  Cybersecurity in building energy management is crucial for protecting
infrastructure, ensuring data integrity, and preventing unauthorized access or
manipulation. This paper investigates the energy efficiency and cybersecurity
of building energy management systems (BMS) against false data injection (FDI)
attacks using proportional-integral (PI) and model predictive control (MPC)
methods. Focusing on a commercial building model with five rooms, vulnerability
of PI-based BMS and nonlinear MPC-based BMS against FDIs on sensors and
actuators is studied. The study aims to assess the effectiveness of these
control strategies in maintaining system performance and lifespan, highlighting
the potential of MPC in enhancing system resilience against cyber threats. Our
case studies demonstrate that even a short term FDIA can cause a 12% reduction
in lifetime of a heat-pump under an MPC controller, and cause a near
thirty-fold overuse of flow valves under a PI controller.
