Pontus: A Linguistics-Based DGA Detection System
Dingkui Yan, Huilin Zhang, Yipeng Wang, Tianning Zang, Xiaolin Xu, Yuwei Zeng · 2019
Many botmasters use domain generation algorithms (DGA) to generate a host of malicious algorithmically- generated domains (mAGDs) and then choose several mAGDs for actual command and control (C2) communication. The botmasters use different seeds (e.g., timestamp) to generate different mAGDs, which makes the communication mechanism resilient to blacklisting. Thus the botmasters can hide C2 channels very well. If we can quickly detect these mAGDs from DNS traffic, we will effectively block the communication. In this paper, we propose a novel system, called Pontus, to detect mAGDs from DNS traffic. Pontus extract features exclusively from the individual domain names. We compare Pontus with the state-of-the-art system and find that Pontus improves the precision by at least 4.7%.