Proceedings of the 8th International Conference on Social Network, Communication and Education (SNCE 2018)

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

Authors
Chunfen Bu
Corresponding Author
Chunfen Bu
Available Online May 2018.
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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Volume Title
Proceedings of the 8th International Conference on Social Network, Communication and Education (SNCE 2018)
Series
Advances in Computer Science Research
Publication Date
May 2018
ISBN
978-94-6252-505-4
ISSN
2352-538X
DOI
10.2991/snce-18.2018.130How to use a DOI?
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/).

Cite this article

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  -