How segmented is my network?
This simple metric could revolutionize how companies assess cybersecurity risk...
Deep Dive
Researchers have developed a novel method to quantify network segmentation—a critical security practice—using just 97 randomly sampled node pairs to achieve a 95% confidence interval with ±0.1 margin of error. The technique models networks as graphs and estimates global edge density, providing a practical metric previously lacking for security practitioners. Validated through Monte Carlo simulations, it enables accurate assessment independent of total network size for applications like zero-trust evaluation and merger integration.
Why It Matters
Provides security teams with a practical, scalable tool to measure and improve network defenses against lateral movement attacks.