Power-SPRINT investigates the cybersecurity risks posed by the growing integration of IoT-enabled smart-home appliances on power grid operations.
Existing research on power grid security mainly focuses on utility-side cyber attacks and the associated SCADA system security. In contrast, the cyber threats posed by end-user appliances on power grid operations have received little attention. Securing the grid against these demand-side threats is very challenging since IoT-enabled load devices are numerous and often poorly engineered from a security point of view.
By analysing network traffic from IoT-smart-home appliances, Power-SPRINT will perform threat analysis and identify the devices that are most likely to be targeted by the attacker.
Using a control theoretic-approach, Power-SPRINT will investigate the impact of compromising a large number of smart-home appliances (in a Botnet-type attack) on power grid operations (e.g., on frequency/voltage control loops) and shed light on how the grid’s resilience can be enhanced by the optimal deployment of security reinforcements and back-up devices to mitigate these attacks.
Power-SPRINT will investigate how to detect such attacks if they occur using the power grid’s physical signals (e.g., load consumption, voltages, frequency, data gathered by existing power grid sensors) and deep learning along with implementing a privacy-preserving mechanism that can be deployed at the edge devices.
SCADA system security: SCADA security is the practice of protecting supervisory control and data acquisition (SCADA) networks, a common framework of control systems used in industrial operations.
Attack Impact Analysis:
[J1] S. Lakshminarayana, J. Ospina, and C. Konstantinou, “Load-Altering Attacks Against Power Grids under COVID-19 Low-Inertia Conditions”, IEEE Open Access Journal of Power and Energy, 2022, vol.9, pp. 226-240, 2022.
[J2] S. Lakshminarayana, S. Adhikari, and C. Maple, “Analysis of IoT-Enabled Load-Altering Attacks Using the Theory of Second-Order Systems,” IEEE Trans. on Smart Grid, 2021, vol. 12, no. 5, pp. 4415-4425, Sept. 2021.
[J3] S. Lakshminarayana, S. Sthapit, and C. Maple, “Data-Driven Detection and Identification of IoT-Enabled Load-Altering Attacks in Power Grids”, IET Smart Grid Journal, 5(3), 203 – 218, 2022.
The Power-SPRINT poster displayed at the PETRAS Academic Conference | Networking Research Showcase on 16 June 2022: