Using repetitive behavioral patterns to detect malware

Abstract

In one embodiment, a device generates one or more time series of characteristics of client-server communications observed in a network for a particular client in the network. The device partitions the one or more time series into sets of time windows based on patterns present in the characteristics of the client-server communications. The device compares the characteristics of the client-server communications from the partitioned time windows to determine measures of behavioral similarity between the compared time windows. The device provides the measures of behavioral similarity between the compared time windows as input to a machine learning-based malware detector. The device causes performance of a mitigation action in the network when the machine learning-based malware detector determines that the particular client in the network is infected with malware.