According to a new report from cyber analytics provider CyberCube, the evolution of natural catastrophe modelling since Hurricane Andrew in 1992 can act as a template for cyber modellers, but only up to a point.
The company believes cyber’s lack of historical data and rapidly evolving nature means modellers need to be selective in the lessons they learn from nat cat models. Beyond that, cyber modellers need to develop their own solutions.
In addition to a lack of historical data and the rapid frequency with which cyber events are changing, cyber-attacks involve ‘active adversaries’ in the form of criminals or terrorists.
The report notes that cyber modellers do not have the time or ability to ‘observe, learn and adapt from past data and models’.
One key challenge for cyber modellers identified in the report is the need to improve accuracy in this sector in which the past provides limited guidance as to future activity.
“There’s a well-known phrase in statistical circles that while all models are wrong, some are useful,” said Oliver Brew, CyberCube’s Head of Client Services.
“Models like CyberCube’s do not have a predictive line of sight to outcomes but they do aid decision-making, capital planning and a wide range of other factors.
“For a long time, our sector thought that by studying the way in which nat cat models developed, we could find answers to build better cyber models. What this report shows is that those parallels will only take us so far.
“The challenge for businesses like CyberCube is to use the tools at our disposal to learn from the past and make informed decisions about the future. The good news is that cyber models are improving rapidly with more useful data sources and faster cloud-hosted processing power.”
