Intercepting worthless requests at the network edge using machine learning

Abstract

The technology screens malicious and probing requests to establish an authorized session, collectively worthless requests, directed to a protected application, by using an identity gateway (IG) positioned as a network edge component on a network. Screening occurs before starting an authentication or authorization journey or other resource consuming interaction with a protected application. The screening setup involves provisioning a ML classifier at an edge server accessible by the IG. When the request to establish an authorized session is received by the IG, screening involves the ML classifier accepting features and outputting a score predicting whether the request is worthless. The IG compares the score to a threshold. Based on the score, the IG may determine to limit the worthless request at the network edge so that the request does not invoke the authorization journey or perform the resource consuming interaction.