Deep learning steganography for big data security using squeeze and excitation with inception architectures

Abstract With the exponential growth of big data in domains such as telemedicine and digital forensics, the secure transmission of sensitive medical information has become a critical concern. Conventional steganographic methods often fail to maintain diagnostic integrity or exhibit robustness agains...

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Bibliografiske detaljer

Principais autores:	Bini M. Issac, S. N. Kumar, Sherin Zafar, Kashish Ara Shakil, Mudasir Ahmad Wani
Format:	Artigo
Sprog:	Inglês
Udgivet:	Nature Portfolio 2025-08-01
Serier:	Scientific Reports
Fag:	Medical image security Steganography Squeeze-and-Excitation Inception module Deep learning Jetson TX2
Online adgang:	https://doi.org/10.1038/s41598-025-16394-7
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