Research Recap: How To Automate Malware Campaign Detection With Telemetry Peak Analyzer
Contributors: Jason Zhang, Stefano Ortolani, Giovanni Vigna
Cyber security threats have been growing significantly in both volume and sophistication over the past decade with no sign of a slowdown. Naturally, this has also been accompanied by an increased collection of threat telemetry data, ranging from detonation timelines to IDS/IPS detections. Telemetry data, typically represented by enriched time series, often contains underlying peak signals which in turn correspond to a few informative events: occurrences of malware campaigns, heavily used malware delivery vectors, commonly affected verticals, and even anomalies possibly revealing the presence of false positives. While all this information clearly holds tremendous value, mining these data sets can be expensive and complex. As a result, organizations often find it challenging to gain further insights of the underlying threat landscape even though they have access to the data.
Recently at VirusBulletin Threat Intelligence Practitioners’ Summit (TIPs) 2021, we presented our latest research aiming to tackle the challenges discussed above: Telemetry Peak Analyzer is a statistical approach to detect malware campaigns as they happen by relying on telemetry data in an efficient and scalable manner.
Read on to get the key insights of the presentation. We’ll provide an overview of the characteristics Continue reading
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