This thesis focuses on securing critical infrastructures such as chemical plants, manufacturing units, and power generating plants against attacks that disrupt the information flow from one component to another. Such systems are controlled by an Industrial Control System (ICS) that includes controllers communicating with each other, and with physical sensors and actuators, using a communications network.

Traditional security models partition the security universe into two worlds, secure and insecure, but in the real world the partitions often overlap and information is leaked even through the physical observation which makes it much harder to analyze a Cyber physical system (CPS). To overcome these, this thesis focus on the Multiple Security Domain Nondeducibility (MSDND) model to identify the vulnerable points of attack on the system that hide critical information as in the STUXNET virus rather than theft of information. It is shown how MSDND analysis, conducted on a realistic multi-stage water treatment testbed, is useful in enhancing the security of a water treatment plant. Based on the MSDND analysis, this thesis offers a thorough documentation on the vulnerable points of attack, invariants used for removing the vulnerabilities, and suggested design decisions that help in developing invariants.