Network security situation element acquisition mechanism based on BN-DBN

Abstract

In order to accelerate the convergence speed of a Dep Belief Network (DBN) and improve the acquisition precision of situation elements under a small sample condition, the invention provides a networksecurity situation element acquisition mechanism based on BN-DBN. On one hand, BN is added into the deep neural network to solve the gradient disappearance problem; on the other hand, an improved active Learning (IAL) algorithm is put forward through the deep neural network output layer, and the deep belief network is finely adjusted in the reverse direction through the algorithm, and the algorithm balances the sample types by actively selecting training samples in each iteration. Theoretical analysis and instance data simulation results show that the mechanism can solve the problems that theconvergence speed of the deep neural network is too slow or the gradient disappears, and samples are accurately classified. And the acquisition precision, the convergence rate and the algorithm complexity of the method are superior to those of other situation element acquisition mechanisms listed in the text.

Description

technical field [0001] The present invention relates to the field of machine learning technology for obtaining network security situation elements, in particular to a BN-DBN-based network security situation element acquisition mechanism Background technique [0002] In 2017, the number of global Internet users reached 3.49 billion, and network security issues have also emerged. There are still many risks of vulnerabilities in the basic network, data leakage is still serious, distributed reflection denial of service attacks are becoming more and more frequent, and network management is very passive. The issue of network security will be an issue that will be focused on in the future, so the academic community then shifts the research focus to Network Security Situation Awareness (NSSA) research. [0003] Recently, a semi-supervised learning method known as deep learning has been introduced into cybersecurity situational awareness. It can be considered as an extension of art...

AI Technical Summary

Problems solved by technology

However, the above studies have ignored the types of attack types in the classification process, and insufficient consideration has been given to attacks of small sample types

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