MALICIOUS WEBSITE DETECTION USING INTERMEDIATE REPRESENTATIONS
MALICIOUS WEBSITE DETECTION USING INTERMEDIATE REPRESENTATIONS
Websites are classified based on intermediate representations of the associated source code using a machine learning model applied to a set of intermediate representations from websites having predetermined classifications. The use of intermediate representations can provide a machine independent classifier that does not required use of lists of websites known to be malicious. The intermediate representation-based classifier can be combined with URL and HTML based classifiers, including classifiers that incorporate URLs that are both statically and dynamically linked.