Man vs. Machine: Speed and Scale in Threat Intelligence
By Chris Pace on November 15, 2017
Approaches to the collection and analysis of all kinds of intelligence have traditionally relied heavily on the capabilities of humans to understand references, filter out noise, and ultimately make a decision about any action that needs to be taken.
Today, the overwhelming amount of available data from numerous sources (internal and external) is challenging the capacity of human analysts to effectively identify potentially useful information, including uncovering emerging threats that could be relevant to your business.
Applying machinery to the collection and analysis of huge volumes of threat-related data unburdens human analysts to focus on refining new intelligence, which is considerably less time consuming than gathering, reading, and understanding information from sources of intelligence manually.
We’ve calculated some of the benefits to be gained in speed and scale by automating collection and analysis of threat data using machine learning and AI. You can see the results in the infographic below.
This information is also available to view as a SlideShare presentation.