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Secure hash algorithm based on efficient chaotic neural network

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dc.contributor.author Abdoun, Nabil
dc.contributor.author El Assad, Safwan
dc.contributor.author Abutaha, Mohammed
dc.contributor.author Assaf, Rima
dc.contributor.author Deforges, Olivier
dc.contributor.author Khalil, Mohamad
dc.date.accessioned 2020-12-09T09:22:54Z
dc.date.accessioned 2022-05-22T08:52:20Z
dc.date.available 2020-12-09T09:22:54Z
dc.date.available 2022-05-22T08:52:20Z
dc.date.issued 2016
dc.identifier.uri http://localhost:8080/xmlui/handle/123456789/8090
dc.description.abstract Secure Hash Algorithm (SHA) is the most popular standard of Cryptographic Hash functions. Several security protocols use SHA to provide message integrity, authentication and digital signature. Nowadays, a new technology based on Chaotic Neural Networks is used to design Hash functions due to the following important properties of Chaos and Neural Networks: non-linearity, compression, confusion and diffusion. Compared to existing Hash functions based on Chaotic Neural Networks, the proposed structure integrates a strong Chaotic generator into neurons instead of using simple Chaotic maps. In fact, simple chaotic maps are not very robust, even against some statistical attacks (Uniformity and NIST). To also reduce the complexity of hash function proposed in ICITST conference (2015), while maintaining strength, we present in this paper a new structure of Hash function
dc.publisher IEEE
dc.title Secure hash algorithm based on efficient chaotic neural network

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