Calculating Known and Unknown Risk: The Math Behind the Cyber Exposure Score
Learn how Tenable’s data science team prioritizes business-critical risks across the full cyberattack surface
Few security teams have the ability to thoroughly assess — let alone protect against — every vulnerability on every asset across their enterprise network. The name of the game in cybersecurity is prioritization — where to apply your limited resources to reduce the greatest amount of risk across your most critical assets.
The Cyber Exposure Score, a critical component of Tenable Lumin, provides an objective measurement of cyber risk for every asset across any digital platform, even for assets hidden from authenticated security scans. The score uses advanced machine learning, paired with one of the industry’s largest threat data lakes, to illuminate which exposures across your attack surface are most vulnerable to a business-impacting attack.
In this technical whitepaper, you’ll learn:
- Why predictive technologies are necessary to understand risk across your full attack surface
- How the Cyber Exposure Score is calculated and each underlying quantity is derived
- Which user controls and metrics within Tenable Lumin can help security teams align their resources with business-critical vulnerabilities