MLN-based network space security situation prediction method and system

A cyberspace and security posture technology, applied in the field of computer networks, can solve problems such as heavy workload, difficulty in obtaining, and inability to use background knowledge, and achieve the effect of improving accuracy and accurate object relationship

Inactive Publication Date: 2017-09-08
SOUTH CHINA NORMAL UNIVERSITY
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AI Technical Summary

Problems solved by technology

In existing techniques, logic-based approaches do not address this uncertainty well
In addition, the method based on probabilistic reasoning requires a lar

Method used

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  • MLN-based network space security situation prediction method and system
  • MLN-based network space security situation prediction method and system
  • MLN-based network space security situation prediction method and system

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Experimental program
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Embodiment Construction

[0047] refer to figure 1 , the present invention is a kind of network space security situation prediction method based on MLN, comprises the following steps:

[0048] Collect asset information data in a specific cyberspace;

[0049] Preprocess the collected asset information data, and build and train a cyberspace security situational awareness model;

[0050] Evaluate the current cyberspace security situation based on the cyberspace security posture awareness model and the actual data in the current cyberspace;

[0051] According to the assessment results of cyberspace security situation, the future cyberspace security situation is predicted, and the security situation prediction result is obtained.

[0052] refer to figure 2 , further as a preferred embodiment, further comprising the following steps:

[0053]Visually display the asset information data, security situation assessment results and security situation prediction results of the current cyberspace.

[0054] Fur...

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Abstract

The invention discloses an MLN-based network space security situation prediction method and system. The method comprises the steps that asset information data in a specific network space is collected; the collected asset information data is preprocessed, and a network space security situation perception model is constructed and trained; the current network space security situation is evaluated according to the network space security situation perception model and actual data in the current network space; and the future network space security situation is predicted according to a security situation evaluation result of the network space to obtain a security situation prediction result. According to the method, the relation between objects and object properties can be easily represented according to a first-order logic rule by applying a Markov logic network; and in addition, by introducing background knowledge, the object relation in the network space can be mastered more accurately, and then the evaluation accuracy rate is effectively increased. The method and system can be widely applied to the computer network field.

Description

technical field [0001] The invention relates to the technical field of computer networks, in particular to an MLN-based network space security situation prediction method and system. Background technique [0002] With the development of computer and network technology, the scale and complexity of the network continue to increase. In order to cope with increasingly complex network attack methods, it is necessary to fully consider the correlation and dynamics between various security nodes, so as to support more comprehensive security protection. However, some traditional security detection and early warning technologies, such as firewall technology and intrusion detection technology, are limited to a single aspect of protection and lack accurate monitoring of the overall network. In response to this problem, network security situational awareness judges the security status of the system from a macro and global perspective on the basis of integrating massive security data inf...

Claims

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Application Information

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IPC IPC(8): H04L12/24H04L29/06
CPCH04L41/145H04L41/147H04L63/20
Inventor 赵淦森任雪琦庄序填吴杰超廖智锐伍昱燊王欣明唐华汤庸马朝辉
Owner SOUTH CHINA NORMAL UNIVERSITY
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