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Parallel computing method capable of expanding precision Logistic chaotic sequence

A logistic equation and chaotic sequence technology, applied in the field of network security and data security, can solve problems such as the difficulty of parallel algorithm design tasks, the decline of dynamic characteristics of chaotic systems, and the difficulty of parallel program design.

Inactive Publication Date: 2010-09-15
HARBIN UNIV OF SCI & TECH
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Problems solved by technology

[0007] In 2003, Li et al. verified that Zhou's piecewise linear chaotic map is not safe enough from the perspective of strict chaos, and pointed out that under the condition of finite computing precision (Finite Computing Precision), the dynamic characteristics of the chaotic system will seriously decline
For example, using the mixed programming mode of MPI and OpenMP, this mixed programming mode will make the already very complex parallel algorithm design task more difficult, and requires the designer of the parallel program to be familiar with both programming models
This greatly increases the difficulty of parallel programming and raises the requirements for parallel programmers

Method used

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  • Parallel computing method capable of expanding precision Logistic chaotic sequence
  • Parallel computing method capable of expanding precision Logistic chaotic sequence
  • Parallel computing method capable of expanding precision Logistic chaotic sequence

Examples

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Effect test

example 1

[0085] Example 1: Implementation based on Message Passing Interface (MPI) and modular design.

[0086] The implementation steps based on message passing interface (MPI) and modular design are as follows: Figure 4 as shown in:

[0087] 1. The initial parameter x of the Logistic equation 0, the μ integer is quantized and stored in a one-dimensional array, set the required precision or specify the number of iterations; the parallel system obtains the information of the currently available slave processors, or specifies the number of slave processors in the parallel system. After MPI initialization using the MPI_Init() function, you can use the MPI_Comm_rank() function to obtain the number of the processor in the parallel system, ie p i . You can use the MPI_Comm_size() function to get the number of processors in the system.

[0088] 2. The first part of the parallel computing algorithm: x=x×(1-x), using the matrix to save the calculation intermediate results, modifying the l...

example 2

[0099] Example 2: Realize the encryption of the image.

[0100] The basic idea of ​​the algorithm based on the scalable precision chaotic random sequence encryption image is to divide the image into several parts (data slices), assuming that the length of the data slice is equal to the number of keys that can be generated by the generated chaotic random sequence. To implement byte encryption, the specific steps are as follows:

[0101] 1. The initial parameter x of the Logistic equation 0 , μ, the number of data slices, etc. can be used as part of the password input by the user. initial parameter x 0 , μ integer quantization saved into a one-dimensional array.

[0102] 2. The first part of parallel computing algorithm: x=x×(1-x);

[0103] 3. The second part of parallel computing algorithm: x=μ×x;

[0104] 4. If the accuracy reaches the number of generated keys, go to step 5; otherwise, go to step 2;

[0105] 5. The obtained chaotic sequence needs to be combined into a ke...

example 3

[0110] Example 3: Network encryption communication model.

[0111] The chaotic encryption algorithm is a symmetric encryption algorithm, that is, the same algorithm is used at the sending end and the receiving end for encryption / decryption.

[0112] The sender and receiver first determine the initial parameter x of the Logistic equation 0 , μ, and the precision or number of iterations, they can be used as part of the password entered by the user. The sending end can encrypt the information to be transmitted, and then transmit it to the other party through the network. After receiving the information, the receiving end performs decryption processing to restore the information.

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Abstract

The invention discloses a parallel computing method capable of expanding a precision Logistic chaotic sequence, comprising the following steps: (1) saving initial parameters x0 and mu integer quantization to an one-dimensional array, and arranging the precision required to be achieved or designating iterative times; (2) the first part of the parallel computational algorithm x=x*(1-x): utilizing amatrix to save and compute the intermediate result, modifying the length of a dynamic array and saving the computation result to the dynamic array; (3) the second part of the parallel computational algorithm x=mu*x: saving the computation result to the dynamic array; (4) and if the precision or the iterative times achieves the required value, acquiring the chaotic sequence in the dynamic array, thus the computation is finished, and otherwise, transferring to step (2). The method of the invention fully utilizes the properties of a chaotic system, provides the chaotic sequence of a more expansive mapping space, can be used in the fields of secret communication, information safety and so on, and is especially suitable for encryption, storage and network transmission of graph, image and multimedia and other information.

Description

technical field [0001] The invention belongs to the technical fields of data security and network security, and specifically uses parallel computing technology to realize a method for obtaining chaotic random sequence based on scalable precision. Background technique [0002] Since Edward Lorenz first proposed the concept of chaos in the study of atmospheric science in 1963, chaos has been applied in various fields to varying degrees. Chaotic motion refers to a highly unstable motion confined to a limited space in a deterministic system; chaos is generated by deterministic equations, and chaotic phenomena can be reproduced as long as the equation parameters and initial values ​​are determined. [0003] The biggest characteristic of the chaotic system is that the evolution of the system is very sensitive to the initial conditions, and the future behavior of the system is unpredictable in the long run. The founder of information theory, the American mathematician Shannon poin...

Claims

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Application Information

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IPC IPC(8): H04L9/00
Inventor 刘嘉辉宋大华陈德运乔佩利王卫兵李岩
Owner HARBIN UNIV OF SCI & TECH
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