Name
Abstract | ||
|---|---|---|
The ICSA (Immune Clonal Selection Algorithm) based structure and parameter learning of wavelet network for intrusion detection is proposed. The hierarchical structure is used in the coding scheme, thus we can realize evolution of topologic structure and the parameter learning of the wavelet network meanwhile. The experimental results show that the method based on ICSA can get higher true rate of IDS (Intrusion Detection System) than advanced wavelet network and Immune wavelet network. At the same time, the method proposed can reduce the false rate of IDS and has faster convergence speed in experiment. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11550822_52 | ICANN (1) |
Keywords | Field | DocType |
false rate,higher true rate,intrusion detection system,hierarchical structure,immune wavelet network,wavelet network,parameter learning,topologic structure,immune clonal selection wavelet,intrusion detection,advanced wavelet network,immune clonal selection | Convergence (routing),Pattern recognition,Immune clonal selection algorithm,Computer science,Parameter learning,Coding (social sciences),Artificial intelligence,Artificial neural network,Clonal selection,Intrusion detection system,Machine learning,Wavelet | Conference |
Volume | ISSN | ISBN |
3696 | 0302-9743 | 3-540-28752-3 |
Citations | PageRank | References |
2 | 0.38 | 5 |
Authors | ||
2 | ||