Intrusion Detection Based on Support Vector Machine Using Heuristic Genetic Algorithm
Tao Yerong, Sai Sui, Ke Xie, Zhe Liu · 2014
The parameters of Support Vector Machine (SVM) are optimized using heuristic genetic algorithm and then to detect the network intrusion behavior. The heuristic real-coded genetic algorithm is used to optimize the best parameters of SVM with Gauss kernel aimed at the classification accuracy of the model. The classification accuracy is largely improved. Experimental results show that this method has a broad application future.