Revolutionary hybrid ensembled deep learning model for accurate and robust side-channel attack detection in cloud computing

Cryptographic systems are essential for securing sensitive information but are increasingly susceptible to side-channel attacks (SCAs) that exploit physical data leakages. In cloud computing environments, where resources shared across multiple tenants, detecting SCAs becomes particularly challenging...

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Vydané v:	Scientific reports Ročník 15; číslo 1; s. 32949 - 29
Hlavní autori:	Reddy, C. Lakshminatha, Malathi, K.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Nature Publishing Group UK 26.09.2025 Nature Publishing Group Nature Portfolio
Predmet:	639/166 639/705 Access to information Cloud computing Convolutional neural networks Cryptographic systems Deep learning Humanities and Social Sciences Long short-term memory Machine learning multidisciplinary Neural networks Science Science (multidisciplinary) Side-channel attacks Software Deep learning Cloud computing Attention mechanism Hybrid ensembled deep learning model Side-channel attacks Cryptographic systems Long short-term memory Cybersecurity Convolutional neural networks AutoEncoder
ISSN:	2045-2322, 2045-2322
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