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As cyber-socio-physical and infrastructure systems are increasingly relying on data and integrating an ever-growing range of disparate, sometimes unconventional, and possibly untrusted data sources, there is a growing need to consider the problem of estimation in the presence of strategic and/or self-interested sensors. This class of problems, called "strategic information transmission" (SIT), differs from classical fault-tolerant estimation since the sensors are not merely failing or malfunctioning, but are actively trying to mislead the estimator for their own benefit. Such strategic behavior could happen through at least two mechanisms, sensor hijacking and willful misreporting, both of which have been observed in practice. One particularly stark and fundamental difference between strategic and faulty sensors is that a population of strategic sensors does not necessarily result in an erroneous estimate. In fact, depending on how each sensor expects others to act, it is even possible for the resulting estimator to converge to a correct value of the estimated quantity of interest faster than in the absence of any strategic intent! In other words, strategic information transmission appears to have the potential for being both a boon and a curse for the systems it targets. The central question for the engineer and system designer, then, is: "where is the demarcation line?"
This project is concerned with a comprehensive study of SIT in the specific contexts of false data attacks in controlled systems, willful misreporting in participatory sensing applications, and adversarial machine learning. It builds on and extends existing models from the so-called "cheap talk" literature in Economics, where strategic information transmission has been considered before, although under widely different assumptions than in the context of security of cyber-physical systems. The novelty, pertinence, and intellectual merit of this project, lie in (1) its formulation of new models that more closely account for the specificity of strategic information transmission in the three applications of interest than existing frameworks, (2) its combined use of information theoretic and game theoretic tools to analyze these models and, (3) the use of behavioral economics experiments to help characterize, and straddle, the boundary between detrimental and beneficial strategic information transmission in practice.
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TWC SBE: Small: From Threat to Boon: Understanding and Controlling Strategic Information Transmission in Cyber-Socio-Physical Systems