Applying genetic algorithm for classifying anomalous TCP/IP packets

We present a method for applying genetic algorithms in order to feature selection of TCP/IP packets. The proposed scheme creates an appropriate polynomial equation with weighted coefficients as an objective function for fitness evaluation. The coefficients of the proposed polynomial equation represent the anomaly score of each field. After the evolutionary process is complete, the selected features are used for preprocessing TCP/IP packets before applying TCP/IP packets directly into anomalous detection. To verify the efficiency of the proposed method, various machine learning algorithms were tested with and without a genetic algorithm selecting the optimal fields.