Predicting Threat Capability in Control Systems to Enhance Cybersecurity Risk Determination

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" Predicting Threat Capability in Control Systems to Enhance Cybersecurity Risk Determination "
Price, Peyton T. Marufuzzaman, Mohammad

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	1106607
Doc. No	:	TLpq2406591673
Main Entry	:	Marufuzzaman, Mohammad
	:	Price, Peyton T.
Title & Author	:	Predicting Threat Capability in Control Systems to Enhance Cybersecurity Risk Determination\ Price, Peyton T.Marufuzzaman, Mohammad
College	:	Mississippi State University
Date	:	2020
student score	:	2020
Degree	:	Ph.D.
Page No	:	67
Abstract	:	Risk assessment is a critical aspect of all businesses, and leaders are tasked with lim- iting risk to the lowest reasonable level within their systems. Industrial Control Systems (ICS) operate in a different cybersecurity risk environment than business systems due to the possibility of second and third-order effects when an attack occurs. We present a process for predicting when an adversary gains the ability to attack an industrial control system. We assist leaders in understanding how attackers are targeting ICS by providing visualiza- tions and percentages that can be applied to updating infrastructure or shifting personnel responsibilities to counter the threat. This new process seeks to integrate defenders and threat intelligence providers, allowing defenders to proactively defend their networks prior to devastating attacks. We apply the process by observing it under randomness with con- straints and through a case study of the 2015 attack on the Ukrainian power grid. We find that this process answers the question of what an attacker can do, provides the ability for the defender to possess an updated understanding of the threat’s capability, and can both increase and decrease the probability that an attacker has a capability against a control system. This process will allow leaders to provide strategic vision to the businesses and systems that they manage.
Subject	:	Information science
	:	Operations research