Cyber Security of Power System Model Dataset: Threats, Impacts, and Defenses

Electric power systems are the Nation’s critical infrastructures that are indispensable for basic functioning the modern society. In the information era, the operation of power systems is increasingly dependent on cyber technologies such as sensing, communication, computing, and data storage. Consequently, cyber security has become a major concern, which if not properly taken care of, may seriously affect the reliability of power delivery.

The power network model dataset, which mathematically describes the electrical characteristics of power systems, serves as the basis for many applications in system operations, such as security assessment, electricity markets, and various control and protection functions. Hence, maintaining accuracy and authenticity of power system model dataset is of ultimate importance.

Recently, there have been extensive discussions on the security of other operational datasets such as measurement datasets, but few efforts have been dedicated to studying the security of network model datasets. As have been clearly revealed by cyber-attack events that already happened in other countries, knowledgeable cyber attackers are capable of intruding into the computer networks of control centers and acquire privileges of internal personnel, which can pose great risks on power system model datasets.

This project aims to initiate investigation on potential threats against information security of power system model datasets, their possible impacts on electricity market operations, as well as effective defense measures. The proposed framework will help understand the vulnerabilities that may be exploited by cyber adversaries, as well as the economic consequences once electricity markets are manipulated via model data falsification.

By developing effective measures against potential threats, the project is expected to provide knowledge on strengthening the cyber-secure operation of power systems, thus benefiting national defense as well as public welfare. The project will also benefit undergraduate and graduate education by introducing cyber-physical perspectives into power system courses.

This project aims to develop a comprehensive framework for analyses of the threats, impacts, and defenses regarding the model dataset security issues. We compare the accessibility, modifiability, and attack motivations of model datasets and measurement datasets, and show that the practicality of cyber-attacks against model datasets cannot be overlooked.

The proposed work encompasses three closely-related research tasks. In Task 1, various patterns of stealthy attacks against network model datasets will be identified and modeled. The possibility of launching coordinated attacks against measurement and model datasets will also be studied.

Task 2 will establish the framework for studying the impacts of model data falsifications on the operation of electricity markets. For quantification of the impacts, a bilevel optimization problem will be formulated, and efficient solution algorithms will be provided. Task 3 will create a systematic security assessment method for identification of all high-impact patterns of model dataset attacks, and develop two measurement-based measures for mitigating the security vulnerabilities in the system planning stage and operation stage, respectively.

A proper validation plan will be carried out for validating both the proposed concepts of model data cyber security, and the proposed methods to analyze, quantify, and mitigate the security vulnerabilities. For the first time, the proposed research will formally establish the conceptual linkage between the information security of model dataset and operational security of power networks, and develop systematic methodologies for assessing the security risks and design mitigation measures.

The proposed work will bring the community’s attention to the information security of power system model datasets, and initiate the advancement of knowledge along this line.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.