{"id":"https://openalex.org/W4413822740","doi":"https://doi.org/10.1109/icccn65249.2025.11133786","title":"P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices","display_name":"P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices","publication_year":2025,"publication_date":"2025-08-04","ids":{"openalex":"https://openalex.org/W4413822740","doi":"https://doi.org/10.1109/icccn65249.2025.11133786"},"language":"en","primary_location":{"id":"doi:10.1109/icccn65249.2025.11133786","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccn65249.2025.11133786","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 34th International Conference on Computer Communications and Networks (ICCCN)","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":null,"display_name":"Wei Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Wei Fan","raw_affiliation_strings":["Virginia Tech,Department of Computer Science,Blacksburg,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Tech,Department of Computer Science,Blacksburg,USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085520447","display_name":"JinYi Yoon","orcid":"https://orcid.org/0000-0001-9457-4432"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"JinYi Yoon","raw_affiliation_strings":["Virginia Tech,Department of Computer Science,Blacksburg,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Tech,Department of Computer Science,Blacksburg,USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036195969","display_name":"Xiaochang Li","orcid":"https://orcid.org/0000-0002-6203-7197"},"institutions":[{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaochang Li","raw_affiliation_strings":["William & Mary,Department of Computer Science,Williamsburg,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"William & Mary,Department of Computer Science,Williamsburg,USA","institution_ids":["https://openalex.org/I16285277"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041685416","display_name":"Huajie Shao","orcid":"https://orcid.org/0000-0001-7627-5615"},"institutions":[{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huajie Shao","raw_affiliation_strings":["William & Mary,Department of Computer Science,Williamsburg,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"William & Mary,Department of Computer Science,Williamsburg,USA","institution_ids":["https://openalex.org/I16285277"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040279482","display_name":"Bo Ji","orcid":"https://orcid.org/0000-0003-0149-7509"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bo Ji","raw_affiliation_strings":["Virginia Tech,Department of Computer Science,Blacksburg,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Tech,Department of Computer Science,Blacksburg,USA","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I859038795"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10843689,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9506000280380249,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9300000071525574,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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":0.7531059980392456},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.573826014995575},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.44387301802635193},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.4235954284667969},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3452219069004059},{"id":"https://openalex.org/keywords/internet-privacy","display_name":"Internet privacy","score":0.24610579013824463},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23642277717590332}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7531059980392456},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.573826014995575},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.44387301802635193},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.4235954284667969},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3452219069004059},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.24610579013824463},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23642277717590332}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icccn65249.2025.11133786","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccn65249.2025.11133786","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 34th International Conference on Computer Communications and Networks (ICCCN)","raw_type":"proceedings-article"},{"id":"doi:10.1109/tnse.2026.3695367","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnse.2026.3695367","pdf_url":null,"source":{"id":"https://openalex.org/S2484352698","display_name":"IEEE Transactions on Network Science and Engineering","issn_l":"2327-4697","issn":["2327-4697","2334-329X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Network Science and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2042980903","https://openalex.org/W2141983208","https://openalex.org/W2533598788","https://openalex.org/W2614367549","https://openalex.org/W2963209930","https://openalex.org/W3009048827","https://openalex.org/W3018102029","https://openalex.org/W3105915864","https://openalex.org/W3107794213","https://openalex.org/W3133012203","https://openalex.org/W3213008925","https://openalex.org/W4285154384","https://openalex.org/W4296411155","https://openalex.org/W4296982580","https://openalex.org/W4366957392","https://openalex.org/W4396506222","https://openalex.org/W4396878072","https://openalex.org/W4399121685","https://openalex.org/W4399882066","https://openalex.org/W4401539777","https://openalex.org/W4402543980"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W4324372666","https://openalex.org/W4225706866","https://openalex.org/W2914646191","https://openalex.org/W3023564924","https://openalex.org/W2942586735"],"abstract_inverted_index":{"Split":[0,100],"Learning":[1,101],"(SL)":[2],"is":[3],"an":[4],"emerging":[5],"privacy-preserving":[6],"machine":[7],"learning":[8,125],"technique":[9,157],"that":[10,66,127,158,235],"enables":[11],"resource":[12,74],"constrained":[13],"edge":[14,36,107],"devices":[15,46,71,209],"to":[16,131,142,161,248,256],"participate":[17],"in":[18,42,48],"model":[19,24,84,196,224],"training":[20],"by":[21,246],"partitioning":[22],"a":[23,97,121,154,204],"into":[25],"client-side":[26],"and":[27,55,82,136,148,189,200,219,226,250],"server-side":[28],"sub-models.":[29],"While":[30],"SL":[31,64,260],"reduces":[32,242],"computational":[33,144,175],"overhead":[34],"on":[35,203],"devices,":[37,215],"it":[38],"encounters":[39],"significant":[40],"challenges":[41],"heterogeneous":[43,63,259],"environments":[44],"where":[45],"vary":[47],"computing":[49],"resources,":[50,145,176],"communication":[51],"capabilities,":[52],"environmental":[53,88,146,177,230],"conditions,":[54,147,178],"privacy":[56,80,134,149,179,190,239],"requirements.":[57],"Although":[58],"recent":[59],"studies":[60],"have":[61],"explored":[62],"frameworks":[65],"optimize":[67],"split":[68,124,167],"points":[69,168],"for":[70,104],"with":[72,181],"varying":[73,87,229],"constraints,":[75],"they":[76],"often":[77],"neglect":[78],"personalized":[79,122,138,166],"requirements":[81],"local":[83,139],"customization":[85],"under":[86,228],"conditions.":[89,231],"To":[90],"address":[91],"these":[92],"limitations,":[93],"we":[94,119,152],"propose":[95],"P3SL,":[96],"Personalized":[98],"Privacy-Preserving":[99],"framework":[102],"designed":[103],"heterogeneous,":[105],"resource-constrained":[106],"device":[108],"systems.":[109],"The":[110],"key":[111],"contributions":[112],"of":[113,207],"this":[114],"work":[115],"are":[116],"twofold.":[117],"First,":[118],"design":[120],"sequential":[123],"pipeline":[126],"allows":[128],"each":[129],"client":[130],"achieve":[132],"customized":[133],"protection":[135],"maintain":[137],"models":[140],"tailored":[141],"their":[143,163],"needs.":[150],"Second,":[151],"adopt":[153],"bi-level":[155],"optimization":[156],"empowers":[159],"clients":[160],"determine":[162],"own":[164],"optimal":[165],"without":[169],"sharing":[170],"private":[171],"sensitive":[172],"information":[173],"(i.e.,":[174],"requirements)":[180],"the":[182,257],"server.":[183],"This":[184],"approach":[185],"balances":[186],"energy":[187,244],"consumption":[188,245],"leakage":[191,240],"risks":[192],"while":[193],"maintaining":[194],"high":[195,253],"accuracy.":[197],"We":[198],"implement":[199],"evaluate":[201],"P3SL":[202,236],"testbed":[205],"consisting":[206],"7":[208],"including":[210],"4":[211],"Jetson":[212],"Nano":[213],"P3450":[214],"2":[216],"Raspberry":[217],"Pis,":[218],"1":[220],"laptop,":[221],"using":[222],"diverse":[223],"architectures":[225],"datasets":[227],"Experimental":[232],"results":[233],"demonstrate":[234],"significantly":[237],"mitigates":[238],"risks,":[241],"system":[243],"up":[247],"59.12%,":[249],"consistently":[251],"retains":[252],"accuracy":[254],"compared":[255],"state-of-the-art":[258],"system.":[261]},"counts_by_year":[],"updated_date":"2026-05-22T09:01:20.584952","created_date":"2025-10-10T00:00:00"}