Approach for Network Fault Diagnosis Based on Bayesian Model

DOI

10.2991/mmsta-19.2019.15How to use a DOI?

Keywords

logon fault; fault diagnosis; Bayesian network; PPPoE

Abstract

User logon failure accounted for a relatively large proportion in network fault. Therefore, it is of great significance for service providers to diagnose and locate login failures quickly. In this paper, a login fault diagnosis method based on bayesian network is proposed. Firstly the login fault events are found by analyzing the data packets generated during PPPoE authentication, and the fault sample table is obtained based on expert knowledge and sample learning in order to further locate the root cause of login failure. And then, the fault Bayesian network model is established. Finally, the final fault reason is obtained through Bayesian reasoning process.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhixian Ran
AU  - Jianning Geng
PY  - 2019/12
DA  - 2019/12
TI  - Approach for Network Fault Diagnosis Based on Bayesian Model
BT  - Proceedings of the 2019 2nd International Conference on Mathematics, Modeling and Simulation Technologies and Applications (MMSTA 2019)
PB  - Atlantis Press
SP  - 67
EP  - 72
SN  - 2352-538X
UR  - https://doi.org/10.2991/mmsta-19.2019.15
DO  - 10.2991/mmsta-19.2019.15
ID  - Ran2019/12
ER  -