Exploiting inherent physical structure of the CPS domains can lead to economically viable and efficient novel algorithms for providing performance, control, synchronization and an alternate approach to CPS security that does not rely solely on cryptography. In each of these systems, regardless of the current state of the network, in the presence of disturbances or adversarial inputs, there is a need to bring the system to desired state for performance and control of the network. This project presents one such novel approach by observing that the CPS applications including smartgrid, coordinating robotics, formation flights in UAV, and synchronization of biological systems including brain networks all exhibit a special physical structure, namely submodularity, with respect to the set of control actions. Submodularity is a diminishing returns property that enables the development of efficient algorithms with provable optimality guarantees and in many cases distributed versions that are locally implementable, and hence scalable. While it has been widely used in the machine learning and discrete optimization communities, the use of submodularity in the context of CPS is a fertile research area. This project initially applies submodularity in the context of smart grid and show how it can lead to greater system stability and attack resilience. By defining suitable metrics that capture the submodular structures underlying the physical dynamics, the researchers develop algorithms that eliminate the time-consuming and computationally expensive verification of control actions through simulation. The fundamental properties of synchronization, convergence, robustness, and attack-resilience considered in this effort have crosscutting applications to multiple CPS domains, which will benefit from the submodular approach that we will research and develop.