Stream-wise detection of surreptitious traffic over DNS

The Domain Name System (DNS) belongs to crucial services in a computer network. Because of its importance, DNS is usually allowed in security policies. That opens a way to break policies and to transfer data from/to restricted area due to misusage of a DNS infrastructure. This paper is focused on a detection of communication tunnels and other anomalies in a DNS traffic. The proposed detection module is designed to process huge volume of data and to detect anomalies at near real-time. It is based on combination of statistical analysis of several observed features including application layer information. Our aim is a stream-wise processing of huge volume of DNS data from backbone networks. To achieve these objectives with minimal resource consumption, the detection module uses efficient extended data structures. The performance evaluation has shown that the detector is able to process approximately 511 thousand DNS flow records per second. In addition, according to experiments, a tunnel that lasts over 30 seconds can be detected in a minute. During the on-line testing on a real traffic from production network, the module signalized on average over 60 confirmed alerts including DNS tunnels per day.