Name
Abstract | ||
|---|---|---|
Under the application background of network security evaluation, a mechanism for situation element extraction based on Particle Swarm Optimization (PSO) and Fuzzy Neural Network (FNN) is proposed. Firstly, the input dataset of historical situation element is pre-fuzzed and then transformed into fuzzy logic rule which can be mapped between neural network layers. Meanwhile, PSO is used to achieve global optimization of BP network¿s weight value and threshold, and then an extraction model based on FNN and PSO (PSO-FNN) is built up. Experiment results prove that this extraction mechanism is effective in situation element extraction, and can be applied in the area of situation extraction for network security situation awareness. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ISKE.2008.4731134 | Intelligent System and Knowledge Engineering, 2008. ISKE 2008. 3rd International Conference |
Keywords | DocType | Volume |
backpropagation network weight value,extraction model,situation element extraction,particle swarm optimisation,global optimization,backpropagation,fuzzy logic,fuzzy logic rule,security situation element,network security evaluation,fuzzy neural nets,network security situation awareness,security of data,particle swarm optimization,fuzzy neural network,data mining,neural network,knowledge engineering,network security,situation awareness,security,artificial neural networks,optimization | Conference | 1 |
Issue | ISSN | ISBN |
null | null | 978-1-4244-2197-8 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wenzhong Guo | 1 | 611 | 76.01 |
| Guolong Chen | 2 | 52 | 11.10 |
| Zongming Lin | 3 | 0 | 0.34 |
| YuZhong Chen | 4 | 40 | 3.46 |
| Xiaotong Tong Fang | 5 | 0 | 0.34 |