{"id":"https://openalex.org/W4406461265","doi":"https://doi.org/10.1109/bigdata62323.2024.10825533","title":"Toward Efficient Homomorphic Encryption-Based Federated Learning: A Magnitude-Sensitivity Approach","display_name":"Toward Efficient Homomorphic Encryption-Based Federated Learning: A Magnitude-Sensitivity Approach","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406461265","doi":"https://doi.org/10.1109/bigdata62323.2024.10825533"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825533","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825533","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5009972633","display_name":"Ren-Yi Huang","orcid":"https://orcid.org/0009-0006-8341-5835"},"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":"Ren-Yi Huang","raw_affiliation_strings":["University of South Florida,Tampa,USA"],"affiliations":[{"raw_affiliation_string":"University of South Florida,Tampa,USA","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041459341","display_name":"Dumindu Samaraweera","orcid":"https://orcid.org/0000-0003-4097-5585"},"institutions":[{"id":"https://openalex.org/I84475105","display_name":"Embry\u2013Riddle Aeronautical University","ror":"https://ror.org/010jskt71","country_code":"US","type":"education","lineage":["https://openalex.org/I84475105"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dumindu Samaraweera","raw_affiliation_strings":["Embry-Riddle Aeronautical University,Daytona Beach,USA"],"affiliations":[{"raw_affiliation_string":"Embry-Riddle Aeronautical University,Daytona Beach,USA","institution_ids":["https://openalex.org/I84475105"]}]},{"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":["University of South Florida,Tampa,USA"],"affiliations":[{"raw_affiliation_string":"University of South Florida,Tampa,USA","institution_ids":["https://openalex.org/I2613432"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5009972633"],"corresponding_institution_ids":["https://openalex.org/I2613432"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23785443,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7810","last_page":"7821"},"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":0.9998000264167786,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9970999956130981,"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/homomorphic-encryption","display_name":"Homomorphic encryption","score":0.8999383449554443},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7907226085662842},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.6421719789505005},{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.569115400314331},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.33615440130233765},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06414952874183655}],"concepts":[{"id":"https://openalex.org/C158338273","wikidata":"https://www.wikidata.org/wiki/Q2154943","display_name":"Homomorphic encryption","level":3,"score":0.8999383449554443},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7907226085662842},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.6421719789505005},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.569115400314331},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.33615440130233765},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06414952874183655},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825533","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825533","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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":42,"referenced_works":["https://openalex.org/W2177209050","https://openalex.org/W2226167778","https://openalex.org/W2734941459","https://openalex.org/W2767079719","https://openalex.org/W2768174108","https://openalex.org/W2781091734","https://openalex.org/W2886444620","https://openalex.org/W2894740066","https://openalex.org/W2942255051","https://openalex.org/W2970408908","https://openalex.org/W2977558206","https://openalex.org/W3000479830","https://openalex.org/W3016632787","https://openalex.org/W3027749727","https://openalex.org/W3028867652","https://openalex.org/W3211470872","https://openalex.org/W3212932635","https://openalex.org/W4221146015","https://openalex.org/W4229455429","https://openalex.org/W4283072613","https://openalex.org/W4287237144","https://openalex.org/W4287822453","https://openalex.org/W4296913515","https://openalex.org/W4307823778","https://openalex.org/W4318619660","https://openalex.org/W4322619364","https://openalex.org/W4353007060","https://openalex.org/W4393405950","https://openalex.org/W6728757088","https://openalex.org/W6754708698