{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T00:16:31Z","timestamp":1767917791333,"version":"3.49.0"},"reference-count":40,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,5,1]],"date-time":"2023-05-01T00:00:00Z","timestamp":1682899200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,5,1]],"date-time":"2023-05-01T00:00:00Z","timestamp":1682899200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,5,1]]},"DOI":"10.1109\/host55118.2023.10133266","type":"proceedings-article","created":{"date-parts":[[2023,5,25]],"date-time":"2023-05-25T17:29:36Z","timestamp":1685035776000},"page":"315-325","source":"Crossref","is-referenced-by-count":7,"title":["VPP: Privacy Preserving Machine Learning via Undervolting"],"prefix":"10.1109","author":[{"given":"Md Shohidul","family":"Islam","sequence":"first","affiliation":[{"name":"George Mason University,CSE Dept., DUET, Bangladesh,Fairfax,VA,USA"}]},{"given":"Behnam","family":"Omidi","sequence":"additional","affiliation":[{"name":"George Mason University,ECE Department,Fairfax,VA,USA"}]},{"given":"Ihsen","family":"Alouani","sequence":"additional","affiliation":[{"name":"Queen&#x2019;s University Belfast,CSIT,UK"}]},{"given":"Khaled N.","family":"Khasawneh","sequence":"additional","affiliation":[{"name":"George Mason University,ECE Department,Fairfax,VA,USA"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3036336"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-17419-7"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2021.3068873"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAD51958.2021.9643551"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ISQED51717.2021.9424310"},{"key":"ref6","article-title":"Enhancing hardware malware detectors security through voltage over-scaling","volume-title":"in 2021 5th ACM SIGARCH Workshop on Cognitive Architectures","author":"Islam"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCD50377.2020.00096"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ISQED48828.2020.9136987"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3240765.3243463"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN55064.2022.9892437"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/SEED51797.2021.00011"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i11.17150"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.41"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00065"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1000167"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978318"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3243734.3243855"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3363201"},{"key":"ref19","article-title":"Mitigating membership inference at-tacks by self-distillation through a novel ensemble architecture","author":"Tang","year":"2021","journal-title":"arXiv preprint arXiv:2110.08324"},{"key":"ref20","article-title":"Semi-supervised knowledge transfer for deep learning from private training data","volume-title":"in International Conference on Learning and Represen-tation (ICLR)","author":"Papernot"},{"key":"ref21","article-title":"Scalable private learning with pate","volume-title":"in International Conference on Learning and Representation (ICLR)","author":"Papernot"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"issue":"1","key":"ref23","first-page":"1929","article-title":"Dropout: a simple way to prevent neural networks from over-fitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"The journal of machine learning research"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3460120.3484575"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/HOST49136.2021.9702287"},{"key":"ref26","article-title":"Chaidnn-v2: Hls based deep neural network accelerator library for xilinx ultrascale + mpsocs","author":"Xilinx","year":"2022"},{"key":"ref27","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014","journal-title":"arXiv preprint arXiv:1409.1556"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref31","article-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TCSII.2012.2231036"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/1176760.1176781"},{"key":"ref34","first-page":"2615","article-title":"Systematic evaluation of privacy risks of ma-chine learning models","author":"Song","year":"2021","journal-title":"in 30th USENIX Security Symposium (USENIX Security 21)"},{"key":"ref35","article-title":"Acquire valued shoppers challenge","author":"P","year":"2017"},{"key":"ref36","article-title":"Texas hospital stays dataset","author":"T","year":"2017"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CSF.2018.00027"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2019.23119"},{"key":"ref39","first-page":"1964","article-title":"Label-only membership inference attacks","volume-title":"in International Conference on Machine Learning. PMLR","author":"Choquette-Choo"},{"key":"ref40","article-title":"Defending model inversion and membership inference attacks via prediction purification","author":"Yang","year":"2020","journal-title":"arXiv preprint arXiv:2005.03915"}],"event":{"name":"2023 IEEE International Symposium on Hardware Oriented Security and Trust (HOST)","location":"San Jose, CA, USA","start":{"date-parts":[[2023,5,1]]},"end":{"date-parts":[[2023,5,4]]}},"container-title":["2023 IEEE International Symposium on Hardware Oriented Security and Trust (HOST)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10132842\/10132914\/10133266.pdf?arnumber=10133266","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,14]],"date-time":"2024-03-14T12:06:24Z","timestamp":1710417984000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10133266\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,1]]},"references-count":40,"URL":"https:\/\/doi.org\/10.1109\/host55118.2023.10133266","relation":{},"subject":[],"published":{"date-parts":[[2023,5,1]]}}}