Title :
Quantification of Network Security Situational Awareness Based on Evolutionary Neural Network
Author :
Liang, Ying ; Wang, Hui-Qiang ; Lai, Ji-Bao
Author_Institution :
Harbin Eng. Univ., Harbin
Abstract :
The proposal of network security situational awareness (NSSA) research means a breakthrough and an innovation to the traditional network security technologies, and it has become a new hot research topic in network security field. Combined with evolutionary strategy and neural network, a quantitative method of network security situational awareness is proposed in this paper. Evolutionary strategy is used to optimize the parameters of neural network, and then the evolutionary neural network model is established to extract the network security situational factors, so the quantification of network security situation is achieved. Finally simulated experiment is done to validate that the evolutionary neural network model can extract situational factors and the model has better generalization ability, which supports the network security technical technologies greatly.
Keywords :
evolutionary computation; neural nets; optimisation; telecommunication security; evolutionary strategy; network security; neural network; optimization; situational awareness; situational factors; Computer science; Computer security; Cybernetics; Electronic mail; Fault detection; Information security; Machine learning; Neural networks; Proposals; Technological innovation; Evolutionary strategy; Network security; Neural network; Situational awareness; Situational factor;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370711