Network Security Situation Generation and Evaluation Based on Heterogeneous Sensor Fusion

Network Security Situation Awareness (NSSA) is an emerging technique in the field of network security and it helps security analysts to be aware of the actual security situation of their networks. In this paper we presented a novel NSSA model based on multi-sensor data fusion. In our model, we acquired data from heterogeneous sensors and fused them employing Multi-Layer Feed-forward Neural Network in combination with efficient feature reduction approach which improved real-time nature of the fusion engine. Furthermore, we discussed the security situation awareness generation techniques and evaluation indicators detailedly. Our model is proved to be feasible and effective through a series of experiments.