Location
Huntsville (Ala.)
Start Date
6-7-2017
Presentation Type
Paper
Description
In this paper, we present a Semi-Markov Process (SMP) model of an Industrial Control System (ICS) Kill Chain. We develop the steady state probability equations by first examining the embedded Discrete Time Markov Chain (DTMC) sojourn times. Based on published reports of ICS vulnerabilities and an actual case study of a cyber-attack on a number of power stations on the Ukraine power grid, we derive the parameter values for our SMP model. Using these values, we calculate the steady state probabilities of the model and provide insights on the results particularly on the top two ICS security attributes: availability and integrity.
Recommended Citation
Francia, Guillermo A. III; Li, Tingting; and Feng, Chen, "A Stochastic Model of an Industrial Control System Kill Chain" (2017). National Cyber Summit. 2.
https://louis.uah.edu/cyber-summit/ncs2017/ncs2017papers/2
A Stochastic Model of an Industrial Control System Kill Chain
Huntsville (Ala.)
In this paper, we present a Semi-Markov Process (SMP) model of an Industrial Control System (ICS) Kill Chain. We develop the steady state probability equations by first examining the embedded Discrete Time Markov Chain (DTMC) sojourn times. Based on published reports of ICS vulnerabilities and an actual case study of a cyber-attack on a number of power stations on the Ukraine power grid, we derive the parameter values for our SMP model. Using these values, we calculate the steady state probabilities of the model and provide insights on the results particularly on the top two ICS security attributes: availability and integrity.