An Extraction Method of Situational Factors for Network Security Situational Awareness

Abstract

The proposal of network security situational awareness (NSSA) research means a great breakthrough and an innovation to the traditional network security technologies, and it has become a new hot research topic in network security field. First the current research status in this field is introduced, after a summarization of the former achievements, a layered NSSA realization model is constructed, in which extraction of the situational factors is pointed out as the most basic and important step in realizing NSSA. Situational factors(SF) are defined here, and the extraction method of SF is the main research topic in this paper. Combined with evolutionary strategy and neural network, an extraction method of situational factors is proposed. Evolutionary strategy is used to optimize the parameters of neural network, and then the evolutionary neural network model is established to extract the SFs, so the foundation of realizing network security situation is established. Finally, simulation experiments are done to validate that the evolutionary neural network model can effectively extract situational factors and the model has better generalization ability, which will accelerate the realization of NSSA greatly.