Metrics Towards Measuring Cyber Agility
This work addresses the need for quantitative metrics to understand cyber agility in cybersecurity, though it is incremental as it builds on existing static metrics.
The paper tackles the lack of systematic metrics for quantifying cyber agility, which characterizes the effectiveness of evolutionary strategies in cyber attacks and defenses, by proposing the first generic framework to transform static security metrics into dynamic ones, validated through case studies on real-world datasets.
In cyberspace, evolutionary strategies are commonly used by both attackers and defenders. For example, an attacker's strategy often changes over the course of time, as new vulnerabilities are discovered and/or mitigated. Similarly, a defender's strategy changes over time. These changes may or may not be in direct response to a change in the opponent's strategy. In any case, it is important to have a set of quantitative metrics to characterize and understand the effectiveness of attackers' and defenders' evolutionary strategies, which reflect their {\em cyber agility}. Despite its clear importance, few systematic metrics have been developed to quantify the cyber agility of attackers and defenders. In this paper, we propose the first metric framework for measuring cyber agility in terms of the effectiveness of the dynamic evolution of cyber attacks and defenses. The proposed framework is generic and applicable to transform any relevant, quantitative, and/or conventional static security metrics (e.g., false positives and false negatives) into dynamic metrics to capture dynamics of system behaviors. In order to validate the usefulness of the proposed framework, we conduct case studies on measuring the evolution of cyber attacks and defenses using two real-world datasets. We discuss the limitations of the current work and identify future research directions.