Proceedings of the 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)

Research on Enterprise Network Topology Anomaly Detection Techniques

Authors
Yanxia Li, Kaikun Dong, Li Guo
Corresponding Author
Yanxia Li
Available Online May 2018.
DOI
https://doi.org/10.2991/amcce-18.2018.29How to use a DOI?
Keywords
network topology graph, link redundancy preprocessing, topology anomaly detection.
Abstract
At present,the enterprise network management system presents the network connections between nodes in the form of network topology,so that the network topology can be visualized.However,the enterprise network itself is complex.With the increase of enterprise business,the number of network nodes increases,resulting in the complexity between node connections,therefore, this paper regards the changes of node connections in the network as exceptions and a network topology anomaly detection technique based on link redundancy preprocessing is proposed for enterprise intranet.The technique detects the abnormal situation in the network topology to locate the equipment failure and promptly discovers the violations of network access control behaviors and illegal intrusions to enhance network security.
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Proceedings
2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
Part of series
Advances in Engineering Research
Publication Date
May 2018
ISBN
978-94-6252-508-5
ISSN
2352-5401
DOI
https://doi.org/10.2991/amcce-18.2018.29How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yanxia Li
AU  - Kaikun Dong
AU  - Li Guo
PY  - 2018/05
DA  - 2018/05
TI  - Research on Enterprise Network Topology Anomaly Detection Techniques
BT  - 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/amcce-18.2018.29
DO  - https://doi.org/10.2991/amcce-18.2018.29
ID  - Li2018/05
ER  -