Modeling and Detection of Evolving Threats Using Random Finite Set Statistics
Zachariah Sutton, Peter Willett, Yaakov Bar‐Shalom · 2018
Many threats in the form of human actions (terrorist attacks, military actions, etc.) can be modeled by someone with relevant expert knowledge. A model would be a hypothesis or guess as to how a threat would develop and what kind of observable evidence it would produce along the way. We present a method of stochastically modeling these types of processes using Hidden Markov Models (HMMs). We then present a detection scheme using a Bernoulli Filter - an increasingly popular application of random finite set statistics