基于机器和深度学习的入侵检测综述

随着互联网的普及，网络空间与陆地、海洋、天空、太空齐名，已成为国家第五大主权领域空间。网络安全的重要性日益凸显，入侵检测作为有效的攻击检测手段，正被广泛研究。首先从入侵检测的概念和分类出发，详细阐述了入侵检测的前两个环节：数据采集及处理和信号分类。然后，围绕机器学习和深度学习两个研究热点对信号分类的技术进行了归纳和总结。最后，对于当前研究的问题提出了思考和总结，并对未来方向进行了分析和展望。

Overview of Intrusion Detection Based on Machine and Deep learning

With the popularity of the Internet, cyberspace is on par with land, sea, sky and space, and has become the fifth largest sovereign domain space of the country. The importance of network security has become increasingly prominent. As an effective means of attack detection, intrusion detection is being widely studied. From the concept and classification of intrusion detection, the first two aspects of intrusion detection are elaborated: data acquisition and pre-processing, signal classification. Then, techniques for signal analysis are summarized around the two research hotspots of machine learning and deep learning. Finally,reflections and summaries on current research issues are presented, and future directions are analysed and foreseen.