@inproceedings{f4a67860f6134b7f92ff87a7d65a1ce5,
title = "A Novel Method of Network Security Situation Assessment Based on Evidential Network",
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.",
keywords = "Bayesian network, Evidence theory, Evidential network, Network security situation assessment",
author = "Xiang Li and Xinyang Deng and Wen Jiang",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 3rd International Conference on Machine Learning for Cyber Security, ML4CS 2020 ; Conference date: 08-10-2020 Through 10-10-2020",
year = "2020",
doi = "10.1007/978-3-030-62223-7_46",
language = "英语",
isbn = "9783030622220",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "530--539",
editor = "Xiaofeng Chen and Hongyang Yan and Qiben Yan and Xiangliang Zhang",
booktitle = "Machine Learning for Cyber Security - Third International Conference, ML4CS 2020, Proceedings",
}