Methods and systems for malware detection

Abstract

Methods, system, and media for detecting malware are disclosed. A network may be monitored to collect samples of the network traffic. Feature vectors may be extracted from the sampled network traffic. One or more machine learning models may be applied to the feature vectors to produce a score indicative of the presence of a particular type of malware. One or more scores obtained by applying the machine learning models may be fused by another machine learning model into a resulting score. A threshold value may be calculated to accompany a score indicating the likelihood that the traffic sample indicates the presence of malware and the likely effectiveness of planned remediation effort. An alert may be generated from the score and the threshold when the threshold is acceded.