Name
Title | ||
|---|---|---|
Intrusion detection system based on support vector machine active learning and data fusion |
Abstract | ||
|---|---|---|
As the viruses and Trojans become more and more rampant and ingenious, the Intrusion Detection technology is a new security technology which is considered to be the second safe gate after the fire wall. This thesis brings forth new ideas of Intrusion Detection System based on support vector machine active learning and data fusion which is completely different from traditional IDSs. This IDS model has an improved algorithm in its incident analysor part that presents some advantages of finding details of concrete attack detecting efficiency and being convenient to update because of the dependence of each classifiers. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-16493-4_28 | ISICA (1) |
Keywords | Field | DocType |
ids model,support vector machine,fire wall,concrete attack,data fusion,new security technology,intrusion detection system,improved algorithm,active learning,intrusion detection technology,new idea,intrusion detection | Data mining,Host-based intrusion detection system,Active learning,Computer science,Support vector machine,Sensor fusion,Anomaly-based intrusion detection system,Artificial intelligence,Intrusion detection system,Machine learning | Conference |
Volume | ISSN | ISBN |
6382 | 0302-9743 | 3-642-16492-7 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Man Zhao | 1 | 4 | 1.43 |
| Jing Zhai | 2 | 67 | 4.96 |
| Zhouqian He | 3 | 0 | 0.34 |