Network Security Based on K-Means Clustering Algorithm in Data Mining Research

DOI

10.2991/snce-18.2018.130How to use a DOI?

Keywords

Intrusion detection systems; Data mining; Network security; Cluster algorithm

Abstract

Nowadays, the network has become the basis of everything. Meanwhile, network security has become one of today's most urgent social problem. Intrusion detection systems are sold through real-time monitoring of network traffic, and take corresponding measures when the suspicious transfer of suspicious problems of a new network security device. Intrusion detection system compared to traditional network security measures, have great advantages. Can solve the shortcomings of the original passive inspired, can also process it before the damage occurred, appearance of the intrusion detection system, has become an important part of network security.

Copyright

© 2018, 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  - Chunfen Bu
PY  - 2018/05
DA  - 2018/05
TI  - Network Security Based on K-Means Clustering Algorithm in Data Mining Research
BT  - Proceedings of the 8th International Conference on Social Network, Communication and Education (SNCE 2018)
PB  - Atlantis Press
SP  - 642
EP  - 645
SN  - 2352-538X
UR  - https://doi.org/10.2991/snce-18.2018.130
DO  - 10.2991/snce-18.2018.130
ID  - Bu2018/05
ER  -