一种智能化网络入侵检测模型设计
Design of an Intelligent Network Intrusion Detection Model
DOI: 10.12677/CSA.2022.129216, PDF,    科研立项经费支持
作者: 姚宇杰, 张宗飞:台州职业技术学院信息技术工程学院,浙江 台州
关键词: 网络入侵检测量子进化算法k-Means新型入侵Network Intrusion Detection Quantum Evolutionary Algorithm k-Means New Types of Intrusion
摘要: 本文针对当前网络入侵检测系统在识别新型入侵行为时存在误警率和漏警率偏高的弊端,将新型优化技术和机器学习技术引入网络入侵检测,设计了一种具有智能性的网络入侵检测模型,实验模拟表明,本文设计的模型是有效的,并且对新型网络攻击行为的识别能力比较好,为开发新型的网络入侵检测系统提供了设计思路。
Abstract: Aiming at the disadvantages that current network intrusion detection systems have high false alarm rate and missing alarm rate when identifying new types of intrusion, new optimization technology and machine learning technology are applied to network intrusion detection, and an intelligent network intrusion detection model is designed in this paper. Simulation results show that the model designed in this paper is effective, and has better ability to identify new types of network attacks, provides a design idea for developing new network intrusion detection system.
文章引用:姚宇杰, 张宗飞. 一种智能化网络入侵检测模型设计[J]. 计算机科学与应用, 2022, 12(9): 2128-2136. https://doi.org/10.12677/CSA.2022.129216

参考文献

[1] 徐辉. 基于GA-SVM算法的网络入侵检测研究[J]. 长春工程学院学报(自然科学版), 2021, 22(1): 101-104.
[2] 徐伟, 冷静. 基于人工蜂群算法和XGBoost的网络入侵检测方法研究[J]. 计算机应用与软件, 2021, 38(3): 314-318+333.
[3] 顾兆军, 李冰, 刘涛. 基于ELM-KNN算法的网络入侵检测模型[J]. 计算机工程与设计, 2018, 39(8): 2412-2416+2421.
[4] Jia, H., Liu, J., Zhang, M., et al. (2021) Network Intrusion Detection Based on IE-DBN Model. Computer Communications, 178, 131-140. [Google Scholar] [CrossRef
[5] Ahmed, M., Seraj, R. and Islam, S.M.S. (2020) The K-Means Algorithm: A Comprehensive Survey and Performance Evaluation. Electronics, 9, 1295. [Google Scholar] [CrossRef
[6] Meng, Y. and Liu, X. (2018) Quantum In-spired Evolutionary Algorithm for Community Detection in Complex Networks. Physics Letters A, 382, 2305-2312. [Google Scholar] [CrossRef
[7] 吴迪, 郭嗣琮. 改进的Fisher Score特征选择方法及其应用[J]. 辽宁工程技术大学学报(自然科学版), 2019, 38(5): 472-479.
[8] KDD Cup 1999 Data. http://kdd.ics.uci.edu/databases/kddcup99/kddcup99.html