Fortinet, Inc.
Determining a risk probability of a URL using machine learning of URL segments

Abstract:

Systems, methods, and apparatuses enable a machine learning model to determine a risk probability of a URL. A query configurator receives a URL in a query and normalizes the URL. The normalized URL is segmented into a plurality of segments. The plurality of segments is serially provided to the machine learning model trained to provide an indication of risk associated with the URL. The indication of risk associated with the URL can be a probability value based on one or more risk probabilities determined for segment-segment transitions of the URL. A security service compares the probability value of the URL to a threshold value and performs a security action based on a result of comparing the probability value to the threshold value.