Secret Communication Systems Using Chaotic Wave Equations with Neural Network Boundary Conditions

In a secret communication system using chaotic synchronization, the communication information is embedded in a signal that behaves as chaos and is sent to the receiver to retrieve the information. In a previous study, a chaotic synchronous system was developed by integrating the wave equation with t...

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Main Authors: Yuhan Chen, Hideki Sano, Masashi Wakaiki, Takaharu Yaguchi
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/23/7/904
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spelling doaj-39498a02f77940948cd132f67b950a752021-07-23T13:39:50ZengMDPI AGEntropy1099-43002021-07-012390490410.3390/e23070904Secret Communication Systems Using Chaotic Wave Equations with Neural Network Boundary ConditionsYuhan Chen0Hideki Sano1Masashi Wakaiki2Takaharu Yaguchi3Graduate School of System Informatics, Kobe University, Kobe 657-8501, JapanGraduate School of System Informatics, Kobe University, Kobe 657-8501, JapanGraduate School of System Informatics, Kobe University, Kobe 657-8501, JapanGraduate School of System Informatics, Kobe University, Kobe 657-8501, JapanIn a secret communication system using chaotic synchronization, the communication information is embedded in a signal that behaves as chaos and is sent to the receiver to retrieve the information. In a previous study, a chaotic synchronous system was developed by integrating the wave equation with the van der Pol boundary condition, of which the number of the parameters are only three, which is not enough for security. In this study, we replace the nonlinear boundary condition with an artificial neural network, thereby making the transmitted information difficult to leak. The neural network is divided into two parts; the first half is used as the left boundary condition of the wave equation and the second half is used as that on the right boundary, thus replacing the original nonlinear boundary condition. We also show the results for both monochrome and color images and evaluate the security performance. In particular, it is shown that the encrypted images are almost identical regardless of the input images. The learning performance of the neural network is also investigated. The calculated Lyapunov exponent shows that the learned neural network causes some chaotic vibration effect. The information in the original image is completely invisible when viewed through the image obtained after being concealed by the proposed system. Some security tests are also performed. The proposed method is designed in such a way that the transmitted images are encrypted into almost identical images of waves, thereby preventing the retrieval of information from the original image. The numerical results show that the encrypted images are certainly almost identical, which supports the security of the proposed method. Some security tests are also performed. The proposed method is designed in such a way that the transmitted images are encrypted into almost identical images of waves, thereby preventing the retrieval of information from the original image. The numerical results show that the encrypted images are certainly almost identical, which supports the security of the proposed method.https://www.mdpi.com/1099-4300/23/7/904chaotic synchronizationsecret communication systemvan der Pol boundary conditiondeep learning
collection DOAJ
language English
format Article
sources DOAJ
author Yuhan Chen
Hideki Sano
Masashi Wakaiki
Takaharu Yaguchi
spellingShingle Yuhan Chen
Hideki Sano
Masashi Wakaiki
Takaharu Yaguchi
Secret Communication Systems Using Chaotic Wave Equations with Neural Network Boundary Conditions
Entropy
chaotic synchronization
secret communication system
van der Pol boundary condition
deep learning
author_facet Yuhan Chen
Hideki Sano
Masashi Wakaiki
Takaharu Yaguchi
author_sort Yuhan Chen
title Secret Communication Systems Using Chaotic Wave Equations with Neural Network Boundary Conditions
title_short Secret Communication Systems Using Chaotic Wave Equations with Neural Network Boundary Conditions
title_full Secret Communication Systems Using Chaotic Wave Equations with Neural Network Boundary Conditions
title_fullStr Secret Communication Systems Using Chaotic Wave Equations with Neural Network Boundary Conditions
title_full_unstemmed Secret Communication Systems Using Chaotic Wave Equations with Neural Network Boundary Conditions
title_sort secret communication systems using chaotic wave equations with neural network boundary conditions
publisher MDPI AG
series Entropy
issn 1099-4300
publishDate 2021-07-01
description In a secret communication system using chaotic synchronization, the communication information is embedded in a signal that behaves as chaos and is sent to the receiver to retrieve the information. In a previous study, a chaotic synchronous system was developed by integrating the wave equation with the van der Pol boundary condition, of which the number of the parameters are only three, which is not enough for security. In this study, we replace the nonlinear boundary condition with an artificial neural network, thereby making the transmitted information difficult to leak. The neural network is divided into two parts; the first half is used as the left boundary condition of the wave equation and the second half is used as that on the right boundary, thus replacing the original nonlinear boundary condition. We also show the results for both monochrome and color images and evaluate the security performance. In particular, it is shown that the encrypted images are almost identical regardless of the input images. The learning performance of the neural network is also investigated. The calculated Lyapunov exponent shows that the learned neural network causes some chaotic vibration effect. The information in the original image is completely invisible when viewed through the image obtained after being concealed by the proposed system. Some security tests are also performed. The proposed method is designed in such a way that the transmitted images are encrypted into almost identical images of waves, thereby preventing the retrieval of information from the original image. The numerical results show that the encrypted images are certainly almost identical, which supports the security of the proposed method. Some security tests are also performed. The proposed method is designed in such a way that the transmitted images are encrypted into almost identical images of waves, thereby preventing the retrieval of information from the original image. The numerical results show that the encrypted images are certainly almost identical, which supports the security of the proposed method.
topic chaotic synchronization
secret communication system
van der Pol boundary condition
deep learning
url https://www.mdpi.com/1099-4300/23/7/904
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