This chapter covers
- The role of advanced cybersecurity metrics
- AI and predictive analytics in cybersecurity
- Using advanced metrics
- Data-driven approaches for proactive cybersecurity management
The cybersecurity landscape has evolved rapidly with advancements in technology. One of the most effective recent changes is the availability of generative and agentic AI. These technologies offer more sophisticated approaches to cybersecurity. Traditional metrics remain a cornerstone for measuring information security programs. Still, we must balance the cat-and-mouse game of defender (blue team) versus attacker (red team). Advanced cybersecurity metrics provide a richer, more nuanced insight into what is taking place within your organization. The purpose is to help define what is happening, understanding the underlying reasons, determining the key actors, and anticipating future developments.
A key difference between traditional and advanced metrics is the latter’s ability to reflect on current and past events, but also to predict and forecast future events, such as threats and vulnerabilities. In this chapter, we use artificial intelligence and predictive analytics to offer these prescriptive insights. This data-driven foresight is where advanced metrics offer a strategic advantage.