The invention relates to the field of
machine learning algorithms and
covert channel detection, and aims to provide an ICMP
covert channel detection method based on a
random forest machine learning
algorithm. According to the technology, firstly, data packets of inter-
network communication are captured, basic information (a source
IP address, a destination
IP address and the like) related to the data packets in the data packets is extracted, the information is classified, an ICMP
message flow is formed according to the information, and characteristics are extracted from the corresponding ICMPmessage flow by utilizing a specific rule of the method; the method comprises the following steps: obtaining the characteristics of the ICMP message communication data flow between a source IP addressand a destination
IP address, training the characteristics by using a
random forest-based
machine learning method, and finally obtaining a classifier for detecting an ICMP
covert channel. When the method is used for ICMP covert channel detection, the calculation cost and the
time cost are low, the generated ICMP flow features are strong in pertinence and high in reliability, and the ICMP covert channel can be effectively detected.