{"id":"https://openalex.org/W4405184816","doi":"https://doi.org/10.1145/3658644.3690375","title":"NeuJeans: Private Neural Network Inference with Joint Optimization of Convolution and FHE Bootstrapping","display_name":"NeuJeans: Private Neural Network Inference with Joint Optimization of Convolution and FHE Bootstrapping","publication_year":2024,"publication_date":"2024-12-02","ids":{"openalex":"https://openalex.org/W4405184816","doi":"https://doi.org/10.1145/3658644.3690375"},"language":"en","primary_location":{"id":"doi:10.1145/3658644.3690375","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3658644.3690375","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3658644.3690375","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3658644.3690375","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021887405","display_name":"Jae Hyung Ju","orcid":"https://orcid.org/0009-0007-8401-0773"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jae Hyung Ju","raw_affiliation_strings":["Seoul National University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069147425","display_name":"Jaiyoung Park","orcid":"https://orcid.org/0009-0000-7072-6147"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaiyoung Park","raw_affiliation_strings":["Seoul National University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100322020","display_name":"Jongmin Kim","orcid":"https://orcid.org/0000-0003-2937-3073"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jongmin Kim","raw_affiliation_strings":["Seoul National University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067779690","display_name":"Min-Sik Kang","orcid":"https://orcid.org/0009-0000-2125-5043"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minsik Kang","raw_affiliation_strings":["Seoul National University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075405418","display_name":"Donghwan Kim","orcid":"https://orcid.org/0009-0000-3294-5744"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Donghwan Kim","raw_affiliation_strings":["Seoul National University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044011121","display_name":"Jung Hee Cheon","orcid":"https://orcid.org/0000-0002-7085-2220"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jung Hee Cheon","raw_affiliation_strings":["Seoul National University &amp; CryptoLab Inc., Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University &amp; CryptoLab Inc., Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078262826","display_name":"Jung Ho Ahn","orcid":"https://orcid.org/0000-0003-1733-1394"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jung Ho Ahn","raw_affiliation_strings":["Seoul National University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5021887405"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":null,"apc_paid":null,"fwci":4.7009,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.95581863,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4361","last_page":"4375"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10237","display_name":"Cryptography and Data Security","score":0.9987999796867371,"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/T10237","display_name":"Cryptography and Data Security","score":0.9987999796867371,"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":0.984499990940094,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9732999801635742,"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":0.8154889345169067},{"id":"https://openalex.org/keywords/ciphertext","display_name":"Ciphertext","score":0.6533671617507935},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.623799741268158},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6037595868110657},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5825082063674927},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5771888494491577},{"id":"https://openalex.org/keywords/bootstrapping","display_name":"Bootstrapping (finance)","score":0.5755794048309326},{"id":"https://openalex.org/keywords/homomorphic-encryption","display_name":"Homomorphic encryption","score":0.5305711627006531},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.46234220266342163},{"id":"https://openalex.org/keywords/cryptography","display_name":"Cryptography","score":0.4306755065917969},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4243903160095215},{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.4171203076839447},{"id":"https://openalex.org/keywords/functional-encryption","display_name":"Functional encryption","score":0.41082853078842163},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4073060154914856},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3984588086605072},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.32233119010925293},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2395285964012146},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1871604323387146},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10462623834609985}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8154889345169067},{"id":"https://openalex.org/C93974786","wikidata":"https://www.wikidata.org/wiki/Q1589480","display_name":"Ciphertext","level":3,"score":0.6533671617507935},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.623799741268158},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6037595868110657},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5825082063674927},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5771888494491577},{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.5755794048309326},{"id":"https://openalex.org/C158338273","wikidata":"https://www.wikidata.org/wiki/Q2154943","display_name":"Homomorphic