Terror and Intelligence: Modeling The Operation of an Intelligence Agency Through Statistically-Informed Monte Carlo Terror Queues

Abstract

Terrorist actors exploit the sensitivities of democratic governments to effect socio-political change or secure ideological objectives using deadly and oft-indiscriminate violence against civilian targets. Domestic counter-terrorism agencies, including the British MI5, the American FBI, and the Israeli Shin-Bet, seek to foresee, detect, and foil terror plots through their intelligence apparatus. This thesis proposes a discrete event simulation able to replicate patterns of terror plot arrivals and anti-terror strategies undertaken by the intelligence agency. Chapter 1 gives a brief socio-historical overview of terrorism as a political modus operandi. We take a closer look at the Israeli case where we examine specific counter-terrorism operations and introduces basic queuing models. Chapter 2 corrects a model simplification in the Kaplan Terror Queue (presented in the award-winning paper [7]) and proposes an algorithm to solve it. In Chapter 3, this thesis showcases a discrete event simulation which extends the Kaplan Terror Queue and offers insight into the metrics of the transient states of ‘Terror Queues’ with any probability distribution to model realistic scenarios of terror arrival, success rates, detection, and interdiction changing over time. Chapter 4 extends this model to ‘informed’ terror queues which take advantage of historical data to model agency strategy. This thesis showcases that the operation of an intelligence agency can be modeled through an informed discrete event simulation.