The Internet Control Message Protocol(ICMP)covert tunnel refers to a network attack that encapsulates malicious data in the data part of the ICMP protocol for transmission.Its concealment is stronger and it is not eas...The Internet Control Message Protocol(ICMP)covert tunnel refers to a network attack that encapsulates malicious data in the data part of the ICMP protocol for transmission.Its concealment is stronger and it is not easy to be discovered.Most detection methods are detecting the existence of channels instead of clarifying specific attack intentions.In this paper,we propose an ICMP covert tunnel attack intent detection framework ICMPTend,which includes five steps:data collection,feature dictionary construction,data preprocessing,model construction,and attack intent prediction.ICMPTend can detect a variety of attack intentions,such as shell attacks,sensitive directory access,communication protocol traffic theft,filling tunnel reserved words,and other common network attacks.We extract features from five types of attack intent found in ICMP channels.We build a multi-dimensional dictionary of malicious features,including shell attacks,sensitive directory access,communication protocol traffic theft,filling tunnel reserved words,and other common network attack keywords.For the high-dimensional and independent characteristics of ICMP traffic,we use a support vector machine(SVM)as a multi-class classifier.The experimental results show that the average accuracy of ICMPTend is 92%,training ICMPTend only takes 55 s,and the prediction time is only 2 s,which can effectively identify the attack intention of ICMP.展开更多
基金This research was supported by National Natural Science Foundation of China(Grant Nos.61972048,62072051).
文摘The Internet Control Message Protocol(ICMP)covert tunnel refers to a network attack that encapsulates malicious data in the data part of the ICMP protocol for transmission.Its concealment is stronger and it is not easy to be discovered.Most detection methods are detecting the existence of channels instead of clarifying specific attack intentions.In this paper,we propose an ICMP covert tunnel attack intent detection framework ICMPTend,which includes five steps:data collection,feature dictionary construction,data preprocessing,model construction,and attack intent prediction.ICMPTend can detect a variety of attack intentions,such as shell attacks,sensitive directory access,communication protocol traffic theft,filling tunnel reserved words,and other common network attacks.We extract features from five types of attack intent found in ICMP channels.We build a multi-dimensional dictionary of malicious features,including shell attacks,sensitive directory access,communication protocol traffic theft,filling tunnel reserved words,and other common network attack keywords.For the high-dimensional and independent characteristics of ICMP traffic,we use a support vector machine(SVM)as a multi-class classifier.The experimental results show that the average accuracy of ICMPTend is 92%,training ICMPTend only takes 55 s,and the prediction time is only 2 s,which can effectively identify the attack intention of ICMP.
文摘网络流分类与协议识别是网络管理的前提和必要条件,但是越来越多加密协议的出现,使得传统的流分类方法失效。针对加密协议的协议识别问题,提出了一种融合自动化逆向分析技术和网络消息聚类分析技术的新型分类方法(automatic reverse and message analysis,ARCA)。该方法通过自动化逆向分析技术获得网络协议的结构特征;再利用网络消息聚类分析技术,获得网络协议的交互过程;最后将网络协议的结构特征与交互过程用于加密协议流量的识别和分类检测。该方法不依赖于网络包的内容检测,能够解决协议加密带来的识别问题。通过对多个加密协议(如迅雷、BT、QQ和GTalk等)真实流量的实验,其准确率和召回率分别高于96.9%和93.1%,而且只需要检测流量中0.9%的字节内容即可。因此,ARCA方法能够对各类加密协议流量进行有效和快速的识别。
