2018.8625131","is_oa":false,"landing_page_url":"https://doi.org/10.1109/desec.2018.8625131","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Conference on Dependable and Secure Computing (DSC)","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/A5100350734","display_name":"Sen Wang","orcid":"https://orcid.org/0000-0001-8457-9571"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sen Wang","raw_affiliation_strings":["Department of Electrical Engineering, University of South Florida, Tampa, Florida"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of South Florida, Tampa, Florida","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055158787","display_name":"J. Morris Chang","orcid":"https://orcid.org/0000-0002-0660-7191"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. Morris Chang","raw_affiliation_strings":["Department of Electrical Engineering, University of South Florida, Tampa, Florida"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of South Florida, Tampa, Florida","institution_ids":["https://openalex.org/I2613432"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100350734"],"corresponding_institution_ids":["https://openalex.org/I2613432"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.17281306,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"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":0.9998000264167786,"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":0.9998000264167786,"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/T10828","display_name":"Biometric Identification and Security","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9968000054359436,"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/computer-science","display_name":"Computer science","score":0.8175351023674011},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7681499123573303},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6978906989097595},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.6795808672904968},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5963934063911438},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5826431512832642},{"id":"https://openalex.org/keywords/private-information-retrieval","display_name":"Private information retrieval","score":0.5679517984390259},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5122551321983337},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.493417888879776},{"id":"https://openalex.org/keywords/protocol","display_name":"Protocol (science)","score":0.49066174030303955},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4886370301246643},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.4832506775856018},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.46614494919776917},{"id":"https://openalex.org/keywords/principal","display_name":"Principal (computer security)","score":0.43176108598709106},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.42337071895599365},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23655462265014648},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.1319778561592102},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.08131852746009827}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8175351023674011},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7681499123573303},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6978906989097595},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.6795808672904968},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5963934063911438},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5826431512832642},{"id":"https://openalex.org/C99221444","wikidata":"https://www.wikidata.org/wiki/Q1532069","display_name":"Private information retrieval","level":2,"score":0.5679517984390259},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5122551321983337},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.493417888879776},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.49066174030303955},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4886370301246643},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.4832506775856018},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.46614494919776917},{"id":"https://openalex.org/C144559511","wikidata":"https://www.wikidata.org/wiki/Q2986279","display_name":"Principal (computer security)","level":2,"score":0.43176108598709106},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.42337071895599365},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23655462265014648},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1319778561592102},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.08131852746009827},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C204787440","wikidata":"https://www.wikidata.org/wiki/Q188504","display_name":"Alternative medicine","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/desec.2018.8625131","is_oa":false,"landing_page_url":"https://doi.org/10.1109/desec.2018.8625131","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Conference on Dependable and Secure Computing (DSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1534308464","https://openalex.org/W1577921908","https://openalex.org/W1734370359","https://openalex.org/W1873763122","https://openalex.org/W1971817345","https://openalex.org/W1977974261","https://openalex.org/W1997690112","https://openalex.org/W2010523825","https://openalex.org/W2018199316","https://openalex.org/W2018573356","https://openalex.org/W2019704260","https://openalex.org/W2027077102","https://openalex.org/W2043969662","https://openalex.org/W2054922243","https://openalex.org/W2078053307","https://openalex.org/W2081769211","https://openalex.org/W2100200691","https://openalex.org/W2109426455","https://openalex.org/W2128399454","https://openalex.org/W2135930857","https://openalex.org/W2158339409","https://openalex.org/W2160955670","https://openalex.org/W2171604933","https://openalex.org/W2215385661","https://openalex.org/W2318956585","https://openalex.org/W2343471405","https://openalex.org/W2490306540","https://openalex.org/W2509467699","https://openalex.org/W2582825155","https://openalex.org/W2767082051","https://openalex.org/W4236107295","https://openalex.org/W4243100297","https://openalex.org/W6634357985","https://openalex.org/W6637507108","https://openalex.org/W6639246211","https://openalex.org/W6655193062","https://openalex.org/W6680267248","https://openalex.org/W6683520304","https://openalex.org/W6685488477","https://openalex.org/W6722529432"],"related_works":["https://openalex.org/W3038283795","https://openalex.org/W2604501336","https://openalex.org/W2734500670","https://openalex.org/W2558166297","https://openalex.org/W2315671126","https://openalex.org/W798507144","https://openalex.org/W2964481303","https://openalex.org/W2571704763","https://openalex.org/W1751413323","https://openalex.org/W2596305496"],"abstract_inverted_index":{"Principal":[0],"Component":[1],"Analysis":[2],"(PCA)":[3],"is":[4,164],"widely":[5],"adopted":[6],"in":[7,46,124,140,158,173],"various":[8],"data":[9,51,58,110,115,123,186],"mining":[10],"and":[11,55,72,94,126,145,150,177,179],"machine":[12],"learning":[13],"applications,":[14],"it":[15,42,182],"computes":[16],"a":[17,36,80,147,184],"low":[18],"dimension":[19],"subspace":[20],"that":[21,181],"captures":[22],"the":[23,27,69,85,92,105,122,127,160,167,171,190],"most":[24],"variances":[25],"of":[26,32,102,175],"underlying":[28],"data.":[29,103],"The":[30,114],"area":[31],"distributed":[33,87,155],"computing":[34],"provides":[35],"promising":[37],"domain":[38],"for":[39,74],"PCA,":[40],"where":[41],"has":[43],"been":[44],"studied":[45],"many":[47],"fields.":[48],"In":[49,166],"big":[50],"era,":[52],"large":[53,100],"volume":[54],"high":[56,185],"dimensional":[57],"are":[59],"generated":[60],"at":[61],"all":[62],"times.":[63],"For":[64],"instance,":[65],"mobile":[66],"devices":[67],"become":[68],"important":[70],"producer":[71],"carrier":[73],"personal":[75],"information,":[76],"which":[77,159],"can":[78],"provide":[79,91],"considerable":[81],"social":[82],"utility.":[83],"However,":[84],"current":[86],"PCA":[88,130,156],"protocol":[89,172],"cannot":[90],"efficiency":[93,176],"scalability":[95],"with":[96],"respect":[97],"to":[98,120,136],"such":[99],"amounts":[101],"Furthermore,":[104],"privacy":[106,153],"issue":[107],"arises":[108],"when":[109],"contains":[111],"sensitive":[112],"information.":[113],"owner":[116],"would":[117],"not":[118],"prefer":[119],"sharing":[121],"cleartext,":[125],"inference":[128],"from":[129],"should":[131],"also":[132],"be":[133],"prevented.":[134],"Motivated":[135],"resolve":[137],"these":[138],"challenges,":[139],"this":[141],"paper,":[142],"we":[143,169],"design":[144],"implement":[146],"highly":[148],"efficient":[149],"largely":[151],"scalable":[152],"preserving":[154,189],"protocol,":[157],"(\u03b5,":[161],"\u03b4)-Differential":[162],"Privacy":[163],"guaranteed.":[165],"experiments,":[168],"evaluate":[170],"terms":[174],"utility,":[178],"shows":[180],"maintains":[183],"utility":[187],"while":[188],"privacy.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
