This project aims at accelerating the deployment of security measures for cyber-physical systems (CPSs) by proposing a framework that combines anomaly identification approaches, which emphasizes on the development of decentralized cyber-attack monitoring and diagnostic-like components, with robust control countermeasure to improve reliability and maintain system functionality. One of the main challenges for cyber-physical systems is the security of transmitted data over the communication network.

The wide-area measurement systems technology using Phasor Measurement Units (PMUs) has been regarded as the key to guaranteeing stability, reliability, state estimation, and control of next-generation power systems. However, with the exponentially increasing number of PMUs, and the resulting explosion in data volume, the design and deployment of an efficient wide-area communication and computing infrastructure is evolving as one of the greatest challenges to the power system and IT communities.

Modern electric power grid is a complex, interconnected cyber physical system (CPS) that forms the lifeline of our society. Reliable, secure, and efficient operation of the grid are of paramount importance to national security and economic well-being. Recent trends in security indicate the increasing threat of cyber-based attacks, both in numbers and sophistication, on energy and other critical infrastructure systems of our nation and the world in general.

In this project we consider the development of a Cyber Physical Freight Transportation System for load balancing in multimodal transportation networks. We use on line simulation models to capture the nonlinear and complex dynamical characteristics of the transportation networks. The simulation models generate the states of the network that are used to solve an optimization problem which finds the optimum routes.

Abstract: Securing critical networked cyber-physical systems (NCPSs) such as the power grid or transportation systems has emerged as a major national and global priority. The networked nature of such systems renders them vulnerable to a range of attacks both in cyber and physical domains as corroborated by recent threats such as the Stuxnet virus.