Concurring of Neural Machines for Robust Session Key Generation and Validation in Telecare Health System During COVID-19 Pandemic.

Abstract

In this technique, it has been proposed to agree the session keys that have been generated through dual artificial neural networks based on the Telecare Health COVID-19 domain. Electronic health enables secure and protected communication between the patients and physicians, especially during this COVID-19 pandemic. Telecare was the main component which served the remote and non-invasive patients in the crisis period of COVID-19. Neural cryptographic engineering support in terms of data security and privacy is the main theme for Tree Parity Machine (TPM) synchronization in this paper. The session key has been generated on different key lengths and key validation done on the proposed set of robust session keys. A neural TPM network receives a vector designed through same random seed and producing a single output bit. Duo neural TPM networks' intermediate keys would be partially shared between the patient and doctor for the purpose neural synchronization. Higher magnitude of co-existence has been observed at the duo neural networks at the Telecare Health Systems in COVID-19. This proposed technique has been highly protective against several data attacks in the public networks. Partial transmission of the session key disables the intruders to guess the exact pattern, and highly randomized through different tests. The average p-values of different session key lengths of 40 bits, 60 bits, 160 bits, and 256 bits were observed to be 221.9, 259.3, 242, and 262.8 (taken under multiplicative of 1000) respectively.