Constructing Highly Nonlinear Cryptographic Balanced Boolean Functions on Learning Capabilities of Recurrent Neural Networks
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DOI: 10.1109/access.2024.3477260
Abstract: This study presents a novel approach to cryptographic algorithm design that harnesses the power of recurrent neural networks. Unlike traditional mathematical-based methods, neural networks offer nonlinear models that excel at capturing chaotic behavior within systems.… read more here.
Keywords: cryptographic balanced; neural networks; highly nonlinear; recurrent neural ... See more keywords