CFA algorithm and BP neural network-based invasion detection method

Abstract

The invention discloses a CFA algorithm and BP neural network-based invasion detection method. The method comprises the following steps of: encoding operation parameters of a BP neural network as cell individuals in a CFA algorithm; taking an error function as an adaptive value function of the CFA algorithm; after carrying out iteration for multiple times, selecting the parameter with the optimum fitness as an initial weight value and threshold value of the BP neural network to carry out training; and finally applied the trained BP neural network into a classifier for invasion detection. According to the method, the characteristics of global search and high convergence speed of the CFA algorithm, the initial operation parameters of the BP neural network are optimized, and then the classifier which can be applied to network invasion detection is constructed. Through improving the disadvantages of local minimum and low convergence speed, caused by initial parameter randomization, of the BP neural network, the detection correctness of the BP neural network in the network invasion detection is improved.

Description

technical field [0001] The invention relates to the research field of network intrusion detection technology, in particular to an intrusion detection method based on a CFA (Cuttle Fish Algorithm) algorithm and a BP neural network. Background technique [0002] In view of the increasingly severe network security problems, passive defense technologies such as network firewalls and user authentication systems cannot completely solve network and information security problems. [0003] As an active defense technology, intrusion detection technology can continuously monitor computers and network behaviors in the network, not only monitor malicious behaviors from outside the network, but also detect unauthorized and malicious behaviors inside the network system. Intrusion detection technology collects network logs through certain technical means, listens to network communications, and analyzes these logs and data packets to detect whether there are malicious behaviors in the networ...

AI Technical Summary

Problems solved by technology

[0009] The present invention aims to improve the traditional BP neural network in network intrusion detection due to the shortcomings of easy to fall into local extremum and slow convergence speed, resulting in low detection accuracy and slow detection speed.

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