Big data intrusion detection method based on naive Bayesian model and cloud security

Abstract

The invention discloses a big data intrusion detection method based on a naive Bayes model and cloud security, and the method comprises an intrusion detection method based on naive Bayes and cloud security. The intrusion detection method based on naive Bayes and cloud security mainly comprises five parts, namely a cloud data security module, a data processing module, an attribute weight determination module, an NB model and an intrusion monitoring system, wherein the data processing module is divided into two parts, namely an improved attribute selection algorithm and data discretization. The attribute weight determination module uses a fisher score value to measure a weighting coefficient, and the NB model is mainly hidden naive Bayes. According to the method, the naive Bayes model is optimized from the aspect of an attribute selection algorithm, the structure of the naive Bayesian model is improved by using weights, and the improved attribute selection algorithm and the weighted hidden naive Bayesian model are combined and applied to big data intrusion detection, so that the anti-intrusion detection effect of data is improved.

Description

technical field [0001] The invention relates to the technical field of big data detection methods, in particular to a big data intrusion detection method based on a naive Bayesian model and cloud security. Background technique [0002] Big data refers to a collection of data that cannot be captured, managed, and processed by conventional software tools within a certain period of time. It is a massive, high-growth rate that requires a new processing model to have stronger decision-making power, insight and discovery, and process optimization capabilities. With the advent of the era of big data, the types of data actually collected are becoming more and more diverse. [0003] However, the existing big data has the following problems in the process of collection and use: (1) There is a processing method of big data intrusion, and there are often irrelevant or redundant attributes in these data, which will affect the classification The result has some negative effects; (2) The ...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a large data intrusion detection method based on naive Bayesian model and cloud security, which solves the problem of processing large data intrusions. These data often have irrelevant or redundant attributes that are not related to research. It will have some negative impact on the classification results, this technical problem

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