Katherine Davis
- Courses2
- Reviews2
- School: Texas A&M University
- Campus: College Station
- Department: Engineering
- Email address: Join to see
- Phone: Join to see
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Location:
College Station, TX - Dates at Texas A&M University: March 2018 - May 2019
- Office Hours: Join to see
Biography
Texas A&M University College Station - Engineering
Assistant Professor of Electrical and Computer Engineering at Texas A&M University
Higher Education
Katherine Rogers
Davis
Bryan, Texas
Primary research interests cover the use of data to enhance power systems monitoring and control, including data-enhanced modeling, event identification from data, and making algorithms more robust with respect to bad data. Other areas of interest include power grid cyber security and wide-area visualization.
Experience
University of Illinois at Urbana-Champaign
Research Assistant, Dr. Thomas J. Overbye
Currently working on applying data mining techniques to power grid analysis and on the Trustworthy Cyber Infrastructure for the Power Grid (TCIPG) project; previous research includes power flow control with distributed flexible AC transmission system (D-FACTS) devices.
University of Illinois at Urbana-Champaign
Research Scientist - Information Trust Institute
Research includes data-enhanced power system modeling and analysis, security-oriented cyber-physical techniques for analyzing electrical and cyber infrastructures, and making algorithms more robust with respect to untrustworthy inputs.
University of Illinois at Urbana-Champaign
ECE Adjunct Assistant Professor
Katherine worked at University of Illinois at Urbana-Champaign as a ECE Adjunct Assistant Professor
University of Illinois at Urbana-Champaign
Instructor, ECE 333, Spring 2011
Taught the Green Electric Energy course, formerly called Renewable Energy Systems (ECE 398 RES). The course covered a range of topics important to sustainable energy integration including wind and solar, distributed generation, engineering economics. The other section was taught by Professor Alejandro Dominguez-Garcia.
Texas A&M University
Assistant Professor of Electrical and Computer Engineering
Katherine worked at Texas A&M University as a Assistant Professor of Electrical and Computer Engineering
PowerWorld Corporation
Software Engineer and Senior Consultant
Software development, research, and development for PowerWorld.
PowerWorld Corporation
Intern
Researched transient stability models, developed code for PowerWorld Simulator, assisted with consulting and other projects.
Kaedago
Founder, Kaedago
Kaedago's mission is to improve the cyber security posture of the electric power industry by providing cyber-physical security analysis and situational awareness (CyPSA). Kaedago is a service company supporting the open service software developed on the DOE ARPA-E funded CyPSA project.
Education
The University of Texas at Austin
BS
Electrical Engineering
University of Illinois at Urbana-Champaign
M.S., Ph.D.
Electrical and Computer Engineering
University of Illinois at Urbana-Champaign
Research Assistant, Dr. Thomas J. Overbye
Currently working on applying data mining techniques to power grid analysis and on the Trustworthy Cyber Infrastructure for the Power Grid (TCIPG) project; previous research includes power flow control with distributed flexible AC transmission system (D-FACTS) devices.University of Illinois at Urbana-Champaign
Research Scientist - Information Trust Institute
Research includes data-enhanced power system modeling and analysis, security-oriented cyber-physical techniques for analyzing electrical and cyber infrastructures, and making algorithms more robust with respect to untrustworthy inputs.University of Illinois at Urbana-Champaign
ECE Adjunct Assistant Professor
University of Illinois at Urbana-Champaign
Instructor, ECE 333, Spring 2011
Taught the Green Electric Energy course, formerly called Renewable Energy Systems (ECE 398 RES). The course covered a range of topics important to sustainable energy integration including wind and solar, distributed generation, engineering economics. The other section was taught by Professor Alejandro Dominguez-Garcia.
