Data Dominance: Turning Large Data Into A Cyber Advantage

Overview
Over the past few years, there has been a major focus on the development of tools that can detect, sense, and capture data across the IT spectrum, from devices to networks to identities.  This has resulted in massive stores of data. This data, however, is not being leveraged in a manner that significantly changes the cyber landscape. Similarly, a core component to Zero Trust Architecture is the protection of data assets, which are growing at an incredible rate.

This project will address how to gain greater power from the data collected and how to better protect the data in the overall environment. 

Project Information
The purpose of this project is to begin developing approaches that maximize the power of the data captured and on ways to tag/categorize data by the capture and creation tools currently in place.

Project Approach
The "Data Dominance: Turning Large Data Into A Cyber Advantage" topic is extremely complex, so this project will be done in phases, with this first phase addressing several key but straightforward topics.  Those topics are:

• What are the best architectures for the storage, movement and consumption of cyber data that enable near real time response to attacks?
• How can current tools be leveraged in the tagging and categorization of data?
• How do these two topic support a Zero Trust Architecture implementation?
• How can artificial intelligence make this data actionable, and what are the guidelines based on recent directives?

Deliverables
The result of this project will be a paper that outlines the group's findings and recommendations, specifically defining an architecture methodology and a data tagging/categorization approach. The paper should be detailed enough to enable a potential demonstration of the approach in the next phase.

Membership 
The Data Dominance project is looking for volunteers from a broad cross-section of members, ranging from operational experience in how data is captured, managed, and reviewed to technical understanding in data management and architecture.  Additionally, members with experience in federal data policy also have a strong role in the project.