{"id":"https://openalex.org/W4308642160","doi":"https://doi.org/10.1145/3548606.3563543","title":"Poster","display_name":"Poster","publication_year":2022,"publication_date":"2022-11-07","ids":{"openalex":"https://openalex.org/W4308642160","doi":"https://doi.org/10.1145/3548606.3563543"},"language":"en","primary_location":{"id":"doi:10.1145/3548606.3563543","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3548606.3563543","pdf_url":null,"source":{"id":"https://openalex.org/S4363608815","display_name":"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security","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 2022 ACM SIGSAC Conference on Computer and Communications Security","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101419902","display_name":"Bingyu Liu","orcid":"https://orcid.org/0000-0002-4537-3498"},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bingyu Liu","raw_affiliation_strings":["Illinois Institute of Technology, Chicago, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Illinois Institute of Technology, Chicago, IL, USA","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073855975","display_name":"Rujia Wang","orcid":"https://orcid.org/0000-0003-4019-5327"},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rujia Wang","raw_affiliation_strings":["Illinois Institute of Technology, Chicago, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Illinois Institute of Technology, Chicago, IL, USA","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072485378","display_name":"Zhongjie Ba","orcid":"https://orcid.org/0000-0003-0921-8869"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongjie Ba","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070625162","display_name":"Shanglin Zhou","orcid":"https://orcid.org/0000-0002-6409-7716"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shanglin Zhou","raw_affiliation_strings":["University of Connecticut, Storrs, CT, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002899157","display_name":"Caiwen Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Caiwen Ding","raw_affiliation_strings":["University of Connecticut, Storrs, CT, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100725148","display_name":"Yuan Hong","orcid":"https://orcid.org/0000-0003-4095-4506"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuan Hong","raw_affiliation_strings":["University of Connecticut, Storrs, CT, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3395","last_page":"3397"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9975000023841858,"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":0.9975000023841858,"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/T11017","display_name":"Chaos-based Image/Signal Encryption","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9957000017166138,"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":0.8426942825317383},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7156468629837036},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.594955325126648},{"id":"https://openalex.org/keywords/cryptography","display_name":"Cryptography","score":0.5903398990631104},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5664708614349365},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.5366363525390625},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5024101734161377},{"id":"https://openalex.org/keywords/cryptographic-primitive","display_name":"Cryptographic primitive","score":0.49475520849227905},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.46828290820121765},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4611971378326416},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41861987113952637},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36841481924057007},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34695327281951904},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.24747434258460999},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.21606937050819397},{"id":"https://openalex.org/keywords/cryptographic-protocol","display_name":"Cryptographic protocol","score":0.19819733500480652},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.07809004187583923}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8426942825317383},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7156468629837036},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.594955325126648},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.5903398990631104},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5664708614349365},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.5366363525390625},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5024101734161377},{"id":"https://openalex.org/C15927051","wikidata":"https://www.wikidata.org/wiki/Q246593","display_name":"Cryptographic primitive","level":4,"score":0.49475520849227905},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.46828290820121765},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4611971378326416},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41861987113952637},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36841481924057007},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34695327281951904},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.24747434258460999},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.21606937050819397},{"id":"https://openalex.org/C33884865","wikidata":"https://www.wikidata.org/wiki/Q1254335","display_name":"Cryptographic protocol","level":3,"score":0.19819733500480652},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.07809004187583923},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3548606.3563543","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3548606.3563543","pdf_url":null,"source":{"id":"https://openalex.org/S4363608815","display_name":"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security","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 2022 ACM SIGSAC Conference on Computer and Communications Security","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G3155510453","display_name":null,"funder_award_id":"CNS-2046335 and CNS-2034870","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1522734439","https://openalex.org/W2088492763","https://openalex.org/W2177209050","https://openalex.org/W2435473771","https://openalex.org/W2765200655","https://openalex.org/W2767079719","https://openalex.org/W2783769334","https://openalex.org/W2801491268","https://openalex.org/W2889746123","https://openalex.org/W2949140995","https://openalex.org/W2963524571","https://openalex.org/W3138596485","https://openalex.org/W3173524712"],"related_works":["https://openalex.org/W3128807919","https://openalex.org/W3176411177","https://openalex.org/W18954787","https://openalex.org/W3138083505","https://openalex.org/W4254460476","https://openalex.org/W2783353176","https://openalex.org/W2339543721","https://openalex.org/W1514794536","https://openalex.org/W1829339118","https://openalex.org/W87530933"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"network":[2],"(DNN)":[3],"services":[4],"have":[5,60,98],"been":[6,61],"widely":[7],"deployed":[8],"in":[9,44,154],"many":[10],"different":[11],"domains.":[12],"For":[13],"instance,":[14],"a":[15],"client":[16,77],"may":[17],"send":[18],"its":[19],"private":[20],"input":[21],"data":[22,51],"(e.g.,":[23],"images,":[24],"texts":[25],"and":[26,67,78,103,122,144,157,162,204],"videos)":[27],"to":[28,48,63,176],"the":[29,49,68,124,147,155],"cloud":[30],"for":[31,90,94,105,112,214],"accurate":[32,113],"inferences":[33,56,74,177],"with":[34,57,137,146,160,178],"pre-trained":[35],"DNN":[36],"models.":[37,164],"However,":[38,80],"significant":[39],"privacy":[40,139],"concerns":[41],"would":[42],"emerge":[43],"such":[45,65,117],"applications":[46],"due":[47],"potential":[50],"or":[52],"model":[53],"sharing.":[54],"Secure":[55],"cryptographic":[58,84,126],"techniques":[59],"proposed":[62],"address":[64,116],"issues,":[66],"system":[69],"can":[70],"perform":[71],"secure":[72],"two-party":[73],"between":[75],"each":[76],"cloud.":[79],"most":[81],"of":[82,216],"existing":[83,172],"systems":[85,149,173],"only":[86],"focus":[87],"on":[88,101,134,150],"DNNs":[89],"extracting":[91,106],"2D":[92],"features":[93,109,136],"image":[95],"inferences,":[96],"which":[97,130],"major":[99],"limitations":[100],"latency":[102],"scalability":[104],"spatio-temporal":[107],"(3D)":[108],"from":[110],"videos":[111,133,153],"inferences.":[114],"To":[115],"critical":[118],"deficiencies,":[119],"we":[120],"design":[121],"implement":[123],"first":[125],"inference":[127],"system,":[128],"Crypto3D,":[129],"privately":[131,151],"infers":[132],"3D":[135,179],"rigorous":[138],"guarantees.":[140],"We":[141],"evaluate":[142],"Crypto3D":[143,169],"benchmark":[145],"state-of-the-art":[148],"inferring":[152],"UCF-101":[156],"HMDB-51":[158],"datasets":[159],"C3D":[161],"I3D":[163],"Our":[165],"results":[166],"demonstrate":[167],"that":[168],"significantly":[170],"outperforms":[171],"(substantially":[174],"extended":[175],"features):":[180],"execution":[181],"time:":[182],"186.89x":[183],"vs.":[184,188,192,196,200,206,211],"CryptoDL":[185],"(3D),":[186,190,194,198,203],"63.75x":[187],"HEANN":[189],"61.52x":[191],"MP-SPDZ":[193],"45x":[195],"E2DM":[197],"3.74x":[199],"Intel":[201],"SGX":[202],"3x":[205],"Gazelle":[207],"(3D);":[208],"accuracy:":[209],"82.3%":[210],"below":[212],"70%":[213],"all":[215],"them.":[217]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2022-11-13T00:00:00"}