Publications
Topology Perturbation for Detecting Malicious Data Injection
Proceedings of the 45th Hawaii International Conference on System Sciences (HICSS)
Bad measurement data exists in power systems for a number of reasons. Malicious data injection attacks, which alter the values of measurements without being detected, are one potential cause of bad data and may have serious consequences. A solution for bad data detection in power systems is proposed in this work, particularly designed to detect malicious data attacks. By applying known perturbations to the sys- tem and measuring the changes elsewhere, the ap- proach ’probes’ the system for unexpected responses in terms of measurement values. Using a developed ’keyspace’ approach, the perturbation used is rendered unpredictable to the attacker, making it difficult for the attacker to adapt his attacks. Thus, unexpected measurement values after a probe provide an indication of both bad and malicious data. The proposed approach is analyzed for sample systems using MATLAB.
Topology Perturbation for Detecting Malicious Data Injection
Proceedings of the 45th Hawaii International Conference on System Sciences (HICSS)
Bad measurement data exists in power systems for a number of reasons. Malicious data injection attacks, which alter the values of measurements without being detected, are one potential cause of bad data and may have serious consequences. A solution for bad data detection in power systems is proposed in this work, particularly designed to detect malicious data attacks. By applying known perturbations to the sys- tem and measuring the changes elsewhere, the ap- proach ’probes’ the system for unexpected responses in terms of measurement values. Using a developed ’keyspace’ approach, the perturbation used is rendered unpredictable to the attacker, making it difficult for the attacker to adapt his attacks. Thus, unexpected measurement values after a probe provide an indication of both bad and malicious data. The proposed approach is analyzed for sample systems using MATLAB.
SCPSE: Security-Oriented Cyber-Physical State Estimation for Power Grid Critical Infrastructures
IEEE Transactions on Smart Grid
Preserving the availability and integrity of the power grid critical infrastructures in the face of fast-spreading intrusions requires advances in detection techniques specialized for such large-scale cyber-physical systems. In this paper, we present a security-oriented cyber-physical state estimation (SCPSE) system, which, at each time instant, identifies the compromised set of hosts in the cyber network and the maliciously modified set of measurements obtained from power system sensors. SCPSE fuses uncertain information from different types of distributed sensors, such as power system meters and cyber-side intrusion detectors, to detect the malicious activities within the cyber-physical system. We implemented a working prototype of SCPSE and evaluated it using the IEEE 24-bus benchmark system. The experimental results show that SCPSE significantly improves on the scalability of traditional intrusion detection techniques by using information from both cyber and power sensors. Furthermore, SCPSE was able to detect all the attacks against the control network in our experiments.
Topology Perturbation for Detecting Malicious Data Injection
Proceedings of the 45th Hawaii International Conference on System Sciences (HICSS)
Bad measurement data exists in power systems for a number of reasons. Malicious data injection attacks, which alter the values of measurements without being detected, are one potential cause of bad data and may have serious consequences. A solution for bad data detection in power systems is proposed in this work, particularly designed to detect malicious data attacks. By applying known perturbations to the sys- tem and measuring the changes elsewhere, the ap- proach ’probes’ the system for unexpected responses in terms of measurement values. Using a developed ’keyspace’ approach, the perturbation used is rendered unpredictable to the attacker, making it difficult for the attacker to adapt his attacks. Thus, unexpected measurement values after a probe provide an indication of both bad and malicious data. The proposed approach is analyzed for sample systems using MATLAB.
SCPSE: Security-Oriented Cyber-Physical State Estimation for Power Grid Critical Infrastructures
IEEE Transactions on Smart Grid
Preserving the availability and integrity of the power grid critical infrastructures in the face of fast-spreading intrusions requires advances in detection techniques specialized for such large-scale cyber-physical systems. In this paper, we present a security-oriented cyber-physical state estimation (SCPSE) system, which, at each time instant, identifies the compromised set of hosts in the cyber network and the maliciously modified set of measurements obtained from power system sensors. SCPSE fuses uncertain information from different types of distributed sensors, such as power system meters and cyber-side intrusion detectors, to detect the malicious activities within the cyber-physical system. We implemented a working prototype of SCPSE and evaluated it using the IEEE 24-bus benchmark system. The experimental results show that SCPSE significantly improves on the scalability of traditional intrusion detection techniques by using information from both cyber and power sensors. Furthermore, SCPSE was able to detect all the attacks against the control network in our experiments.
