How Machine Learning Can Be Applied in Network Traffic Analysis

Presented by

Alissa Torres, SANS Analyst & Abhishek Sharma, Data Scientist

About this talk

In the new security landscape, blind spots in network traffic can not solely be monitored by security tools designed for simple, on-premise traditional architectures. Modern organizations are implementing a combination of machine learning, advanced analytics, and rule-based detection to detect suspicious activities on enterprise networks. In this presentation we'll go through three uses cases where machine learning can be applied in network traffic analysis: *Detecting Credential Misuse using Lateral Movement *Identify Credential Stuffing Attack using Behavioral Modeling *C2 (Command & Control) Detection using Relationship Based Modeling

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