Secure multi-party computation in deep learning : Enhancing privacy in distributed neural networks

Ensuring data privacy while applying Deep Learning (DL) on distributed datasets represents an essential task in the current period of critical data security. Data privacy and accuracy of models are typically impacted by traditional methods. Data privacy is of the most tremendous significance in dist...

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Vydané v:	Journal of discrete mathematical sciences & cryptography Ročník 27; číslo 2-A; s. 249 - 259
Hlavní autori:	Sagar, P. Vidya, Ghanimi, Hayder M. A., Prabhu, L. Arokia Jesu, Raja, L., Dadheech, Pankaj, Sengan, Sudhakar
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	01.03.2024
ISSN:	0972-0529, 2169-0065
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