{"id":"https://openalex.org/W2914756587","doi":"https://doi.org/10.1109/wifs.2018.8630790","title":"Privacy-Preserving Distributed Deep Learning with Privacy Transformations","display_name":"Privacy-Preserving Distributed Deep Learning with Privacy Transformations","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2914756587","doi":"https://doi.org/10.1109/wifs.2018.8630790","mag":"2914756587"},"language":"en","primary_location":{"id":"doi:10.1109/wifs.2018.8630790","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wifs.2018.8630790","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Workshop on Information Forensics and Security (WIFS)","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/A5022090297","display_name":"Sen-ching S. Cheung","orcid":"https://orcid.org/0000-0002-9207-5514"},"institutions":[{"id":"https://openalex.org/I143302722","display_name":"University of Kentucky","ror":"https://ror.org/02k3smh20","country_code":"US","type":"education","lineage":["https://openalex.org/I143302722"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sen-ching S. Cheung","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Kentucky, Lexington, KY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Kentucky, Lexington, KY","institution_ids":["https://openalex.org/I143302722"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039655720","display_name":"Muhammad Usman Rafique","orcid":"https://orcid.org/0000-0001-5504-5482"},"institutions":[{"id":"https://openalex.org/I143302722","display_name":"University of Kentucky","ror":"https://ror.org/02k3smh20","country_code":"US","type":"education","lineage":["https://openalex.org/I143302722"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Muhammad Usman Rafique","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Kentucky, Lexington, KY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Kentucky, Lexington, KY","institution_ids":["https://openalex.org/I143302722"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110256765","display_name":"Wai-Tian Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I135428043","display_name":"Cisco Systems (United States)","ror":"https://ror.org/03yt1ez60","country_code":"US","type":"company","lineage":["https://openalex.org/I135428043"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wai-tian Tan","raw_affiliation_strings":["Innovation Labs Cisco Systems Inc., San Jose, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Innovation Labs Cisco Systems Inc., San Jose, CA","institution_ids":["https://openalex.org/I135428043"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"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":0.9993000030517578,"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":0.9962999820709229,"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":0.8321511149406433},{"id":"https://openalex.org/keywords/homomorphic-encryption","display_name":"Homomorphic encryption","score":0.8141923546791077},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.6285879611968994},{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.5963389873504639},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5538448691368103},{"id":"https://openalex.org/keywords/cryptography","display_name":"Cryptography","score":0.5354108810424805},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.4464268386363983},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.38986384868621826},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33256208896636963},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3274334669113159},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2664368748664856}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8321511149406433},{"id":"https://openalex.org/C158338273","wikidata":"https://www.wikidata.org/wiki/Q2154943","display_name":"Homomorphic encryption","level":3,"score":0.8141923546791077},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.6285879611968994},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.5963389873504639},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5538448691368103},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.5354108810424805},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.4464268386363983},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38986384868621826},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33256208896636963},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3274334669113159},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2664368748664856}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wifs.2018.8630790","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wifs.2018.8630790","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Workshop on Information Forensics and Security (WIFS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W972261331","https://openalex.org/W1520270249","https://openalex.org/W1520311163","https://openalex.org/W1533861849","https://openalex.org/W2004177075","https://openalex.org/W2053171205","https://openalex.org/W2053637704","https://openalex.org/W2089497633","https://openalex.org/W2176455458","https://openalex.org/W2194775991","https://openalex.org/W2277014070","https://openalex.org/W2317339301","https://openalex.org/W2380240963","https://openalex.org/W2435473771","https://openalex.org/W2473418344","https://openalex.org/W2520442116","https://openalex.org/W2560610000","https://openalex.org/W2579435656","https://openalex.org/W2585580772","https://openalex.org/W2591882872","https://openalex.org/W2620512600","https://openalex.org/W2701059868","https://openalex.org/W2724212798","https://openalex.org/W2753648062","https://openalex.org/W2767079719","https://openalex.org/W2949140995","https://openalex.org/W2961396908","https://openalex.org/W2983170364","https://openalex.org/W3118608800","https://openalex.org/W4239982965","https://openalex.org/W6663928093","https://openalex.org/W6726828527","https://openalex.org/W6732586565","https://openalex.org/W6743851369","https://openalex.org/W6763152210"],"related_works":["https://openalex.org/W3038283795","https://openalex.org/W2604501336","https://openalex.org/W2558166297","https://openalex.org/W2734500670","https://openalex.org/W2315671126","https://openalex.org/W798507144","https://openalex.org/W2539930818","https://openalex.org/W2964481303","https://openalex.org/W2887779253","https://openalex.org/W4391095118"],"abstract_inverted_index":{"Distributed":[0],"Deep":[1],"Learning":[2],"(DDL)":[3],"allows":[4],"disparate":[5],"sites":[6],"or":[7,40],"entities":[8],"to":[9,14,57],"use":[10],"their":[11],"local":[12],"data":[13,25,56],"collaboratively":[15],"learn":[16],"a":[17,20,48,125],"model":[18,87],"at":[19,73,149],"central":[21],"server.":[22,59,151],"To":[23,119],"protect":[24],"privacy,":[26],"existing":[27],"approaches":[28],"like":[29],"fully":[30],"homomorphic":[31],"encryption":[32],"and":[33,70,88,100,140,145],"differential":[34],"privacy":[35,68],"are":[36],"either":[37],"computationally":[38],"prohibitive":[39],"insecure.":[41],"In":[42],"this":[43,121],"paper,":[44],"we":[45,91,123],"proposed":[46,124],"applying":[47],"privacy-preserving":[49],"transformation":[50],"(PPT)":[51],"before":[52],"sending":[53],"the":[54,58,74,85,111,116,137,150],"transformed":[55],"The":[60],"design":[61],"goals":[62],"of":[63,79],"PPT":[64],"include":[65],"computation":[66],"efficiency,":[67],"preservation,":[69],"good":[71,146],"learnability":[72],"server":[75],"with":[76],"maximal":[77],"reuse":[78],"DL":[80],"software":[81],"infrastructure.":[82],"After":[83],"analyzing":[84],"security":[86,144],"possible":[89],"attacks,":[90],"evaluated":[92],"simple":[93],"PPTs":[94],"including":[95],"scrambling,":[96],"random":[97,127,138],"linear":[98],"transforms,":[99],"Advanced":[101],"Encryption":[102],"Standard":[103],"(AES).":[104],"While":[105],"AES":[106],"is":[107],"more":[108],"secure":[109],"than":[110],"others,":[112],"it":[113],"significantly":[114],"degrades":[115],"learning":[117,147],"performance.":[118],"address":[120],"challenge,":[122],"novel":[126],"deep":[128],"neural":[129],"network":[130],"as":[131],"PPT.":[132],"Our":[133],"experiments":[134],"showed":[135],"that":[136],"weights":[139],"connections":[141],"provide":[142],"adequate":[143],"performances":[148]},"counts_by_year":[{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
