Publication Type:

Journal Article

Source:

Journal of Interdisciplinary Mathematics, Taylor & Francis, Volume 23, Number 2, p.435-451 (2020)

URL:

https://doi.org/10.1080/09720502.2020.1731956

Abstract:

Abstract Security is considered as an important anxiety for applications which involve communication (more than two) over public networks. Group key management is one of the essential building blocks in securing group communication. Most of the researches in group key management are based on the general idea of the original Diffie–Hellman (DH) key agreement protocol. The major drawback of generalized DH for multi-party is the fact that there are expensive exponential operations to be carried out. The factors that influence the capability of a Group Key agreement (GKA) protocol are communication rounds and the computational cost. In this paper, the concept of neural cryptography, based on the mutual learning of Tree Parity Machine (TPM), is extended to operations to be carried out. The factors that influence the capability of a Group Key agreement (GKA) protocol are communication rounds and the computational cost. In this paper, the concept of neural cryptography, based on the mutual learning of Tree Parity Machine (TPM), is extended to obtain a group key. The group key has been generated for an interactive conference key agreement system, where the system authenticates the users and allows them to compute their own session key, and also it has been recognized that the neural network based GKA protocols achieve key freshness and key secrecy. The quantity demand and investment in research and development, while the other model focuses on a more realistic relationship between the quantity demand and the price.

Cite this Research Publication

Dr. S. Santhanalakshmi, Sangeeta, K., and Patra, G. K., “Design of group key agreement protocol using neural key synchronization”, Journal of Interdisciplinary Mathematics, vol. 23, pp. 435-451, 2020.