Hybrid detection and tracking of fast-flux botnet on domain name system traffic

Fast-flux is a Domain Name System (DNS) technique used by botnets to organise compromised hosts into a high-availability, load-balancing network that is similar to Content Delivery Networks (CDNs). Fast-Flux Service Networks (FFSNs) are usually used as proxies of phishing websites and malwares, and hide upstream servers that host actual content. In this paper, by analysing recursive DNS traffic, we develop a fast-flux domain detection method which combines both real-time detection and long-term monitoring. Experimental results demonstrate that our solution can achieve significantly higher detection accuracy values than previous flux-score based algorithms, and is lightweight in terms of resource consumption. We evaluate the performance of the proposed fast-flux detection and tracking solution during a 180-day period of deployment on our university's DNS servers. Based on the tracking results, we successfully identify the changes in the distribution of FFSN and their roles in recent Internet attacks.