{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T20:18:46Z","timestamp":1740169126745,"version":"3.37.3"},"reference-count":34,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100004298","name":"Secom Science and Technology Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004298","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003382","name":"Core Research for Evolutional Science and Technology","doi-asserted-by":"publisher","award":["JPMJCR19F6"],"id":[{"id":"10.13039\/501100003382","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2939410","type":"journal-article","created":{"date-parts":[[2019,9,4]],"date-time":"2019-09-04T20:09:12Z","timestamp":1567627752000},"page":"139021-139034","source":"Crossref","is-referenced-by-count":8,"title":["MOBIUS: Model-Oblivious Binarized Neural Networks"],"prefix":"10.1109","volume":"7","author":[{"given":"Hiromasa","family":"Kitai","sequence":"first","affiliation":[]},{"given":"Goichiro","family":"Hanaoka","sequence":"additional","affiliation":[]},{"given":"Jason Paul","family":"Cruz","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0817-6188","authenticated-orcid":false,"given":"Naoto","family":"Yanai","sequence":"additional","affiliation":[]},{"given":"Naohisa","family":"Nishida","sequence":"additional","affiliation":[]},{"given":"Tatsumi","family":"Oba","sequence":"additional","affiliation":[]},{"given":"Yuji","family":"Unagami","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4362-4887","authenticated-orcid":false,"given":"Tadanori","family":"Teruya","sequence":"additional","affiliation":[]},{"given":"Nuttapong","family":"Attrapadung","sequence":"additional","affiliation":[]},{"given":"Takahiro","family":"Matsuda","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"journal-title":"The transport layer security (TLS) protocol version 1 1","year":"2008","author":"rescorla","key":"ref33"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-88313-5_13"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/359168.359176"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/3274694.3274740"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1137\/090755886"},{"key":"ref10","first-page":"201","article-title":"Cryptonets: Applying neural networks to encrypted data with high throughput and accuracy","author":"gilad-bachrach","year":"2016","journal-title":"Proc ICML"},{"article-title":"Private collaborative neural network learning","year":"2017","author":"chase","key":"ref11"},{"article-title":"Fast homomorphic evaluation of deep discretized neural networks","year":"2017","author":"bourse","key":"ref12"},{"article-title":"Securenn: Efficient and private neural network training","year":"2018","author":"wagh","key":"ref13"},{"key":"ref14","article-title":"Tapas: Tricks to accelerate (encrypted) prediction as a service","author":"sanyal","year":"2018","journal-title":"Proc ICML 2018"},{"key":"ref15","article-title":"Binarized neural networks: Training deep neural networks with weights and activations constrained to +1 or ?1","author":"courbariaux","year":"2016","journal-title":"arXiv 1602 02830 [cs]"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/1536414.1536440"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2015.23113"},{"key":"ref18","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"Proc of im"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/11681878_15"},{"key":"ref28","first-page":"1705","article-title":"The bernstein mechanism: Function release under differential privacy","author":"ald\u00e0","year":"2017","journal-title":"Proc AAAI"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134056"},{"key":"ref27","first-page":"26","article-title":"Comparing population means under local differential privacy: With significance and power","author":"ding","year":"2018","journal-title":"Proc AAAI"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2015.23241"},{"article-title":"EzPC: Programmable, efficient, and scalablesecure two-party computation for machine learning","year":"2017","author":"chandran","key":"ref6"},{"key":"ref29","first-page":"601","article-title":"Stealing machine learning models via prediction apis","author":"tram\u00e8r","year":"2016","journal-title":"Proc USENIX Security07"},{"key":"ref5","article-title":"Deepsecure: Scalable provably-secure deep learning","author":"rouhani","year":"2017","journal-title":"arXiv 1705 08963"},{"key":"ref8","article-title":"Gazelle: A low latency framework for secure neural network inference","author":"juvekar","year":"2018","journal-title":"arXiv 1801 05507"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3196494.3196522"},{"key":"ref2","article-title":"Oblivious neural network computing via homomorphic encryption","volume":"1","author":"orlandi","year":"2007","journal-title":"EURASIP J Inf Secur"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.12"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/1161366.1161393"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-46800-5_25"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-14577-3_6"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3243734.3243760"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/11787006_1"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15317-4_13"},{"key":"ref26","first-page":"429","article-title":"Local privacy and statistical minimax rates","author":"duchi","year":"2013","journal-title":"Proc FOCS"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978318"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08824120.pdf?arnumber=8824120","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,10]],"date-time":"2021-08-10T19:40:48Z","timestamp":1628624448000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8824120\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2939410","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2019]]}}}