Open Access

ARTICLE

Secured ECG Signal Transmission Using Optimized EGC with Chaotic Neural Network in WBSN

Ishani Mishra^1,*, Sanjay Jain², Vivek Maik³

1 Department of ECE, New Horizon College of Engineering, Bengaluru, 560103, India
2 CMR Institute of Technology, Bengaluru, 560037, India
3 SRM University, Chennai, 603203, India

* Corresponding Author: Ishani Mishra. Email:

Computer Systems Science and Engineering 2023, 44(2), 1109-1123. https://doi.org/10.32604/csse.2023.025999

Received 12 December 2021; Accepted 24 January 2022; Issue published 15 June 2022

Abstract

In wireless body sensor network (WBSN), the set of electrocardiogram (ECG) data which is collected from sensor nodes and transmitted to the server remotely supports the experts to monitor the health of a patient. While transmitting these collected data some adversaries may capture and misuse it due to the compromise of security. So, the major aim of this work is to enhance secure transmission of ECG signal in WBSN. To attain this goal, we present Pity Beetle Swarm Optimization Algorithm (PBOA) based Elliptic Galois Cryptography (EGC) with Chaotic Neural Network. To optimize the key generation process in Elliptic Curve Cryptography (ECC) over Galois field or EGC, private key is chosen optimally using PBOA algorithm. Then the encryption process is enhanced by presenting chaotic neural network which is used to generate chaotic sequences or cipher data. Results of this work show that the proposed cryptography algorithm attains better encryption time, decryption time, throughput and SNR than the conventional cryptography algorithms.

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Keywords

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