基于人工智能的网络入侵检测与响应机制  

Network Intrusion Detection and Response Mechanism Based on Artificial Intelligence

作　　者：罗卓君[1] LUO Zhuojun(Hunan Mass Media Vocational&Technical College,Changsha 410100,China)

机构地区：[1]湖南大众传媒职业技术学院,湖南长沙410100

出　　处：《通信电源技术》2024年第9期196-198,共3页Telecom Power Technology

摘　　要：针对当前网络入侵检测领域的挑战,提出了一种基于改进型朴素贝叶斯算法的网络入侵检测方法。首先,深入研究了网络入侵检测与响应的整体框架;其次,提出了改进型朴素贝叶斯算法,引入了特征加权和条件概率平滑策略,以提高对入侵行为检测的准确性;最后,利用CIC-IDS2017数据集进行实验验证,并与传统朴素贝叶斯方法进行比较。实验结果表明,改进型朴素贝叶斯方法的多个指标均优于传统方法,充分证明了其在网络入侵检测中的有效性。Aiming at the challenges in the field of network intrusion detection,a network intrusion detection method based on improved naive bayes algorithm is proposed.Firstly,the overall framework of network intrusion detection and response is deeply studied.Secondly,an improved naive bayes algorithm is proposed,which introduces feature weighting and conditional probability smoothing strategy to improve the accuracy of intrusion detection.Finally,the CIC-IDS2017 data set is used for experimental verification and compared with the traditional naive bayesian method.The experimental results show that the improved naive bayes method is superior to the traditional method in many indexes,which fully proves its effectiveness in network intrusion detection.

关 键 词：人工智能 入侵检测 朴素贝叶斯算法 网络安全 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TN929.5[自动化与计算机技术—控制科学与工程]