Human factor complicates cyber and pandemic risk modelling

Understanding and predicting human behaviour is a major challenge in creating effective cyber and pandemic risk models.

Research from analytics platform CyberCube has found the potential for political decisions and the public’s response to affect the duration and severity of both types of events is critical to successful modelling.

Whether viruses are digital or biological the research says modellers in both areas can learn from each other. The research report is entitled: “Viruses, contagion and tail-risk: Modelling cyber risk in the age of pandemics.”

Oli Brew (pictured), head of client success at CyberCube, said: “It’s clear that lessons can be learnt and applied to cyber risk modelling from understanding how pandemic models have evolved. As the COVID-19 pandemic continues, even though there are differences between computer and human viruses, parallels are emerging in the modelling, the methodologies and the data challenges.”

He added: “There is real value in learning from interdisciplinary teams in how to balance the needs of accuracy and precision in developing models to meet the market needs. At a minimum, the need for a creative, but reality-based imagination to represent forward-looking risks is critical.”

Nita Madhav, CEO of epidemic research specialist Metabiota, added: “There are parallels with modelling the global spread of a disease and how cyber systems are connected - both are network issues. The impact of mitigation risk and early action can potentially make a difference. Furthermore, you can be asymptomatic with COVID-19; similarly, you may not know if a cyber intruder has already infiltrated your network.”

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