Abstract
A method of misuse intrusion detection based on fuzzy Petri nets is proposed, and the learning ability similar to neural networks introduced into fuzzy Petri nets to adjust the parameters of attack knowledge model. Analysis indicated that, in the misuse detection system based on fuzzy Petri nets, the reasoning efficiency seemed to be improved, and the parameters such as threshold, weights and belief strength can be learned from the environment dynamically. Test results displayed that, under most circumstances, system detection rate was increased when the attack knowledge model was adjusted after learning.
| Original language | English |
|---|---|
| Pages (from-to) | 312-317 |
| Number of pages | 6 |
| Journal | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
| Volume | 27 |
| Issue number | 4 |
| Publication status | Published - Apr 2007 |
Keywords
- Fuzzy Petri nets
- Knowledge learning
- Knowledge representation
- Misuse detection