Power flow cyber attacks and perturbation-based defense
IEEE SmartGridComm 2012
In this paper, we present two contributions to false data injection attacks and mitigation in electric power systems. First, we introduce a method of creating unobservable attacks on the AC power flow equations. The attack strategy details how an adversary can launch a stealthy attack to achieve a goal. Then, we introduce a proactive defense strategy that is capable of detecting attacks. The defense strategy introduces known perturbations by deliberately probing the system in a specific, structured manner. We show that the proposed approach, under certain conditions, is able to detect the presence of false data injection attacks, as well the attack locations and information about the manipulated data values
Topology Perturbation for Detecting Malicious Data Injection
Proceedings of the 45th Hawaii International Conference on System Sciences (HICSS)
Bad measurement data exists in power systems for a number of reasons. Malicious data injection attacks, which alter the values of measurements without being detected, are one potential cause of bad data and may have serious consequences. A solution for bad data detection in power systems is proposed in this work, particularly designed to detect malicious data attacks. By applying known perturbations to the sys- tem and measuring the changes elsewhere, the ap- proach ’probes’ the system for unexpected responses in terms of measurement values. Using a developed ’keyspace’ approach, the perturbation used is rendered unpredictable to the attacker, making it difficult for the attacker to adapt his attacks. Thus, unexpected measurement values after a probe provide an indication of both bad and malicious data. The proposed approach is analyzed for sample systems using MATLAB.
SCPSE: Security-Oriented Cyber-Physical State Estimation for Power Grid Critical Infrastructures
IEEE Transactions on Smart Grid
Preserving the availability and integrity of the power grid critical infrastructures in the face of fast-spreading intrusions requires advances in detection techniques specialized for such large-scale cyber-physical systems. In this paper, we present a security-oriented cyber-physical state estimation (SCPSE) system, which, at each time instant, identifies the compromised set of hosts in the cyber network and the maliciously modified set of measurements obtained from power system sensors. SCPSE fuses uncertain information from different types of distributed sensors, such as power system meters and cyber-side intrusion detectors, to detect the malicious activities within the cyber-physical system. We implemented a working prototype of SCPSE and evaluated it using the IEEE 24-bus benchmark system. The experimental results show that SCPSE significantly improves on the scalability of traditional intrusion detection techniques by using information from both cyber and power sensors. Furthermore, SCPSE was able to detect all the attacks against the control network in our experiments.
Power flow cyber attacks and perturbation-based defense
IEEE SmartGridComm 2012
In this paper, we present two contributions to false data injection attacks and mitigation in electric power systems. First, we introduce a method of creating unobservable attacks on the AC power flow equations. The attack strategy details how an adversary can launch a stealthy attack to achieve a goal. Then, we introduce a proactive defense strategy that is capable of detecting attacks. The defense strategy introduces known perturbations by deliberately probing the system in a specific, structured manner. We show that the proposed approach, under certain conditions, is able to detect the presence of false data injection attacks, as well the attack locations and information about the manipulated data values
An Authenticated Control Framework for Distributed Voltage Support on the Smart Grid
IEEE Transactions on Smart Grid
Existing and forthcoming devices at the residential level have the ability to provide reactive power support. Inverters which connect distributed generation such as solar panels and pluggable hybrid electric vehicles (PHEVs) to the grid are an example. Such devices are not currently utilized by the power system. We investigate the integration of these end-user reactive-power-capable devices to provide voltage support to the grid via a secure communications infrastructure. We determine effective locations in the transmission system and show how reactive power resources connected at those buses can be controlled. Buses belong to reactive support groups which parallel the regions of the secure communications architecture that is presented. Ultimately, our goal is to present how the smart grid can enable the utilization of available end-user devices as a resource to mitigate power system problems such as voltage collapse.
