The invention relates to the technical field of APP detection
data processing, and discloses a deep detection method for an effective
core domain name of a harmful APP, which comprises the following steps: firstly, constructing a sandbox environment, constructing a network
proxy service in the sandbox environment, comprehensively acquiring communication flow information of the APP, and accessing
the Internet after connecting a gateway in a TUN mode in a sandbox test environment; performing internal operation of the automatic operation APP, wherein the internal operation comprises login, registration and refreshing operation; and carrying out operation analysis, and limiting network bandwidth,
delay and
packet loss rate parameters. Carrying out
core domain name analysis, wherein the
core domain name analysis specifically comprises carrying out deep detection on a traffic log; and training the model according to the traffic log, analyzing the traffic log through the model, performing model analysis by using a
machine learning
decision tree algorithm or a
data analysis method, and confirming and analyzing effective condition data of the APP. According to the method, an APP communication log analysis model is constructed based on a
decision tree algorithm, and suspected core domain names are identified based on dimensions such as communication behaviors and communication contents.