","https://openalex.org/W6755166560","https://openalex.org/W6764838729","https://openalex.org/W6768459703","https://openalex.org/W6773039429","https://openalex.org/W6775563089","https://openalex.org/W6778434676","https://openalex.org/W6779821316","https://openalex.org/W6780438843","https://openalex.org/W6793226373","https://openalex.org/W6839074529","https://openalex.org/W6849712443","https://openalex.org/W6851532263"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2539930818","https://openalex.org/W4403623784","https://openalex.org/W4393118461","https://openalex.org/W4390664647","https://openalex.org/W3012147850","https://openalex.org/W4313300189","https://openalex.org/W2949835517"],"abstract_inverted_index":{"Federated":[0],"Learning":[1],"(FL)":[2],"is":[3,127,207,290],"a":[4,32,59,75,113,153,192,273],"privacy-preserving":[5],"technique":[6],"that":[7,74,278,312],"allows":[8,241],"clients":[9,23],"to":[10,39,137,177,208,286,295,308],"collaboratively":[11],"train":[12],"models":[13,182,299],"while":[14,120,140,219],"keeping":[15],"their":[16],"local":[17,87],"data":[18],"private":[19,46],"from":[20],"both":[21],"other":[22],"and":[24,94,165,183,198,212,264,319],"the":[25,29,66,122,129,142,159,254,267],"central":[26],"server.":[27],"However,":[28,89],"presence":[30],"of":[31,115,155,158,235,261,266],"malicious":[33,76],"server":[34,67,77],"or":[35,78,84],"attacker":[36,79],"can":[37],"lead":[38],"model":[40,63,82,118,250,268],"inversion":[41],"attacks,":[42],"which":[43],"compromise":[44],"clients\u2019":[45,86],"information.":[47,88],"To":[48,104],"counteract":[49],"these":[50,134,171],"threats,":[51],"homomorphic":[52,147,217],"encryption":[53,199,276],"(HE)":[54],"has":[55],"been":[56],"proposed":[57],"as":[58],"solution,":[60],"enabling":[61],"encrypted":[62,246],"aggregation":[64],"by":[65,216,231],"without":[68],"exposing":[69],"raw":[70],"data.":[71],"This":[72,189],"ensures":[73],"cannot":[80],"access":[81],"parameters":[83,119,136],"reveal":[85],"HE":[90,238,257],"introduces":[91,191],"substantial":[92],"computational":[93],"communication":[95,213],"overhead,":[96],"making":[97,321],"it":[98,126,322],"impractical":[99,185],"for":[100,201,293,324],"many":[101],"real-world":[102,227,325],"implementations.":[103,188],"address":[105],"this,":[106],"recent":[107],"research":[108],"suggests":[109],"selectively":[110],"encrypting":[111],"only":[112,280],"subset":[114,154],"most":[116],"important":[117],"leaving":[121],"rest":[123],"unencrypted.":[124],"While":[125],"promising,":[128],"challenge":[130],"lies":[131],"in":[132,226,259,300],"identifying":[133],"key":[135],"maintain":[138],"security":[139,283],"minimizing":[141],"additional":[143,255],"costs":[144],"associated":[145],"with":[146,152],"operations.":[148],"In":[149,169],"addition,":[150],"even":[151],"parameters,":[156],"none":[157],"existing":[160,287],"methods":[161,288],"offer":[162],"truly":[163],"efficient":[164],"practical":[166,224,292],"HE-based":[167,202],"solution.":[168],"general,":[170],"approaches":[172],"fall":[173],"short":[174],"when":[175],"applied":[176],"large,":[178],"complex":[179,298],"deep":[180],"learning":[181],"are":[184],"beyond":[186],"basic":[187],"paper":[190],"straightforward":[193],"yet":[194],"effective":[195],"parameter":[196],"selection":[197],"strategy":[200,277],"federated":[203],"learning.":[204],"Our":[205],"goal":[206],"minimize":[209],"this":[210,304],"computational,":[211],"overhead":[214],"caused":[215],"operations":[218,244],"maintaining":[220],"robust":[221],"security,":[222],"ensuring":[223],"applicability":[225],"scenarios.":[228],"We":[229],"begin":[230],"evaluating":[232],"different":[233],"implementations":[234],"CKKS":[236],"(Cheon-Kim-Kim-Song)-based":[237],"algorithm":[239],"(which":[240],"floating":[242],"point":[243],"on":[245],"domain)":[247],"across":[248],"various":[249],"architectures,":[251],"systematically":[252],"analyzing":[253],"burden":[256],"imposes":[258],"terms":[260],"processing":[262],"time":[263],"size":[265],"parameters.":[269],"Next,":[270],"we":[271],"introduce":[272],"magnitude-based":[274],"selective":[275],"not":[279],"provide":[281],"same":[282],"guarantees":[284],"compared":[285],"but":[289],"also":[291],"scaling":[294],"larger,":[296],"more":[297],"FL":[301],"environments.":[302],"Hence,":[303],"approach":[305],"enables":[306],"developers":[307],"make":[309],"informed":[310],"decisions":[311],"strike":[313],"an":[314],"optimal":[315],"balance":[316],"between":[317],"performance":[318],"privacy/security,":[320],"feasible":[323],"deployments.":[326]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}