Validating Machine Learning and Security Analytics

PRODUCT BRIEFS

Validating Machine Learning and Security Analytics

It is well understood that data is the key for proper development and maturity of any analytics or machine learning tool. Meaningful domain-specific data, events, or logs help to establish the baseline behavior of a domain, and eventually helps in understanding the tool’s ability to detect anomalies that diverge from the baseline behavior. A universal truth of analytics and machine learning is that the larger the volume of baseline data a model receives, the better it gets.

This document describes the challenges of validating using a diverse set of traffic patterns that replicate behaviors of different types of domains and vertical markets, and how Ixia's BreakingPoint will help you overcome them.