A Malicious Domain Detection Approach Based on Character and Resolution Features
Malicious domain is widely used in phishing and remote control trojan,and there still exist many limitations to detect malicious domain with high efficiency.In the light of the differences between malicious domains and normal domains in characters,generating algorithms,and resolving,a detection approach based on character and resolution features is proposed with the help of machine learning.With the approach applied to a large amount of malicious domains from CNCERT,the effectiveness of discrimination features has been proven.What's more,the detection approach improves the accuracy with cost reduced.As a conclusion,multi-dimension features and machine learning algorithms can be used in detection of malicious domains for network security.
Malicious domainRemote control trojanMachine learningFeature extraction
NETL
NSTL
万方数据
维普
