Watermark encryption and decryption algorithm based on chaotic neural network

A neural network and watermark encryption technology, applied in the field of information hiding, can solve the problems of not being able to know the content, and the scrambling rules are easy to be cracked

Pending Publication Date: 2020-02-07
CHINA UNIV OF PETROLEUM (EAST CHINA)
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  • Summary
  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

Without knowing the encryption method of the watermark, even if the image is intercepted by an attacker during transmission, its content cannot be known
[0004] Commonly used watermar

Method used

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  • Watermark encryption and decryption algorithm based on chaotic neural network
  • Watermark encryption and decryption algorithm based on chaotic neural network
  • Watermark encryption and decryption algorithm based on chaotic neural network

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Experimental program
Comparison scheme
Effect test

Embodiment

[0017] Step 1: Establish the LCNN neural network. figure 1 The schematic diagram of the LCNN neural network is shown, and the specific algorithm steps are described as follows:

[0018] 101. Initialize the input and output vectors of the neural network, and initialize the initial value x of the Logistic map 1 =0.32, iterate 220 times, generate chaotic sequence x k , put x k The last 200 sequences are used as the input vector and target vector of LCNN;

[0019] 102. First initialize the network weights W and α, and then use the obtained Logistic chaotic sequence x k Train the network, calculate the output t of the neural network, and then calculate the partial derivatives of the error E of the neural network to the network weights W and α respectively and r=1,...,m;

[0020] 103. Correct the weights of the neural network, namely: r=1,...,m;

[0021]

[0022]

[0023] 104. Calculate the error E of the neural network;

[0024] 105. If the exit condition of trainin...

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PUM

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Abstract

The invention relates to a watermark encryption and decryption algorithm based on a chaotic neural network, and belongs to the technical field of information hiding. The characteristic that Logistic chaotic mapping is extremely sensitive to an initial value and the good approximation effect of the Chebyshev neural network are utilized, and an LCNN network is established to encrypt the watermark, so that the security of the watermark is ensured. The network weights obtained by the LCNN neural network during each operation are different, and the secret keys for watermark encryption are also different, so that the encryption algorithm obtained based on the LCNN has a large secret key space, and the security is high. Besides, when the chaos initial value is slightly changed, the secret key isgreatly changed, the encrypted watermarks obtained after encryption are different from one another, the expected goal of one-time pad can be achieved, and the safety of the algorithm is improved.

Description

technical field [0001] The invention relates to a watermark encryption and decryption algorithm based on a chaotic neural network, belonging to the technical field of information hiding. Background technique [0002] With the popularization of electronic equipment and the rapid development of Internet technology, digital products can be easily copied and widely distributed in the network environment, and large-scale piracy is becoming increasingly rampant. Copyright owners hope to use digital watermarking to protect the legitimate rights and interests of their digital products. At the same time, various experts related to digital watermarking technology have also proposed algorithms based on various theories. Digital watermarking is to use a special algorithm to hide specific digital information (watermark) in various common digital products. Hidden information can not only be used to prove the ownership of works, but also can be used as evidence of illegal infringement. I...

Claims

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Application Information

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IPC IPC(8): G06T1/00G06N3/04
CPCG06T1/0092G06N3/043
Inventor 郑秋梅刘楠杨金路曹宝琴
Owner CHINA UNIV OF PETROLEUM (EAST CHINA)
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