New Mathematical Models for Forecasting Cyber Attacks

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Session by Charlene Deaver-Vazquez of

Title: New Mathematical Models for Forecasting Cyber Attacks

Probability theory gives us the ability to quantify risk and forecast events in a predictable way. These methods have been used in epidemiology, seismology, finance, and even space and nuclear safety analysis. Today a new algorithm gives us the ability to model the phenomenon of one event increasing the likelihood of more such events, referred to as “self-excitement”. We witness this when a restaurant seats the first customers in the front window because they intuitively know it increases the likelihood of more customers. We also see it when a tweet goes viral. Applying these models to the cyber realm gives us an unprecedented opportunity to peer into the future with the goals of improving our current decisions and developing mitigations before the risk is upon us.

Charlene Deaver-Vazquez

Charlene has worked in the IT field for over 30 years, and as a Subject Matter Expert for over 12. She created the Probabilistic Risk Model for Cyber Framework (P-RMOD4Cyber). She authored the book “Ensure Your Business Success with Risk-Informed Decisions: the easy way to quantify risk”. For the last several years she has been providing analytical services for the Nuclear Regulatory Commission.

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