Topology Perturbation for Detecting Malicious Data Injection
Proceedings of the 45th Hawaii International Conference on System Sciences (HICSS)
Bad measurement data exists in power systems for a number of reasons. Malicious data injection attacks, which alter the values of measurements without being detected, are one potential cause of bad data and may have serious consequences. A solution for bad data detection in power systems is proposed in this work, particularly designed to detect malicious data attacks. By applying known perturbations to the sys- tem and measuring the changes elsewhere, the ap- proach ’probes’ the system for unexpected responses in terms of measurement values. Using a developed ’keyspace’ approach, the perturbation used is rendered unpredictable to the attacker, making it difficult for the attacker to adapt his attacks. Thus, unexpected measurement values after a probe provide an indication of both bad and malicious data. The proposed approach is analyzed for sample systems using MATLAB.
SCPSE: Security-Oriented Cyber-Physical State Estimation for Power Grid Critical Infrastructures
IEEE Transactions on Smart Grid
Preserving the availability and integrity of the power grid critical infrastructures in the face of fast-spreading intrusions requires advances in detection techniques specialized for such large-scale cyber-physical systems. In this paper, we present a security-oriented cyber-physical state estimation (SCPSE) system, which, at each time instant, identifies the compromised set of hosts in the cyber network and the maliciously modified set of measurements obtained from power system sensors. SCPSE fuses uncertain information from different types of distributed sensors, such as power system meters and cyber-side intrusion detectors, to detect the malicious activities within the cyber-physical system. We implemented a working prototype of SCPSE and evaluated it using the IEEE 24-bus benchmark system. The experimental results show that SCPSE significantly improves on the scalability of traditional intrusion detection techniques by using information from both cyber and power sensors. Furthermore, SCPSE was able to detect all the attacks against the control network in our experiments.
Power flow cyber attacks and perturbation-based defense
IEEE SmartGridComm 2012
In this paper, we present two contributions to false data injection attacks and mitigation in electric power systems. First, we introduce a method of creating unobservable attacks on the AC power flow equations. The attack strategy details how an adversary can launch a stealthy attack to achieve a goal. Then, we introduce a proactive defense strategy that is capable of detecting attacks. The defense strategy introduces known perturbations by deliberately probing the system in a specific, structured manner. We show that the proposed approach, under certain conditions, is able to detect the presence of false data injection attacks, as well the attack locations and information about the manipulated data values
An Authenticated Control Framework for Distributed Voltage Support on the Smart Grid
IEEE Transactions on Smart Grid
Existing and forthcoming devices at the residential level have the ability to provide reactive power support. Inverters which connect distributed generation such as solar panels and pluggable hybrid electric vehicles (PHEVs) to the grid are an example. Such devices are not currently utilized by the power system. We investigate the integration of these end-user reactive-power-capable devices to provide voltage support to the grid via a secure communications infrastructure. We determine effective locations in the transmission system and show how reactive power resources connected at those buses can be controlled. Buses belong to reactive support groups which parallel the regions of the secure communications architecture that is presented. Ultimately, our goal is to present how the smart grid can enable the utilization of available end-user devices as a resource to mitigate power system problems such as voltage collapse.
A Sensitivity Approach to Detection of Local Market Power Potential
IEEE Transactions on Power Systems
Market power gives certain market participants the ability to manipulate the market to their advantage when their product is not substitutable by competitors. Identification of generators which have the potential for market power either individually or within a small group is performed using sensitivity information from the linear programming optimal power flow (LP OPF). The impact of network constraints on admissible price perturbations are used to group generators that have the potential to exhibit local market power. Specific price perturbation vectors are found that highlight a constraint-induced locational advantage for these suppliers. In practice, this is most commonly observed in “load pockets,” for which ISO policies mitigate market power.
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