网络入侵检测技术的研究进展与展望  

Research Progress and Prospect of Network Intrusion Detection Technology

作　　者：魏鹏飞 WEI Peng-fei(Beijing Technology and Business University,Beijing 100048)

机构地区：[1]北京工商大学,北京100048

出　　处：《数字技术与应用》2020年第5期180-180,182,共2页Digital Technology & Application

摘　　要：网络入侵检测是一种互联网安全防御技术,经过多年的应用和实践,已经引入很多更加先进的技术,比如深度包过滤技术、深度学习技术、固件技术,不仅可以提高网络入侵检测的可靠性和准确度,还可以提高网络入侵检测的速度。当前,互联网接入设备不断增多,不仅包括服务器、交换机、路由器等有线设备,还包括智能手机、平板电脑等无线设备,因此网络组成架构和接入设备更加复杂,更加容易产生系统漏洞,受到网络中潜在的病毒或木马攻击,因此未来还需要引入网格算法以及其它人工智能技术,进一步提高网络入侵检测的成效,保护网络安全运行。Network intrusion detection is an Internet security defense technology.After years of application and practice,many more advanced technologies have been introduced,such as deep packet filtering technology,deep learning technology,and firmware technology,which can not only improve the reliability and reliability of network intrusion detection.Accuracy can also improve the speed of network intrusion detection.However,with the increase in Internet access devices,not only wired devices such as servers,switches,routers,but also wireless devices such as smartphones and tablets,the network composition architecture and access devices are more complex and more vulnerable to system vulnerabilities.Being attacked by potential viruses or Trojan horses in the network,grid algorithms and other artificial intelligence technologies will need to be introduced in the future to further improve the effectiveness of network intrusion detection and protect the safe operation of the network.

关 键 词：网络入侵检测 深度包过滤 深度学习 人工智能 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]