Training trusted users of an enterprise network for phishing attacks on a per-user basis

Abstract

A user behavior training model is generated, using machine learning, from tracking a plurality of trusted users for interactions with respect to a plurality of monitored phishing e-mails. When a unique phishing attack is detected from an incoming email, a new campaign is initiated. A unique phishing attack email that is modified by the user behavior model is generated for each user. In particular, a first test phishing e-mail for a first user is modified based on interactions tracked for the first user and a second test phishing e-mail for a second user is modified based on interactions tracked for the second user. Based on responses to the plurality of test phishing emails, a plurality of custom training videos is generated. A first training video is modified based on a response from the first user and a second training video is modified based on a response from the second user.

CPC Classifications