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Development of GAN-based optimal neural network structure for group synchronization

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Abstract

In this paper, a GAN-based optimal neural network structure for group synchronization is proposed. For generating a key between two parties, asymmetric cryptography is commonly used to exchange the key over an unprotected medium. However, as the approaches that used this technique, such as RSA, have been compromised, new ways to produce a key that can provide protection must be found. To address this problem, a new branch of cryptography known as neural cryptography was developed. The main goal of this neural cryptography is to generate a secret key using an insecure medium. This paper gives an analysis of the ideal neural network configuration for generating and establishing a secret key between the two authenticated entities. Also, research into the synchronization of a group of neural networks is rare. For the design of the public key exchange protocol, a Generative Adversarial Network (GAN)-based synchronization of a group of neural networks with three hidden layers is proposed. For neural synchronization, GAN is used for Pseudo-Random Number Generators (PRNG). More than 15 million simulations were performed to determine the coordination time, steps were taken, and the number of times the attacking neural network could reproduce the behavior of the two approved networks. Various parametric experiments have been conducted on the proposed methodology. In terms of the paper’s cited findings, simulations of the method indicate that it is accurate.

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Acknowledgments

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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Sarkar, A. Development of GAN-based optimal neural network structure for group synchronization. Multimed Tools Appl 81, 28999–29025 (2022). https://doi.org/10.1007/s11042-022-12601-z

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