摘要
网络使用量不断增加的同时,网络入侵形式也日趋多样,网络安全受到了严重威胁,因此可将改进蚁群算法优化的模糊支持向量机算法应用于网络入侵检测中。本文首先分析网络入侵检测的基本原理,研究网络入侵判别的数学模型;其次,分析模糊支持向量机的基本原理,构建模糊支持向量机的数学模型;然后,讨论改进蚁群算法的基本原理,设计改进蚁群算法的基本流程。最后,进行网络入侵检测的仿真分析。仿真结果表明,该算法能够提高网络入侵检测的准确性。
As the network usage keeps increasing, the forms of network intrusion are also varying; therefore, network security is facing severe threat. To solve the problem, Fuzzy Support Vector Machine （FSVM） optimized by the improved ant colony algorithm can be applied to network intrusion detection. Firstly, the essay analyzed the fundamental principles of network intrusion detection and studied on the mathematical model distinguishing network intrusion. Next, the essay analyzed the fundamental principles of FSVM and built the mathematical model of FSVM. Then, the essay discussed the fundamental principles of improving ant colony algorithm and designed the basic procedure to improve the ant colony algorithm. At last, the essay conducted simulated analysis on network intrusion detection. As indicated by the simulation results, this algorithm can improve the accuracy of network intrusion detection.
出处
《长春师范大学学报》
2017年第8期29-33,共5页
Journal of Changchun Normal University
关键词
改进蚁群算法
模糊支持向量机
网络入侵检测
improved ant colony algorithm
fuzzy support vector machine
network intrusion detection
