Abstract
The Wireless Body Sensor Networks (WBSN) play an essential role in remote monitoring for healthcare, sports, disaster relief, military, etc. As the network scalability is expanding, the number of nodes and links is also increasing, further enhancing the computational complexity of the network. WBSN grows as the body-to-body network, and the most significant challenges faced while developing a WBSN are energy consumption and security. Therefore, a Remodeled Chaotic Compressive Sensing (RCCS) network based on the principle of storing matrix generation parameters is proposed in this work. Also, remodeled chaotic sensitivity utilized in the proposed network provides secured data transmission. The measurement matrix measures the physiological data in two directions for achieving compression and encryption simultaneously. The resulting data is encrypted by the operation of the duty shift, which RCCS controls. The secret key used in this algorithm is more sensitive; more than 15 discomposures of the secret key are realized, and it gives 100% relative error. This method provides a better result in image encryption and significant improvement in the security of the network, i.e., the vertical, horizontal, and diagonal, the correlation of adjacent pixels is less than 0.04 pixels in various directions. The cipher image entropy with 256- gray level value is more than 7.98 pixels. The human Body expands by the network in the proposed scheme, and the nodes interact via wireless communication. This system simplifies the required distribution and decreases the data space simultaneously.
Published Version
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