16 citations · 49 across the 5 of their papers we have counts for
6 papers
Learning Without Adversarial Training: A Physics-Informed Neural Network for Secure Power System State Estimation under False Data Injection Attacks
Solon Falas, Markos Asprou, Charalambos Konstantinou +1
Power System State Estimation (PSSE) converts geographically distributed measurements into the voltage magnitudes and phase angles needed for grid monitoring and control. Learned e…
Physics-Informed Neural Networks for Accelerating Power System State Estimation
Solon Falas, Markos Asprou, Charalambos Konstantinou +1
State estimation is the cornerstone of the power system control center since it provides the operating condition of the system in consecutive time intervals. This work investigates…
Towards a Secure and Resilient All-Renewable Energy Grid for Smart Cities
Charalambos Konstantinou
The concept of smart cities is driven by the need to enhance citizens' quality of life. It is estimated that 70% of the world population will live in urban areas by 2050. The elect…
Physics-Informed Neural Networks for Securing Water Distribution Systems
Solon Falas, Charalambos Konstantinou, Maria K. Michael
Physics-informed neural networks (PINNs) is an emerging category of neural networks which can be trained to solve supervised learning tasks while taking into consideration given la…
Multi-Model Resilient Observer under False Data Injection Attacks
Olugbenga Moses Anubi, Charalambos Konstantinou, Carlos A. Wong +1
In this paper, we present the concept of boosting the resiliency of optimization-based observers for cyber-physical systems (CPS) using auxiliary sources of information. Due to the…
A Modular End-to-End Framework for Secure Firmware Updates on Embedded Systems
Solon Falas, Charalambos Konstantinou, Maria K. Michael
Firmware refers to device read-only resident code which includes microcode and macro-instruction -level routines. For Internet-of-Things (IoT) devices without an operating system,…