A Novel Method of Network Security Situation Assessment Based on Evidential Network

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

Network security situation awareness is a new type of network security technology. It evaluates the network security situation in real time from a macro perspective. Also it can predict the trend of the development of the network security situation, providing a basis for the decision analysis of administrators. It is difficult to obtain complete and accurate information in network security situation assessment by using evidential network. So we introduce an evidential network based on Bayesian network to solve that problem. Firstly, transform the parent node information and inference rules into plausibility function so as to be compatible with imperfect and inaccurate information. Secondly, we use the full probability formula of Bayesian network as reference to make similar reasoning under the framework of evidence theory. Then transform the inference result to BPA form by using the minimum specificity algorithm, and obtain the final result by projection. Finally, an example of network security situation assessment is given to illustrate the rationality and effectiveness of the method.

Original languageEnglish
Title of host publicationMachine Learning for Cyber Security - Third International Conference, ML4CS 2020, Proceedings
EditorsXiaofeng Chen, Hongyang Yan, Qiben Yan, Xiangliang Zhang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages530-539
Number of pages10
ISBN (Print)9783030622220
DOIs
StatePublished - 2020
Event3rd International Conference on Machine Learning for Cyber Security, ML4CS 2020 - Guangzhou, China
Duration: 8 Oct 202010 Oct 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12486 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Machine Learning for Cyber Security, ML4CS 2020
Country/TerritoryChina
CityGuangzhou
Period8/10/2010/10/20

Keywords

  • Bayesian network
  • Evidence theory
  • Evidential network
  • Network security situation assessment

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