Presented at
BSidesSF 2015,
April 19, 2015, noon
(60 minutes)
Analyzing traffic patterns for trends can be a rich source of information for investigating potential malicious domains. This talk will be an examination of spikes in DNS queries and how they can be used to find potentially new threats. Malicious domains that appear as spiked domains usually belong to Domain Generation Algorithm (DGA) or exploit kit families. However, not all domains that spike are necessarily malicious. One challenge is sifting through the large data set and extracting the potentially harmful spikes. To accomplish this goal we rely on unsupervised learning methods such as clustering to help us explore and eventually classify the data.
Presenters:
-
Thomas Mathew
- Security Research - Data - Cisco - OpenDNS
Thomas Mathew is a Security Researcher at OpenDNS (now part of Cisco) where he works on implementing pattern recognition algorithms to classify malware and botnets. His main interest lies in using various time series techniques on network sensor data to identify malicious threats. Previously, Thomas was a researcher at UC Santa Cruz, the US Naval Postgraduate School, and as a Product and Test Engineer at handsfree streaming video camera company Looxcie, Inc. He presented at ISOI APT, BruCon, FloCon 2016 and Kaspersky SAS.
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