  In this paper, we examine the factors that influence the success of false
data injection (FDI) attacks in the context of both cyber and physical styles
of reinforcement. Many works consider the FDI attack in the context of the
ability to change a measurement in a static system only. However, successful
attacks will require first intrusion into a system followed by construction of
an attack vector that can bypass bad data detection (BDD). In this way, we
develop a full service framework for FDI risk assessment. The framework
considers both the costs of system intrusion via a weighted graph assessment in
combination with a physical, line overload-based vulnerability assessment. We
present our simulations on a IEEE 14-bus system with an overlain RTU network to
model the true risk of intrusion. The cyber model considers multiple methods of
entry for the FDI attack including meter intrusion, RTU intrusion and combined
style attacks. Post-intrusion our physical reinforcement model analyses the
required level of topology divergence to protect against a branch overload from
an optimised attack vector.
