Malware infection prediction and prevention

Abstract

A malware infection prediction method predicts a likelihood that a client device is to be infected with in a period of time based on state and behavior telemetry data. A malware infection prediction system receives telemetry data associated with use (i.e. behavior data) and configuration (i.e. state data) of a client device. By using a trained model, the system predicts a likelihood of the client device becoming infected within a given time frame. Based on the predicted likelihood, the system generates recommendations including recommended actions for reducing the likelihood of the client device becoming infected. The system then generates notifications including the recommendations and sends the notifications to the client device or to an administrative account associated with the client device.