PSO-FNN-based extraction of security situation element

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.