MACHINE LEARNING TECHNIQUES FOR INTERNET PROTOCOL ADDRESS TO DOMAIN NAME RESOLUTION SYSTEMS

摘要

An IP-to-Domain (IP2D) resolution system predicts which domain is most likely associated with an IP address. The resolution system generates unique source vote features (FSV) from (IP, domain, source) data. The FSV features are used to train a computer learning model that predicts which domain is most likely associated with an IP address. The domain predictions can then be used to more efficiently process events, more accurately calculate consumption scores, and more accurately detect associated company surges.