机器学习在网络入侵检测中的应用

发布时间：2018-01-09 09:24

本文关键词：机器学习在网络入侵检测中的应用　出处：《数据采集与处理》2017年03期 　论文类型：期刊论文

【摘要】：随着网络的快速发展,网络安全成为计算机网络中一个重要的研究方向。网络攻击日益频繁,传统的安全防护产品存在漏洞,入侵检测作为信息安全的重要防护手段弥补了防火墙的不足,提供了有效的网络入侵检测措施,保护网络安全。然而传统的入侵检测系统存在许多问题,基于机器学习的入侵检测方法实现了对网络攻击的智能检测,提高了入侵检测的效率,降低了漏报率和误报率。本文首先简要介绍机器学习的部分算法,然后对机器学习算法在网络入侵检测中的应用进行深入的分析,比较各个算法在入侵检测应用中的优势和缺点,最后总结了机器学习的应用前景,为获得性能良好的网络入侵检测和防御系统奠定基础。
[Abstract]:With the rapid development of network, network security has become an important research direction in computer network. Intrusion detection as an important means of information security makes up for the lack of firewall, provides effective network intrusion detection measures to protect network security. However, there are many problems in traditional intrusion detection system. The intrusion detection method based on machine learning realizes the intelligent detection of network attack, improves the efficiency of intrusion detection, and reduces the false alarm rate and false alarm rate. Firstly, this paper briefly introduces some algorithms of machine learning. Then, the application of machine learning algorithm in network intrusion detection is deeply analyzed, and the advantages and disadvantages of each algorithm in intrusion detection application are compared. Finally, the application prospect of machine learning is summarized. It lays the foundation for obtaining the network intrusion detection and defense system with good performance.
【作者单位】：南京航空航天大学计算机科学与技术学院;
【基金】：江苏省自然科学基金(BK20160812)资助项目
【分类号】：TP181;TP393.08
【正文快照】： 引言当今社会网络成为人类交流的常用工具,因此对网络的安全要求很严格。计算机网络实现了各类金融、资源管理以及虚拟社区的应用,加快了社会信息化的进程。然而网络的对外开放性为网络攻击者提供了破坏的机会。网络入侵者通常尝试从网络中获得信息、修改信息或者造成系统瘫痪

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