Name
Abstract | ||
|---|---|---|
As a network defense technology, honeypot can take the initiative to respond to external attacks, with high reliability and convenient management. In the current complex industrial control network situation, honeypot as a defense tool can maximize the protection of data resources. In this paper, we design a honeynet-based intrusion detection system. It captures the actual traffic and uses support vector machine (SVM) algorithm to study the intrusion behavior based on the KDDCUP99 dataset. The experimental results show that the detection accuracy of intrusion behavior in the monitored network is up to 89%.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3331453.3360983 | Proceedings of the 3rd International Conference on Computer Science and Application Engineering |
Keywords | DocType | ISBN |
Honeynet, Industrial control network, Intrusion detection, SVM | Conference | 978-1-4503-6294-8 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiqiang Wang | 1 | 158 | 35.98 |
| Gefei Li | 2 | 0 | 0.68 |
| Yaping Chi | 3 | 2 | 2.35 |
| Jianyi Zhang | 4 | 2 | 2.01 |
| Qixu Liu | 5 | 0 | 0.68 |
| Tao Yang | 6 | 160 | 76.32 |
| Wei Zhou | 7 | 0 | 0.34 |