Abstract: The invention relates to a system and method that can detect botnets by classifying the communication activities for each client according to destination or based on similarity between the groups of collected traffic. According to certain aspects of the invention, the communication activities for each client can be classified to model network activity by differentiating the protocols of the collected network traffic based on destination and patterning the subgroups for the respective protocols. Those servers that are estimated to be C&C servers can be classified into download and upload, spam servers and command control servers, within a botnet group detected by modeling network activity, i.e. analyzing network-based activity patterns. Also, botnet groups can be detected by way of a group information management function, for generating an activity pattern-based group matrix based on group data, and a mutual similarity analysis, performed on groups suspected to be botnets from the group information.