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In this article, we propose to contribute to this direction by studying the impact of some particular deep learning techniques for tackling side-channel attack problems. More precisely, we propose to focus on three existing techniques: batch normalization, dropout, and weight decay, not yet used in side-channel context. By combining adequately these techniques for our problem, we show that it is possible to improve the attack performance, i.e., the number of traces needed to recover the secret, by more than 55%. Additionally, they allow us to have a gain of more than 34% in terms of training time. We also show that an architecture trained with such techniques is able to perform attacks efficiently even in the context of desynchronized traces.<\/jats:p>","DOI":"10.1145\/3453162","type":"journal-article","created":{"date-parts":[[2021,6,30]],"date-time":"2021-06-30T19:26:58Z","timestamp":1625081218000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Improving Deep Learning Networks for Profiled Side-channel Analysis Using Performance Improvement Techniques"],"prefix":"10.1145","volume":"17","author":[{"given":"Damien","family":"Robissout","sequence":"first","affiliation":[{"name":"Univ Lyon, UJM-Saint-Etienne, CNRS Laboratoire Hubert Curien UMR 5516 F-42023, Saint-Etienne, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lilian","family":"Bossuet","sequence":"additional","affiliation":[{"name":"Univ Lyon, UJM-Saint-Etienne, CNRS Laboratoire Hubert Curien UMR 5516 F-42023, Saint-Etienne, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amaury","family":"Habrard","sequence":"additional","affiliation":[{"name":"Univ Lyon, UJM-Saint-Etienne, CNRS Laboratoire Hubert Curien UMR 5516 F-42023, Saint-Etienne, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vincent","family":"Grosso","sequence":"additional","affiliation":[{"name":"Univ Lyon, UJM-Saint-Etienne, CNRS Laboratoire Hubert Curien UMR 5516F-42023, Saint-Etienne, France and CNRS, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,6,30]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/648255.752713"},{"key":"e_1_2_1_2_1","article-title":"Deep learning for side-channel analysis and introduction to ASCAD database","author":"Benadjila Ryad","year":"2019","unstructured":"Ryad Benadjila , Emmanuel Prouff , R\u00e9mi Strullu , Eleonora Cagli , and C\u00e9cile Dumas . 2019 . 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