Intercepting worthless requests at the network edge using machine learning

A non-transitory computer readable storage medium impressed with computer program instructions to screen malicious and probing requests to establish an authorized session, collectively worthless requests, directed to a protected application, using an identity gateway (IG) positioned as a network edge component on a network, the screening being invoked before starting an authentication or authorization journey or other resource consuming interaction with the protected application, the instructions, when executed on a processor, implement a method comprising:

• provisioning a trained ML classifier at an edge server accessible by the IG, wherein the trained ML classifier accepts a variable length array of features available when a request to establish an authorized session is received and outputs a score that predicts whether the request is a worthless request;
• receiving the request, from a client, to establish an authorized session at the IG,
• assigning the array of features to the request,
• processing the features using the trained ML classifier to generate a score,
• determining by comparing the score to a threshold that the request is a worthless request, and
• responsive to the determining, limiting the worthless request at the network edge so that it does not invoke the authentication or authorization journey or the other resource consuming interaction that establishes the authorized session.