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Intelligent encryption method for wireless sensing signal of underwater vehicles

Intelligent encryption method for wireless sensing signal of underwater vehicles An intelligent encryption method of wireless sensing signal of underwater vehicles based on compressed sensing is proposed. The compressed sensing theory was used to collect the wireless sensing signal of underwater vehicles, observe the signal, reduce the dimension of signal, and then construct the observation matrix. Based on the constructed observation matrix, Hamming window was used to process the wireless sensor signal. After the framing processing, discrete cosine transform was used to enhance the sparsity of wireless sensor signals and improve the effectiveness of encryption. Finally, the signal encryption and decryption were realised by chaotic scrambling and its inverse process. The experimental results showed that compared with the traditional encryption method, the proposed intelligent encryption method had a lower intrusion rate and had better encryption effect via resisting the interference of white noise. The maximum rate of the proposed method was 2.72 KB s−1, the maximum occupied space was 19 KB, and the residual error of the proposed method was the largest when the sparsity was 60, which was 4.5×10−14, which was much lower than that of the other two methods. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Vehicle Information and Communication Systems Inderscience Publishers

Intelligent encryption method for wireless sensing signal of underwater vehicles

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1471-0242
eISSN
1741-8208
DOI
10.1504/ijvics.2022.129034
Publisher site
See Article on Publisher Site

Abstract

An intelligent encryption method of wireless sensing signal of underwater vehicles based on compressed sensing is proposed. The compressed sensing theory was used to collect the wireless sensing signal of underwater vehicles, observe the signal, reduce the dimension of signal, and then construct the observation matrix. Based on the constructed observation matrix, Hamming window was used to process the wireless sensor signal. After the framing processing, discrete cosine transform was used to enhance the sparsity of wireless sensor signals and improve the effectiveness of encryption. Finally, the signal encryption and decryption were realised by chaotic scrambling and its inverse process. The experimental results showed that compared with the traditional encryption method, the proposed intelligent encryption method had a lower intrusion rate and had better encryption effect via resisting the interference of white noise. The maximum rate of the proposed method was 2.72 KB s−1, the maximum occupied space was 19 KB, and the residual error of the proposed method was the largest when the sparsity was 60, which was 4.5×10−14, which was much lower than that of the other two methods.

Journal

International Journal of Vehicle Information and Communication SystemsInderscience Publishers

Published: Jan 1, 2022

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