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Video chaos encryption method based on quantum cellular neural network

A neural network and chaotic encryption technology, applied in biological neural network models, secure communication through chaotic signals, neural architecture, etc., can solve the problems of corrupted video encoding format, poor real-time video transmission, slow encryption speed, etc., and achieve huge key Space, huge anti-attack performance, and high encryption efficiency

Active Publication Date: 2020-04-21
CHANGCHUN UNIV OF SCI & TECH
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  • Summary
  • Abstract
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Problems solved by technology

[0007] The present invention provides a video chaotic encryption method based on quantum cellular neural network to solve the problems of slow encryption speed, damaged video encoding format, poor real-time video transmission and poor security in existing encryption methods.

Method used

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  • Video chaos encryption method based on quantum cellular neural network
  • Video chaos encryption method based on quantum cellular neural network
  • Video chaos encryption method based on quantum cellular neural network

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specific Embodiment approach 1

[0023] Specific implementation mode one, combination Figure 1 to Figure 6 Explain this embodiment, a video chaotic encryption method based on quantum cellular neural network, figure 1 This is a schematic diagram of the key generation of the encryption method in this embodiment, and the key generation process is described in steps A1 to F1 as follows.

[0024] According to the H.264 video coding standard, the encryption process of the video encryption method of the present invention is as follows: figure 2 As shown, the specific implementation details of the key generation module are as follows figure 1 , Which is realized by step A1 to step F1.

[0025] A1. Take a two-cell quantum cellular neural network hyperchaotic system, and its state equation is:

[0026]

[0027] Where x 1 ,x 2 ,x 3 ,x 4 Is the state variable; ω 1 , Ω 3 It is proportional to the energy between quantum dots in each cell, ω 2 , Ω 4 Represents the weighted effect of the difference in polarizability of adjacent c...

specific Embodiment approach 2

[0074] Specific implementation mode two, combination figure 2 , Figure 5 with Image 6 To describe this embodiment, this embodiment is another example of the first embodiment: the key generation process and the encryption process in the embodiment are the same as those in the first embodiment.

[0075] Combine Figure 5 To explain this embodiment, select the "person" video data in the cif format with a size of 352*288. This embodiment runs in the JM8.6 basic mode of H.264, the video length is 30 frames, and the I frame interval is 8, where extract Figure 5 The original image in the 20th frame.

[0076] Image 6 This is the ciphertext image of the 20th frame image of the "person" video data in this embodiment after being encrypted by the video encryption method of the present invention.

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Abstract

The invention discloses a quantum cellular neural network based video chaotic encryption method, relates to the technical field of video encryption and solves the problems such as relatively slow encryption speed, destruction of the coding format of a video, poor video transmission real-time performance and poor safety of the existing encryption method. The quantum cellular neural network based video chaotic encryption method comprises the steps of performing iteration solution on two cellular quantum cellular neural network hyper-chaotic systems to generate a matrix A; performing matrix transformation on the A to generate a chaotic sequence K and an index sequence Index; dividing the chaotic sequence K to generate an initial key pool; regarding elements in the index sequence Index as initial values of Logistic chaotic mapping, respectively and iterating to generate two chaotic index sequences and transforming to obtain two integer sequences; regarding the integer sequences as indexes respectively and carrying the indexes into the initial key pool to calculate and generate a Boolean key KeyB; dividing the Boole key KeyB into keyb1 and keyb2; encrypting the exponential-Golomb encoding information bit of H.264 by using the keyb1; and regarding the keyb2 as a key to encrypt the encoding data of the H.264 to realize video chaotic encryption of the quantum cellular neural network.

Description

Technical field [0001] The invention relates to the technical field of video encryption, in particular to a video encryption method based on a quantum cellular neural network hyperchaotic system. Background technique [0002] With the development of social networks and the popularization of smartphones with camera functions, people can easily obtain video information through video websites and social software, making people’s demand for video security surge. However, most of the video storage and transmission use plain text and video data. It is easy to be stolen. Once a video involving personal privacy is leaked, it will have an incalculable impact. The clear text transmission of video data also involves the copyright issue of the video content. Therefore, the issue of video security has received more and more attention and has become one of the research topics to be solved urgently. [0003] In recent years, researchers have proposed many different types of video encryption sc...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L9/00H04N21/4408H04N19/70H04N19/46G06N3/04
CPCG06N3/0418H04L9/001H04N19/46H04N19/70H04N21/4408
Inventor 李锦青底晓强从立钢闫飞祁晖赵建平任维武王欢
Owner CHANGCHUN UNIV OF SCI & TECH
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