Data input method and device for network security index calculation

Abstract

The invention discloses a data input method for network security index calculation, and the method comprises the steps: carrying out the data partitioning according to obtained network security data,and obtaining first network security data; performing data processing on the first network security data to obtain second network security data; constructing an equal-length multi-dimensional vector by utilizing the second network security data; and forming a data set by the equal-length multi-dimensional vectors, and inputting data. The invention further discloses a data input device for calculating the network security index. According to the data input method and device for network security index calculation provided by the embodiment of the invention, the accuracy of a network security index calculation model can be improved.

Description

technical field [0001] The invention relates to the field of network and information security, in particular to a data input method and device for network security index calculation. Background technique [0002] The existing network security index calculation is generally based on the experience of network security experts to set the network security index system and the weight values ​​of the corresponding indicators, and then calculate the network security index. Such a calculation method relies too much on network security experts and is highly subjective. , cannot be learned and adjusted according to the actual situation, and the accuracy is not high. [0003] Another study is to use the feedforward neural network for the calculation of the network security index, and to train and adjust the weight of each indicator in the network security index system through the feedforward neural network. However, due to the limited depth of the feedforward social network, the amount...

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Problems solved by technology

[0002] The existing network security index calculation is generally based on the experience of network security experts to set the network security index system and the weight values ​​of the corresponding indicators, and then calculate the network security index. Such a calculation method relies too much on network security experts and is highly subjective. , can not be adjusted according to the actual situation, the accuracy is not high

[0003] Another study is to use the feedforward neural network for the calculation of the network security index, and to train and adjust the weight of each indicator in the network security index system through the feedforward neural network. However, due to the limited depth of the feedforward social network, the amount of calculation is large, and it is difficult to converge. , the accuracy of this method is not high when it is applied to the calculation of network security index of large-scale network

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