Feature Selection Algorithm Based on Quantum Evolution in Network Intrusion Detection

1Haogui CHEN, 2Huifeng LONG

1Modern Education Technology Center, Hunan City University, HuNan, Yiyang 413000, CHINA

2College of Urban Management, Hunan City University, HuNan, Yiyang 413000, CHINA

Abstract: As there are ubiquity problems about slowing in detecting limited by optimizing performances in current network intrusion detection, this paper proposed the feature selection algorithm based on quantum evolution. Firstly, in order to reach optimizing performance, this algorithm promoted quantum evolution algorithm for objective and formed the evaluation function of feature subset, then designed network intrusion detection feature selection algorithm according to the process of quantum evolution algorithm, finally made a comparing experiment of the algorithm in this text with feature selection algorithm based on genetic algorithm(FS-IGA), the results showed: the global optimizing ability of quantum evolution’s feature selection algorithm made universal search to feature space, took out unrelated and useless features, increased detection effect.

Keywords: Intrusion Detection; Optimized Feature; Coding, Detection Rate