  The abundance of cyber-physical components in modern day power grid with
their diverse hardware and software vulnerabilities has made it difficult to
protect them from advanced persistent threats (APTs). An attack graph depicting
the propagation of potential cyber-attack sequences from the initial access
point to the end objective is vital to identify critical weaknesses of any
cyber-physical system. A cyber security personnel can accordingly plan
preventive mitigation measures for the identified weaknesses addressing the
cyber-attack sequences. However, limitations on available cybersecurity budget
restrict the choice of mitigation measures. We address this aspect through our
framework, which solves the following problem: given potential cyber-attack
sequences for a cyber-physical component in the power grid, find the optimal
manner to allocate an available budget to implement necessary preventive
mitigation measures. We formulate the problem as a mixed integer linear program
(MILP) to identify the optimal budget partition and set of mitigation measures
which minimize the vulnerability of cyber-physical components to potential
attack sequences. We assume that the allocation of budget affects the efficacy
of the mitigation measures. We show how altering the budget allocation for
tasks such as asset management, cybersecurity infrastructure improvement,
incident response planning and employee training affects the choice of the
optimal set of preventive mitigation measures and modifies the associated
cybersecurity risk. The proposed framework can be used by cyber policymakers
and system owners to allocate optimal budgets for various tasks required to
improve the overall security of a cyber-physical system.
