*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
Title: Cyber Threat Propagation Modeling in Cyber-Physical Systems
Committee:
Dr. Vincent Mooney, ECE, Chair, Advisor
Dr. Santiago Grijalva, ECE, Co-Advisor
Dr. Lee Lerner, ECE
Dr. Daniel Molzahn, ECE
Dr. Brandon Eames, Sandia
Dr. Chelsea White, ISyE
Abstract: Cyber-physical attacks on critical industrial control systems are on the rise. These attacks may target individual field cyber-components or the communications network. In the electricity grid, cyber-physical attacks can modify or affect data or software applications such as state estimator demand response, frequency regulation and voltage control. As a result, a cyber-physical attack on the grid can trigger operators to take inappropriate actions which can lead to instability in the power grid and cascading failures with significant consequences. Hence, to ensure a secure and reliable power grid, it is imperative to study the different ways in which the cyber-physical power grid can be compromised and then develop techniques and mechanisms to detect, evaluate and mitigate the propagation and impact of a potential cyber-physical attack. The objective of the research is to model the propagation of cyber-attack in cyber-physical systems. We use the electricity grid as the main exemplar for our work. We utilize our novel hybrid attack model, which combines both Markov and PLADD model. In our hybrid attack model, an attack is split into preparation and execution stages. Additionally, the hybrid attack model is extended to assess risk in a cyber-physical system. The risk assessment allows cyber-physical system operators to quantitatively determine which area of the cyber-physical system is the most vulnerable and requires a security update.