The detection method of Network attacks in Campus Network

DOI

10.2991/asei-15.2015.88How to use a DOI?

Keywords

attack detection; Hidden Markov Model; entropy

Abstract

In the process of the detection method of network attacks in campus network, with current algorithm, there are defects such as high demand for data and low detection rate for model. Therefore, a network attack detection method based on improved Hidden Markov Model algorithm is proposed. Structure and characteristics of the campus network is firstly analyzed. Based on the hidden Markov model, the learning of the normal school network behavior sample is then established. On this basis, the information entropy of information theory is introduced to measure the degree of dispersion of source IP addresses. According to the change of the initial stage of Hurst index and entropy threshold is adaptive set to detect the attacks so as to complete attack behavior detection. The experimental results show that the detection method based on the improved hidden Markov model has high accuracy and robustness

Copyright

© 2015, 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  - Hongxu Wang
PY  - 2015/05
DA  - 2015/05
TI  - The detection method of Network attacks in Campus Network
BT  - Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
PB  - Atlantis Press
SP  - 436
EP  - 439
SN  - 2352-5401
UR  - https://doi.org/10.2991/asei-15.2015.88
DO  - 10.2991/asei-15.2015.88
ID  - Wang2015/05
ER  -