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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Veröffentlicht in:	Journal of discrete mathematical sciences & cryptography Jg. 27; H. 2-A; S. 249 - 259
Hauptverfasser:	Sagar, P. Vidya, Ghanimi, Hayder M. A., Prabhu, L. Arokia Jesu, Raja, L., Dadheech, Pankaj, Sengan, Sudhakar
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	01.03.2024
ISSN:	0972-0529, 2169-0065
Online-Zugang:	Volltext
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