Name
Title | ||
|---|---|---|
Unknown Attack Detection by Multistage One-Class SVM Focusing on Communication Interval. |
Abstract | ||
|---|---|---|
Cyber attacks have been more sophisticated. Existing countermeasures, e. g, Intrusion Detection System (IDS), cannot work well for detecting their existence. Although anomaly-based IDS is considered to be promising approach to detect unknown attacks, it still lacks the ability to distinguish sophisticated attacks from trivial known ones. Therefore, we applied multistage one-class Support Vector Machine (OC-SVM) to detect such serious attacks. At the first stage, two training data are retrieved from traffic archive. The one is used for training OC-SVM and then, attacks are obtained from the another. Also testing data from real network are examined by the same OC-SVM and attacks are extracted. The attacks from the traffic archive are used for training OC-SVM at the second stage and those from real network are analyzed. Finally, we can obtain unknown attacks which are not stored in archive. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-12643-2_40 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
Intrusion Detection System,anomaly detection,network security | Training set,Data mining,Anomaly detection,Robust random early detection,Computer science,Network security,Support vector machine,Artificial intelligence,Test data,Intrusion detection system,Machine learning | Conference |
Volume | ISSN | Citations |
8836 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shohei Araki | 1 | 1 | 0.35 |
| Yukiko Yamaguchi | 2 | 6 | 1.37 |
| Hajime Shimada | 3 | 1 | 1.36 |
| H. Takakura | 4 | 13 | 2.74 |