{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T15:09:49Z","timestamp":1730214589878,"version":"3.28.0"},"reference-count":13,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/dft50435.2020.9250869","type":"proceedings-article","created":{"date-parts":[[2020,11,11]],"date-time":"2020-11-11T22:04:48Z","timestamp":1605132288000},"page":"1-4","source":"Crossref","is-referenced-by-count":1,"title":["Evaluating Data Encryption Effects on the Resilience of an Artificial Neural Network"],"prefix":"10.1109","member":"263","reference":[{"doi-asserted-by":"publisher","key":"ref10","DOI":"10.1109\/ACCESS.2017.2742698"},{"doi-asserted-by":"publisher","key":"ref11","DOI":"10.1145\/3126908.3126964"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1109\/LATW.2019.8704548"},{"year":"0","author":"van winkle","journal-title":"C Neural Network Library Genann","key":"ref13"},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.1109\/SOCC.2015.7406921"},{"doi-asserted-by":"publisher","key":"ref3","DOI":"10.1109\/ETS.2019.8791552"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1109\/LATS49555.2020.9093670"},{"doi-asserted-by":"publisher","key":"ref5","DOI":"10.1109\/LCA.2016.2623628"},{"key":"ref8","article-title":"Resiliency of Deep Neural Networks under Quantization","volume":"abs 1511 6488","author":"sung","year":"2015","journal-title":"CoRR"},{"doi-asserted-by":"publisher","key":"ref7","DOI":"10.17487\/rfc2315"},{"key":"ref2","first-page":"601","article-title":"Stealing machine learning models via prediction apis","author":"tram\u00e8r","year":"2016","journal-title":"25th USENIX Conference on Security Symposium ser SEC&#x2019;16"},{"doi-asserted-by":"publisher","key":"ref1","DOI":"10.1038\/nature14539"},{"key":"ref9","article-title":"A survey of FPGA-based accelerators for convolutional neural networks","author":"mittal","year":"2018","journal-title":"Neural Computing and Applications"}],"event":{"name":"2020 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT)","start":{"date-parts":[[2020,10,19]]},"location":"Frascati, Italy","end":{"date-parts":[[2020,10,21]]}},"container-title":["2020 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9250742\/9250725\/09250869.pdf?arnumber=9250869","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T15:44:53Z","timestamp":1656344693000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9250869\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":13,"URL":"https:\/\/doi.org\/10.1109\/dft50435.2020.9250869","relation":{},"subject":[],"published":{"date-parts":[[2020]]}}}