Name
Abstract | ||
|---|---|---|
In the recent years one of the most focused topics in the field of network security and more specifically intrusion detection systems was to find a solution to reduce the overwhelming alerts generated by IDSs in the network. Inspired by human defence system and danger theory we propose a complementary subsystem for IDS which can be integrated into any existing IDS models to aggregate the alerts in order to reduce them, and subsequently reduce false alarms among the alerts. After evaluation using different datasets and attack scenarios, our model managed to aggregate the alerts by the average rate of 97.5 percent. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/CyberSec.2012.6246083 | CyberSec |
Keywords | Field | DocType |
danger theory,intrusion detection system,network security,alert fusion model,alarm systems,intrusion detection systems,computer network security,alert correlation,alert fusion,artificial immune system,artificial immune systems,ids models,false alarms,human defence system,computational modeling,immune system,correlation,intrusion detection | Data mining,Artificial immune system,Computer security,Network security,Engineering,Intrusion detection system,Alert correlation | Conference |
ISBN | Citations | PageRank |
978-1-4673-1425-1 | 1 | 0.35 |
References | Authors | |
12 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammad Mahboubian | 1 | 1 | 0.35 |
| Nur Izura Udzir | 2 | 164 | 28.44 |
| Shamala Subramaniam | 3 | 201 | 24.55 |
| Nor Asila Wati | 4 | 164 | 14.67 |