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Machine Learning in Security: Deep Learning Based DGA Detection with a Pre-trained Model | Splunk

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The SMLS team enables Splunk customers to find obscure and buried threats in large amounts of data through expert analytics. This work is part of a set of machine learning detections built by a specialized team of security-focused data scientists working in concert with Splunk’s threat research teams to help Splunk customers sift through vast amounts of data to identify and alert users of suspicious content. Based on recent threat research, a large percentage of organizations experienced DNS attacks. There are various mechanisms to establish Command and Control infrastructure, and one of them is Dynamic Resolution which uses Domain Generation Algorithms (DGA). As malware families evolve, it will only get more challenging for defenders to detect, block and track these threats in real-time. The SMLS team has developed a detection in Enterprise Security Content Update (ESCU) app which predicts DGA generated domains using a pre-trained Deep Learning (DL) model. The model is deployed using

Machine Learning in Security: Deep Learning Based DGA Detection with a Pre-trained Model | Splunk Machine Learning in Security: Deep Learning Based DGA Detection with a Pre-trained Model Security December 06, 2022 Namratha Sreekanta The SMLS team enables Splunk customers to find obscure and buried threats in large amounts of data through expert analytics. This work is part of a set of machine learning detections built by a specialized team of security-focused data scientists working in concert with Splunk’s threat research teams to help Splunk customers sift through vast amounts of data to ide

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