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Neural cryptography using optimal structure of neural networks

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Abstract

The asymmetric cryptography method is typically used to transfer the key via an insecure channel while creating a key between two parties. However, since the methods using this strategy, like RSA, are now breached, new strategies must be sought to generate a key that can provide security. To solve this issue, a new group of cryptography was created known as neural cryptography. The main objective of this neural cryptography is to create a secret key using an unsafe medium. This paper suggests an overview of the optimal configuration of the neural network that enables the generation and establishment of a secret key between the two approved entities. Synchronization of two neural networks with three hidden layers is proposed for the development of the public key exchange protocol. Over 15 million simulations were carried out to measure the synchronization time, the steps taken as well as the number of times the assaulting neural network can replicate the behavior of the two authorized networks. The proposed technique has been passed through different parametric tests. Simulations of the process show effectiveness in terms of cited results in the paper.

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Acknowledgements

The author expressed deep gratitude for the moral and congenial atmosphere support provided by Ramakrishna Mission Vidyamandira, Belur Math, India.

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This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.his research received no external fundings.

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  1. Department of Computer Science and Electronics, Ramakrishna Mission Vidyamandira, Belur Math, Howrah, 711202, West Bengal, India

    Arindam Sarkar

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Correspondence to Arindam Sarkar.

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Sarkar, A. Neural cryptography using optimal structure of neural networks. Appl Intell 51, 8057–8066 (2021). https://doi.org/10.1007/s10489-021-02334-1

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