摘要
群体智能在解决非确定性多项式(NP)问题或搜索空间过大的问题时有着显著优势。将鸽群优化(Pigeon Inspired Optimization,PIO)算法应用于入侵检测系统的特征选择中。提出基于Sigmoid的PIO(SPIO)和基于Cosine余弦相似度的PIO(CPIO)算法对入侵检测数据集KDDCUP99进行特征选择,并用机器学习的方法进行实验,建立模型并评估结果。
Swarm intelligence has significant advantages in solving nondeterministic polynomial(NP)problems or problems with too much search space.In this paper,pigeon inspired optimization(PIO)is applied to the feature selection of intrusion detection systems.The Sigmoid-based PIO(SPIO)and Cosine-based PIO(CPIO)algorithms were proposed to select the features of the intrusion detection data set KDDCUP99 and conduct experiments with the method of machine learning to build the model and evaluate the results.
作者
王康
霍朝宾
李青旭
Wang Kang;Huo Chaobin;Li Qingxu(National Computer System Engineering Research Institute of China,Beijing 100083,China)
出处
《电子技术应用》
2021年第2期11-15,共5页
Application of Electronic Technique
