Deep learning for malicious URL classification (URLC) with the innocent until proven guilty (IUPG) learning framework
Abstract:
Techniques for providing deep learning for malicious URL classification (URLC) using the innocent until proven guilty (IUPG) learning framework are disclosed. In some embodiments, a system, process, and/or computer program product includes storing a set comprising one or more innocent until proven guilty (IUPG) models for static analysis of a sample; performing a static analysis of one or more URLs associated with the sample, wherein performing the static analysis includes using at least one stored IUPG model; and determining that the sample is malicious based at least in part on the static analysis of the one or more URLs associated with the sample, and in response to determining that the sample is malicious, performing an action based on a security policy.
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