The Research and Simulation on Optimization Method for Diverse Network Intrusions
Feng Kang, Xiao Ping Zeng, Xiao Hui Jiang · Applied Mechanics and Materials · 2014
In current complex network environment, various kinds of attacks are mixed together forming the attack group. The diversity of the attack group leads to diverse attack signatures, which cannot be constrained by uniform conditions. Based on mixed attack signatures estimation model, the paper proposes a detection method for mixed and diverse attack groups. The paper classifies the different attacks in the mixed and diverse attack groups by use of attack constraint classification methods, builds invasion recognition particle tree, and detects mixed diverse attack groups in complex network environment according to error estimation. Experimental results show that the algorithm can effectively improve the accuracy of detection in complex network environment. atures;