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Syst."],"published-print":{"date-parts":[[2022,1,31]]},"abstract":"<jats:p>\n            This work presents a\n            <jats:bold>Cross-device Deep-Learning based Electromagnetic (EM-X-DL) side-channel analysis (SCA)<\/jats:bold>\n            on AES-128, in the presence of a significantly lower\n            <jats:bold>signal-to-noise ratio (SNR)<\/jats:bold>\n            compared to previous works. Using a novel algorithm to intelligently select multiple training devices and proper choice of hyperparameters, the proposed 256-class\n            <jats:bold>deep neural network (DNN)<\/jats:bold>\n            can be trained efficiently utilizing pre-processing techniques like PCA, LDA, and FFT on measurements from the target encryption engine running on an 8-bit Atmel microcontroller. In this way, EM-X-DL achieves &gt;90% single-trace attack accuracy. Finally, an efficient end-to-end SCA leakage detection and attack framework using EM-X-DL demonstrates high confidence of an attacker with &lt;20 averaged EM traces.\n          <\/jats:p>","DOI":"10.1145\/3465380","type":"journal-article","created":{"date-parts":[[2021,9,29]],"date-time":"2021-09-29T19:16:42Z","timestamp":1632943002000},"page":"1-17","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":29,"title":["EM-X-DL: Efficient Cross-device Deep Learning Side-channel Attack With Noisy EM Signatures"],"prefix":"10.1145","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5837-1304","authenticated-orcid":false,"given":"Josef","family":"Danial","sequence":"first","affiliation":[{"name":"Purdue University, West Lafayette, Indiana, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Debayan","family":"Das","sequence":"additional","affiliation":[{"name":"Purdue University, West Lafayette, Indiana, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anupam","family":"Golder","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology, Atlanta, Georgia, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Santosh","family":"Ghosh","sequence":"additional","affiliation":[{"name":"Intel Corporation, Hillsboro, Oregon, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arijit","family":"Raychowdhury","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology, Atlanta, Georgia, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shreyas","family":"Sen","sequence":"additional","affiliation":[{"name":"Purdue University, West Lafayette, Indiana, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2021,9,29]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/3026877.3026899"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.5555\/648255.752713"},{"key":"e_1_2_1_3_1","volume-title":"International Cryptographic Module Conference","volume":"1001","author":"Becker George","year":"2013","unstructured":"George Becker , J. 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