Self-iteration situation prediction method and system based on data center

Abstract

The invention discloses a self-iteration situation prediction method and system based on a data center station, and the method comprises the following steps: S1, data preprocessing; s2, situation assessment; s3, situation prediction; s4, carrying out self-iteration optimization; and S5, binding the situation presentation component. According to the method, the following problems in the prior art are solved: aiming at original security data with wide sources, complicated types and heterogeneous formats, a single fixed situation evaluation and prediction algorithm is difficult to accurately analyze a situation development trend in massive multivariate heterogeneous network security data; the efficiency and efficiency of network security situation assessment and prediction are low.

Description

technical field [0001] The invention relates to the technical field of network security situation assessment and prediction, in particular to a self-iterative situation prediction method and system based on a data center. Background technique [0002] With the development and progress of Internet theory and technology, security has become an extremely important factor in cyberspace research. Network security situation assessment and prediction can integrate security factors at different levels, and intuitively and comprehensively reflect network history, current and upcoming security conditions through numerical values, charts, etc., and provide a reference for enhancing network security. The assessment and prediction of network security situation is mainly based on the collection of network security data, from commonly used traffic analysis, to terminal and server service status monitoring, vulnerability distribution, virus killing, firewall policies and a series of securit...

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Problems solved by technology

[0006] In order to overcome the deficiencies of the prior art, the present invention provides a self-iterative situation prediction method and system based on the data center, which solves the following problems in the prior art: original security data with a wide range of sources, various types and heterogeneous formats , it is difficult for a single fixed situation assessment and prediction algorithm to accurately analyze the development trend of the situation in the massive multivariate heterogeneous network security data, and the effectiveness and efficiency of network security situation assessment and prediction are low

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