encryption","level":3,"score":0.5305711627006531},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.46234220266342163},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.4306755065917969},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4243903160095215},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.4171203076839447},{"id":"https://openalex.org/C2780746774","wikidata":"https://www.wikidata.org/wiki/Q17014981","display_name":"Functional encryption","level":4,"score":0.41082853078842163},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4073060154914856},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3984588086605072},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.32233119010925293},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2395285964012146},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1871604323387146},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10462623834609985},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3658644.3690375","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3658644.3690375","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3658644.3690375","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3658644.3690375","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3658644.3690375","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3658644.3690375","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4405184816.pdf"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W2061171222","https://openalex.org/W2134128809","https://openalex.org/W2531409750","https://openalex.org/W2557738935","https://openalex.org/W2765200655","https://openalex.org/W2788025656","https://openalex.org/W2942711826","https://openalex.org/W3012235108","https://openalex.org/W3013801589","https://openalex.org/W3093021001","https://openalex.org/W3104454153","https://openalex.org/W3137610633","https://openalex.org/W3141199462","https://openalex.org/W3173128495","https://openalex.org/W3195598474","https://openalex.org/W4210897777","https://openalex.org/W4281609193","https://openalex.org/W4281792301","https://openalex.org/W4285276028","https://openalex.org/W4307925365","https://openalex.org/W4361986437","https://openalex.org/W4390421891"],"related_works":["https://openalex.org/W2152926062","https://openalex.org/W2947510282","https://openalex.org/W2949607150","https://openalex.org/W2950312267","https://openalex.org/W2363701519","https://openalex.org/W3123945077","https://openalex.org/W2398715209","https://openalex.org/W2601739120","https://openalex.org/W3203896436","https://openalex.org/W2292786713"],"abstract_inverted_index":{"Fully":[0],"homomorphic":[1],"encryption":[2],"(FHE)":[3],"is":[4,100],"a":[5,19,28,74,115,136,183,191],"promising":[6],"cryptographic":[7],"primitive":[8],"for":[9,47,66,148],"realizing":[10],"private":[11],"neural":[12,53],"network":[13],"inference":[14,25],"(PI)":[15],"services":[16],"by":[17,102,168],"allowing":[18],"client":[20,34],"to":[21,27,37,125,157,170,173],"fully":[22],"offload":[23],"the":[24,33,38,48,58,62,67,104,109,127,163,180,186],"task":[26],"cloud":[29],"server":[30],"while":[31],"keeping":[32],"data":[35],"oblivious":[36],"server.":[39],"This":[40,121],"work":[41,177],"proposes":[42],"NeuJeans,":[43],"an":[44],"FHE-based":[45,175],"solution":[46],"PI":[49,176,181],"of":[50,61,70,108,165,182,188],"deep":[51],"convolutional":[52],"networks":[54],"(CNNs).":[55],"NeuJeans":[56,161],"tackles":[57],"critical":[59],"problem":[60],"enormous":[63],"computational":[64],"cost":[65],"FHE":[68],"evaluation":[69],"CNNs.":[71],"We":[72,94],"introduce":[73],"novel":[75],"encoding":[76,99],"method":[77],"called":[78],"Coefficients-in-Slot":[79],"(CinS)":[80],"encoding,":[81],"which":[82],"enables":[83,123],"multiple":[84],"convolutions":[85],"in":[86,117],"one":[87],"HE":[88],"multiplication":[89],"without":[90],"costly":[91],"slot":[92],"permutations.":[93],"further":[95],"observe":[96],"that":[97],"CinS":[98,130],"obtained":[101],"conducting":[103],"first":[105],"several":[106],"steps":[107],"Discrete":[110],"Fourier":[111],"Transform":[112],"(DFT)":[113],"on":[114],"ciphertext":[116,137],"conventional":[118],"Slot":[119,132],"encoding.":[120],"property":[122],"us":[124],"save":[126],"conversion":[128],"between":[129],"and":[131,154,178],"encodings":[133],"as":[134],"bootstrapping":[135],"starts":[138],"with":[139],"DFT.":[140],"Exploiting":[141],"this,":[142],"we":[143],"devise":[144],"optimized":[145],"execution":[146],"flows":[147],"various":[149],"two-dimensional":[150],"convolution":[151],"(conv2d)":[152],"operations":[153],"apply":[155],"them":[156],"end-to-end":[158],"CNN":[159,184],"implementations.":[160],"accelerates":[162],"performance":[164],"conv2d-activation":[166],"sequences":[167],"up":[169],"5.68\u00d7":[171],"compared":[172],"state-of-the-art":[174],"performs":[179],"at":[185],"scale":[187],"ImageNet":[189],"within":[190],"mere":[192],"few":[193],"seconds.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2024-12-10T00:00:00"}
