Information Flow Quantification Framework for Cyber Physical System with Constrained Resources

In Cyber Physical Systems (CPSs), traditional security mechanisms such as cryptography and access control are not enough to ensure the security of the system. In a CPS, security is violated through complex interactions between the cyber and physical worlds, and, most insidiously, unintended information leakage through observable physical actions. Information flow analysis, which aims at controlling the way information flows among different entities, is better suited for CPSs. Information theory is widely used to quantify information leakage received by a program that produces a public output. Quantifying information leakage in CPSs can, however, be challenging due to implicit information flow between the cyber portion, the physical portion, and the outside world. This paper focuses on statistical methods to quantify information leakage in CPSs, especially, CPSs that allocate constrained resources. With aggregated physical observations, unintended information about the constrained resource might be leaked. The framework proposed is based on the advice tape concept of algorithmically quantifying information leakage and statistical analysis. An electric smart grid has been used as an example to develop confidence intervals of information leakage within a real CPS. The impact of this work is that it can be used as in algorithmic design to allocate electric power to nodes while maximizing the uncertainly of the information flow to an attacker.