Feature selection method based on fuzzy set feature entropy calculation

Abstract

The invention belongs to the field of security data analysis, and particularly relates to a feature selection method based on fuzzy set feature entropy calculation. The method mainly comprises the steps of calculating an ideal vector matrix, calculating a similarity matrix, calculating entropy of features, calculating a scaling factor SFi, and calculating a scaling factor SFi. According to the method, the distance between the ideal vectors in each category is calculated by using the scaling factors of the features and the entropy between the specific categories, feature selection can be optimized, and the calculation complexity is reduced. According to the method, a fuzzy set information entropy calculation method FIEE is adopted to solve the problem that in a traditional information gainand information gain ratio calculation method, calculation cannot be conducted due to the fact that the feature value space is huge. According to the method, the calculation complexity can be greatlyreduced.

Description

technical field [0001] The invention belongs to the field of security data analysis, and in particular relates to a feature selection method based on fuzzy set feature entropy value calculation. Background technique [0002] In recent years, with the continuous increase in the number of Internet users, network security has also become a topic of great concern. Intrusion detection system (IDS) is an effective method for fighting malicious behaviors of network attackers, and the decisive factor for determining the performance of IDS is whether there is a corresponding efficient and accurate classification model, and how to target security Analyzing the characteristics of the data set and building a suitable classification model has also become a research hotspot in this field. A large number of redundant features is the biggest feature of security analysis data. In the process of data analysis, irrelevant features will confuse the classifier, which not only increases the comp...

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Problems solved by technology

[0006] The purpose of the present invention is to solve the problem of large number of features and high calculation complexity in the field of network security analysis. In order to solve the problem of evaluating the importance of features in network security analysis data, although the classical entropy value theory can directly evaluate the effect of individual features on classification results Contribution, but the traditional entropy calculation method is related to the number of values ​​of the feature, and can only deal with discrete features

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