Network security situation awareness model and method based on improved BP neural network

Abstract

The invention discloses a network security situation awareness model and method based on an improved BP neural network. The model comprises a data preprocessing module, a situation calculation module,a parameter optimization module and a situation prediction module, and the method comprises the following steps: collecting data sets from different sources, and extracting principal component information for situation awareness to obtain asset attack threat data and system state data; calculating a risk value according to the asset attack threat data of the network equipment, and evaluating thesecurity situation of the whole network; and improving a BP neural network by using the L-M optimization algorithm, optimizing weight parameters of BP neural network, obtaining optimal weight parameters after multiple iterations, and substituting the optimal weight parameters into BP neural network to perform network security situation prediction.. The problem that the BP neural network is caughtin a local optimal solution is effectively avoided, the convergence rate and generalization ability of the BP neural network are improved to a great extent, and the BP neural network can obtain a goodeffect in situation prediction.

Description

Technical field: [0001] The invention relates to the field of computer network security, in particular to a network security situation awareness model and method based on an improved BP neural network. Background technique: [0002] With the rapid development of network technology, network attack incidents are also increasing year by year, and network security issues have become the focus of people's current attention. Predicting the network security situation can grasp the security status of the network before a network attack event occurs, so as to take corresponding protective measures to avoid unnecessary attacks and losses; [0003] At present, most of the research on network security situation awareness is the research on network threat quantification and security situation assessment. A few prediction models can only be applied to specific standard systems and application scenarios, and it is difficult to achieve very accurate and efficient prediction results. BP (Ba...

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Problems solved by technology

[0004] However, the BP neural network tends to fall into a local optimal state during the training process, making its learning speed slower and the convergence time longer, which limits its ability in situation prediction

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