{"id":"https://openalex.org/W4306317401","doi":"https://doi.org/10.1145/3511808.3557450","title":"Serpens: Privacy-Preserving Inference through Conditional Separable of Convolutional Neural Networks","display_name":"Serpens: Privacy-Preserving Inference through Conditional Separable of Convolutional Neural Networks","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306317401","doi":"https://doi.org/10.1145/3511808.3557450"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557450","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557450","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","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/A5091907725","display_name":"Longlong Sun","orcid":"https://orcid.org/0000-0002-7032-4866"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Longlong Sun","raw_affiliation_strings":["Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100423964","display_name":"Hui Li","orcid":"https://orcid.org/0000-0003-2382-6289"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Li","raw_affiliation_strings":["Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003941820","display_name":"Yanguo Peng","orcid":"https://orcid.org/0000-0002-3210-0714"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanguo Peng","raw_affiliation_strings":["Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048420839","display_name":"Jiangtao Cui","orcid":"https://orcid.org/0000-0001-5569-0780"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangtao Cui","raw_affiliation_strings":["Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5091907725"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.2087,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.42787493,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1837","last_page":"1847"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","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/T10237","display_name":"Cryptography and Data Security","score":0.9994000196456909,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9980000257492065,"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":0.7783724069595337},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6843839287757874},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6748001575469971},{"id":"https://openalex.org/keywords/plaintext","display_name":"Plaintext","score":0.6743646860122681},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.605169415473938},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.49753883481025696},{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.47661152482032776},{"id":"https://openalex.org/keywords/cryptography","display_name":"Cryptography","score":0.4645616114139557},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.43929582834243774},{"id":"https://openalex.org/keywords/separable-space","display_name":"Separable space","score":0.4337725043296814},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.360612154006958},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2971571683883667},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.2615029215812683},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11489373445510864}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7783724069595337},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6843839287757874},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6748001575469971},{"id":"https://openalex.org/C92717368","wikidata":"https://www.wikidata.org/wiki/Q1162538","display_name":"Plaintext","level":3,"score":0.6743646860122681},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.605169415473938},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.49753883481025696},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.47661152482032776},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.4645616114139557},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.43929582834243774},{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.4337725043296814},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.360612154006958},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2971571683883667},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2615029215812683},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11489373445510864},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3511808.3557450","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557450","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1966731635","https://openalex.org/W2112796928","https://openalex.org/W2152926062","https://openalex.org/W2162538292","https://openalex.org/W2226167778","https://openalex.org/W2400124473","https://openalex.org/W2573908344","https://openalex.org/W2747329762","https://openalex.org/W2754237067","https://openalex.org/W2768174108","https://openalex.org/W2794888826","https://openalex.org/W2811323882","https://openalex.org/W2899140612","https://openalex.org/W2912213068","https://openalex.org/W2982083293","https://openalex.org/W2985527074","https://openalex.org/W2994111940","https://openalex.org/W3008493372","https://openalex.org/W3028867652","https://openalex.org/W3035490021","https://openalex.org/W6778434676"],"related_works":["https://openalex.org/W1657880117","https://openalex.org/W2595172197","https://openalex.org/W2127970246","https://openalex.org/W2084856301","https://openalex.org/W1001352512","https://openalex.org/W4382618745","https://openalex.org/W2885125400","https://openalex.org/W2281112860","https://openalex.org/W3092327956","https://openalex.org/W2048539412"],"abstract_inverted_index":{"With":[0],"the":[1,48,115,125,160,166,170,178,186],"extensive":[2],"usage":[3],"of":[4,51,69,117,172],"convolutional":[5],"neural":[6],"networks":[7],"(CNNs),":[8],"privacy":[9],"issues":[10],"within":[11],"practical":[12],"applications":[13],"have":[14,32],"attracted":[15],"much":[16],"attention,":[17],"especially":[18],"when":[19],"deep":[20],"learning":[21],"services":[22],"are":[23,38,99],"provided":[24],"by":[25,59],"third-party":[26],"clouds.":[27],"Many":[28],"private":[29,107,162],"inference":[30,49,108,163,188],"schemes":[31],"been":[33],"proposed,":[34],"but":[35],"their":[36],"overheads":[37],"still":[39],"too":[40],"large.":[41],"In":[42],"this":[43,63],"work,":[44],"we":[45,65,94,103,133],"find":[46],"that":[47,97,154],"procedure":[50],"CNNs":[52,83,98],"can":[53,84],"be":[54,85],"separated":[55],"and":[56,74,123,143,148,169],"performed":[57],"synergistically":[58],"many":[60],"parties.":[61],"Following":[62],"observation,":[64],"present":[66],"a":[67,80,106],"pair":[68],"novel":[70],"notions,":[71],"namely":[72],"separable":[73],"conditional":[75],"separable,":[76],"to":[77,120],"tell":[78],"whether":[79],"layer":[81],"in":[82,165,177],"exactly":[86],"computed":[87],"over":[88,189],"multiple":[89],"parties":[90],"or":[91],"not.":[92],"Besides,":[93],"also":[95],"prove":[96],"conditionally":[100],"separable.":[101],"Accordingly,":[102],"propose":[104],"Serpens,":[105],"framework":[109],"under":[110],"multi-server":[111],"settings.":[112,150],"Serpens":[113,155,173],"reduces":[114],"overhead":[116],"linear":[118],"layers":[119],"almost":[121],"zero,":[122],"now":[124],"computing":[126],"bottleneck":[127],"is":[128,156,174],"ReLU.":[129],"To":[130],"address":[131],"that,":[132],"design":[134],"two":[135],"secure":[136],"ReLU":[137],"protocols":[138],"based":[139],"on":[140],"homomorphic":[141],"encryption":[142],"random":[144],"masks":[145],"for":[146],"two-":[147],"three-server":[149,179],"Experimental":[151],"results":[152],"show":[153],"78x-105x":[157],"faster":[158],"than":[159,184],"state-of-the-art":[161],"scheme":[164],"two-server":[167],"setting,":[168,180],"superiority":[171],"even":[175],"larger":[176],"only":[181],"11x-64x":[182],"slower":[183],"performing":[185],"same":[187],"plaintext":[190],"images.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}