Name
Abstract | ||
|---|---|---|
Due to the diversified threat elements of resources and information in computer network system, the research on a biological immune system is becoming one way for network security. Inspired by adaptive immune system principles of artificial immune system, we proposed an anomaly detection algorithm using a multiplex detector. In this algorithm, the multiplex detector is created by applying negative selection, positive selection and clonal selection to detect anomaly behaviors in network. Also the multiplex detector gives an effective method and dynamic detection. In this paper, the detectors are classified by K-detector, memory detector, B-detector, and T-detector for achieving multi level detection. We apply this algorithm in intrusion detection and, to be sure, it has a good performance. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11751595_17 | ICCSA (3) |
Keywords | Field | DocType |
adaptive immune system principle,multiplex detector,dynamic detection,memory detector,multi level detection,biological immune system,computer network system,artificial immune system,adaptive multiplex detector,network anomaly behavior detection,anomaly detection algorithm,intrusion detection,negative selection,network security,computer network,adaptive immunity,positive selection,immune system,anomaly detection | Anomaly detection,Artificial immune system,Adaptive system,Computer science,Multiplex,Network security,Computer network,Real-time computing,Artificial intelligence,Multiplexing,Intrusion detection system,Detector | Conference |
Volume | ISSN | ISBN |
3982 | 0302-9743 | 3-540-34075-0 |
Citations | PageRank | References |
1 | 0.41 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Misun Kim | 1 | 18 | 4.21 |
| Min-Soo Kim | 2 | 437 | 51.12 |
| Jae-Hyun Seo | 3 | 45 | 6.55 |