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首页> 外文期刊>American Journal of Signal Processing >Stego- Cryptography Using Chaotic Neural Network
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Stego- Cryptography Using Chaotic Neural Network

机译:使用混沌神经网络的密码学

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摘要

Information protection is now a crucial problem and good solution to this problem is cryptography and steganography. The content of message is kept secret in cryptography, where as in Steganography; a message is embedded in a cover image. In our proposed work a system is developed in which LSB Steganography and Cryptography using chaotic neural network is combined together to provide high security to the message during communication in an unsecure channel. In LSB Steganography taking advantage of the way the human eye perceives images, the technique involves of replacing the N least significant bits of each pixel of a container image with the data of a hidden message. Cryptography based on chaotic neural network is used because of its noise like behaviour which is quite significant for cryptanalyst to know about the hidden information as it is hard to predict. Thus the information is being kept secret. In this work we have considered the advantages of both the concepts and developed a model in which initially a message is embedded in a gray scale image using LSB steganography and then the stegoimage is encrypted using chaotic neural network to provide high security to the message. The whole process is implemented using MATLAB. The simulation results show the robustness of the technique.
机译:信息保护现在是一个关键问题,密码和隐写术是解决此问题的好方法。消息的内容在密码术中是秘密的,而在密码术中则是秘密的;在封面图像中嵌入一条消息。在我们提出的工作中,开发了一个系统,在该系统中,使用混沌神经网络的LSB隐写术和密码术结合在一起,可以在不安全的通道中进行通信时为消息提供高度的安全性。在利用人眼感知图像的方式进行的LSB隐写术中,该技术涉及用隐藏消息的数据替换容器图像的每个像素的N个最低有效位。之所以使用基于混沌神经网络的密码术,是因为它具有类似噪声的行为,这对于密码分析者了解难以预测的隐藏信息非常重要。因此,信息被保密。在这项工作中,我们考虑了这两种概念的优点,并开发了一种模型,该模型首先使用LSB隐写技术将消息嵌入灰度图像中,然后使用混沌神经网络对隐秘图像进行加密以为消息提供高安全性。整个过程使用MATLAB实现。仿真结果表明了该技术的鲁棒性。

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