{"id":"https://openalex.org/W7134888148","doi":"https://doi.org/10.1109/asp-dac66049.2026.11420798","title":"EP-HDC: Hyperdimensional Computing with Encrypted Parameters for High-Throughput Privacy-Preserving Inference","display_name":"EP-HDC: Hyperdimensional Computing with Encrypted Parameters for High-Throughput Privacy-Preserving Inference","publication_year":2026,"publication_date":"2026-01-19","ids":{"openalex":"https://openalex.org/W7134888148","doi":"https://doi.org/10.1109/asp-dac66049.2026.11420798"},"language":null,"primary_location":{"id":"doi:10.1109/asp-dac66049.2026.11420798","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asp-dac66049.2026.11420798","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 31st Asia and South Pacific Design Automation Conference (ASP-DAC)","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/A5100359860","display_name":"Jaewoo Park","orcid":"https://orcid.org/0000-0002-6477-9813"},"institutions":[{"id":"https://openalex.org/I48566637","display_name":"Ulsan National Institute of Science and Technology","ror":"https://ror.org/017cjz748","country_code":"KR","type":"education","lineage":["https://openalex.org/I48566637"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jaewoo Park","raw_affiliation_strings":["Ulsan National Institute of Science and Technology (UNIST),Department of Computer Science and Engineering,Ulsan,Korea"],"affiliations":[{"raw_affiliation_string":"Ulsan National Institute of Science and Technology (UNIST),Department of Computer Science and Engineering,Ulsan,Korea","institution_ids":["https://openalex.org/I48566637"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035412352","display_name":"Chenghao Quan","orcid":"https://orcid.org/0000-0001-7754-7467"},"institutions":[{"id":"https://openalex.org/I48566637","display_name":"Ulsan National Institute of Science and Technology","ror":"https://ror.org/017cjz748","country_code":"KR","type":"education","lineage":["https://openalex.org/I48566637"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chenghao Quan","raw_affiliation_strings":["Ulsan National Institute of Science and Technology (UNIST),Department of Electrical Engineering,Ulsan,Korea"],"affiliations":[{"raw_affiliation_string":"Ulsan National Institute of Science and Technology (UNIST),Department of Electrical Engineering,Ulsan,Korea","institution_ids":["https://openalex.org/I48566637"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128719732","display_name":"Jongeun Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I48566637","display_name":"Ulsan National Institute of Science and Technology","ror":"https://ror.org/017cjz748","country_code":"KR","type":"education","lineage":["https://openalex.org/I48566637"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jongeun Lee","raw_affiliation_strings":["Ulsan National Institute of Science and Technology (UNIST),Department of Electrical Engineering,Ulsan,Korea"],"affiliations":[{"raw_affiliation_string":"Ulsan National Institute of Science and Technology (UNIST),Department of Electrical Engineering,Ulsan,Korea","institution_ids":["https://openalex.org/I48566637"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100359860"],"corresponding_institution_ids":["https://openalex.org/I48566637"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.89156216,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1237","last_page":"1243"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9854999780654907,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9854999780654907,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.003100000089034438,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.0026000000070780516,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.48080000281333923},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4316999912261963},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.29490000009536743},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.29420000314712524},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.2655999958515167}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6209999918937683},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.48080000281333923},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40389999747276306},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33970001339912415},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3109999895095825},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.29490000009536743},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.29420000314712524},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.26600000262260437},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2655999958515167},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.262800008058548},{"id":"https://openalex.org/C2987376176","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy inference system","level":5,"score":0.2572000026702881}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asp-dac66049.2026.11420798","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asp-dac66049.2026.11420798","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 31st Asia and South Pacific Design Automation Conference (ASP-DAC)","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":21,"referenced_works":["https://openalex.org/W2007339694","https://openalex.org/W2070862086","https://openalex.org/W2554538030","https://openalex.org/W2583857261","https://openalex.org/W2768174108","https://openalex.org/W2771100829","https://openalex.org/W2924179447","https://openalex.org/W2993412634","https://openalex.org/W3092127391","https://openalex.org/W3157477139","https://openalex.org/W3176945641","https://openalex.org/W3184049905","https://openalex.org/W3204836041","https://openalex.org/W3208591904","https://openalex.org/W3212932635","https://openalex.org/W4293025145","https://openalex.org/W4307925365","https://openalex.org/W4312121059","https://openalex.org/W4380881143","https://openalex.org/W4386765257","https://openalex.org/W4389160768"],"related_works":[],"abstract_inverted_index":{"While":[0],"homomorphic":[1],"encryption":[2,59,102],"(HE)":[3],"provides":[4],"strong":[5,118],"privacy":[6],"protection,":[7],"its":[8,14],"high":[9,52,58,111],"computational":[10],"cost":[11],"has":[12,26,49],"restricted":[13],"application":[15,129],"to":[16,24,38,128],"simple":[17],"tasks.":[18],"Recently,":[19],"hyperdimensional":[20],"computing":[21],"(HDC)":[22],"applied":[23,37],"HE":[25,48],"shown":[27],"promising":[28],"performance":[29],"for":[30,120,131],"privacy-preserving":[31],"machine":[32],"learning":[33],"(PPML).":[34],"However,":[35],"when":[36],"more":[39],"realistic":[40],"scenarios":[41],"such":[42],"as":[43,55,57,107,109],"batch":[44,168],"inference,":[45],"the":[46,101,151,155],"HDC-based":[47],"still":[50],"very":[51],"compute":[53],"time":[54],"well":[56,108],"and":[60,103,123,144,154,165,182],"data":[61,104,122],"transmission":[62,105],"overheads.":[63],"To":[64],"address":[65],"this":[66],"problem,":[67],"we":[68,135],"propose":[69],"HDC":[70],"with":[71,113,188],"encrypted":[72,94],"parameters":[73],"(EP-HDC),":[74],"which":[75],"is":[76,86],"a":[77,89,92],"novel":[78],"PPML":[79,176],"approach":[80],"featuring":[81],"client-side":[82,133],"HE,":[83],"i.e.,":[84],"inference":[85,169],"performed":[87],"on":[88],"client":[90],"using":[91,150],"homomorphically":[93],"model.":[95],"Our":[96,147],"EP-HDC":[97],"can":[98,162],"effectively":[99],"mitigate":[100],"overhead,":[106],"providing":[110,117],"scalability":[112],"many":[114],"clients":[115],"while":[116],"protection":[119],"user":[121],"model":[124],"parameters.":[125,146],"In":[126],"addition":[127],"examples":[130],"our":[132,160],"PPML,":[134],"also":[136],"present":[137],"design":[138],"space":[139],"exploration":[140],"involving":[141],"quantization,":[142],"architecture,":[143],"HE-related":[145],"experimental":[148],"results":[149],"BFV":[152],"scheme":[153],"Face/Emotion":[156],"datasets":[157],"demonstrate":[158],"that":[159],"method":[161],"improve":[163],"throughput":[164],"latency":[166],"of":[167,172],"by":[170],"orders":[171],"magnitude":[173],"over":[174],"previous":[175],"methods":[177],"($36.52":[178],"\\sim":[179,184],"1068":[180],"\\times$":[181],"$6.45":[183],"733":[185],"\\times$,":[186],"respectively)":[187],"<1%":[189],"accuracy":[190],"degradation.":[191]},"counts_by_year":[],"updated_date":"2026-03-13T14:20:09.374765","created_date":"2026-03-12T00:00:00"}
