Security multicast communication method based on chaotic neural network

A neural network and secure multicast technology, applied in the field of information security, can solve problems such as application limitations of multicast communication security

Inactive Publication Date: 2014-07-30
HUAQIAO UNIVERSITY
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Problems solved by technology

However, the security of multicast

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  • Security multicast communication method based on chaotic neural network
  • Security multicast communication method based on chaotic neural network
  • Security multicast communication method based on chaotic neural network

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Embodiment Construction

[0017] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0018] A method for secure multicast communication based on chaotic neural network: the symmetric cryptographic algorithm based on chaotic neural network and the centralized group key management protocol LKH are combined and applied to multicast communication;

[0019] The chaotic neural network refers to the introduction of chaos into the neural network, so that the artificial neural network has rich nonlinear dynamic characteristics and high computational complexity, and many neural network models can achieve chaotic characteristics, such as improved discrete with chaotic characteristics. Hopfield neural network; the symmetric cryptographic algorithm of the chaotic neural network uses the output of the parallel LFSR as the input of the discrete Hopfield neural network with chaotic characteristics, and uses the nonlinear dynamic characteristics a...

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Abstract

The invention provides a security multicast communication method based on a chaotic neural network. The security multicast communication method is characterized by comprising the steps of combining a symmetric cryptographic algorithm based on the chaotic neural network and a centralized key management protocol LKH, and applying the combination to multicast communication, wherein according to the chaotic neural network, the chaos theory is introduced into a neural network to enable an artificial neural network to have abundant non-linear dynamic characteristics and high computational complexity, and chaotic characteristics can be achieved through multiple neural network models, such as a disperse Hopfield neural network having the chaotic characteristics after improvement; according to the symmetric cryptographic algorithm based on the chaotic neural network, output of concurrent LFSRs is taken as input of the disperse Hopfield neural network having the chaotic characteristics, and random selection is performed on pseudorandom sequences generated by the LFSRs by means of the non-linear dynamic characteristics and the chaotic characteristics of the neural network. Therefore, in a secret key of the symmetric algorithm (as specified in the specification), T0 is a connection weight singular matrix, H is a circulant matrix, and H' is a transposed matrix of H.

Description

technical field, [0001] The invention relates to the field of information security, in particular to a method for information security encryption. Background technique [0002] In recent years, chaotic neural network has a wide range of application prospects in network communication, combinatorial optimization and artificial intelligence, especially in the fields of secure communication. With the development of communication technology, multicast communication has made some progress, and a relatively complete communication model has been formed and widely used. Multicast communication can reduce the overhead of sending packets by the sender, save network bandwidth, increase the scalability of the group communication system, and improve the efficiency and capability of network application services. But the security of multicast communication makes its application subject to certain restrictions. [0003] As a key technology in multicast applications, secure multicast has hi...

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Application Information

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IPC IPC(8): H04L12/18H04L9/00
Inventor 李国刚钟超林王燕琼
Owner HUAQIAO UNIVERSITY
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