CPS: Medium: Foundations of Secure Cyber Physical Systems
Lead PI:
Suhas Diggavi
Co-Pi:
Abstract
Cyber-physical systems regulating critical infrastructures, such as electrical grids and water networks, are increasingly geographically distributed, necessitating communication between remote sensors, actuators and controllers. The combination of networked computational and physical subsystems leads to new security vulnerabilities that adversaries can exploit with devastating consequences. A synchronized attack on the interdependent network components and physical plants can create complex and new security vulnerabilities that cannot be addressed by securing the constituent systems individually. This project takes a holistic view by utilizing the properties of physical systems to design new secure protocols and architectures for cyber-physical systems (CPS) through a unified conceptual framework, which uses models for the physical system and the communication/computation network to define precise attack models and vulnerabilities. These mathematical models are used to design algorithms and protocols with provable operational security guarantees, thus enabling the design of more trustworthy architectures and components. The algorithms, protocols, and architectures are validated on CPS testbeds targeting building, automobile, and smart-grid applications. Additionally, the research is being integrated into the curriculum via the creation of novel coursework combining the underlying control, information theory, cryptography, and embedded system concepts. By improving the protection of critical cyber-physical infrastructure against emerging threats, this research is expected to provide direct socio-economic benefits, ranging from individual organizations to a national scale. The inter-disciplinary team of this project will integrate teaching and curriculum development with the research, contributing to the training of a new generation of engineers well versed in the design of trustworthy cyber-physical systems.
Suhas Diggavi
Performance Period: 09/01/2011 - 08/31/2016
Institution: University of California-Los Angeles
Sponsor: National Science Foundation
Award Number: 1136174
Project URL