Using machine learning algorithm to ascertain network devices used with anonymous identifiers

A device, comprising:

• a processor;
• an endpoint detection and response (EDR) mechanism coupled to the processor, the EDR mechanism further comprises:
• a uniform resource locator (URL) parser configured to monitor a plurality of URLs by a cellular device over a cellular network, and extract a plurality of key-value pairs in a query string of a monitored URL;
• a URL verifier configured to:
• train an algorithm upon an extracted plurality of key-value pairs to generate a number of votes;
• rank the number of votes;
• and use a ranking threshold to verify the URL, wherein the plurality of key-value pairs of a verified URL is associated with a device identifier of the cellular device;
• and
• a key-value pair database that stores the plurality of key-value pairs of the verified URL and the associated device identifier.

A computer-implemented method, comprising:

• monitoring a plurality of uniform resource locators (URLs) by a cellular device over a cellular network;
• extracting a plurality of key-value pairs in a query string of a monitored URL, wherein the key-value pairs include one or more potential anonymous identifiers;
• training a Random Forest algorithm upon an extracted plurality of key-value pairs to verify the URL, wherein a verified URL associates the one or more potential anonymous identifiers as one or more actual anonymous identifiers to a device identifier;
• and
• storing the one or more actual anonymous identifiers and the device identifier.