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1 Security and Vulnerability of Cyber-Ph... > 1.2 Definitions for Security and Vul... - Pg. 7

CHAPTER 1 Security and Vulnerability of Cyber-Physical Infrastructure Networks 7 estimation or inference techniques, and related network partitioning methods, are very germane to the study of dynamical network security. Specif- ically, they can provide explicit graph-theoretic characterizations of security measures and associ- ated estimators, and hence permit design of net- work dynamics that are secure. Here, we overview these promising tools for network estimation and estimator characterization and summarize their application in characterizing network security (Section 1.3.1). Next, we overview new ideas on perturbation and control of network dynamics that are needed for characterization of network vulnerability (Section 1.3.2). Like estimation, per- turbation/control of dynamical systems and even networks has been very extensively studied. How- ever, to develop useful characterizations of the notions of vulnerability that we have proposed, we critically need methods that relate dynamics and control to the network's topological structure; we Our work is largely motivated by growing concerns about threats and uncertainties impact- ing the physical world of large-scale cyber- physical infrastructures. More formally, we are primarily concerned with infrastructure or phys- ical networks, whose primary purpose is the completion of a physical task rather than only information transfer. Classically, the state dynam- ics of such physical-infrastructure networks have been viewed as being governed by the underlying laws of interaction (e.g., physics or population dynamics rules), which yield differential equa- tion models defined on a graph for the dynamics. Historically, natural disturbances (e.g., weather phenomena) and unexpected operational failures have been considered the primary causes of fail- ure for such networks, and hence the robust- ness or vulnerability of the networks to such natural adversaries has been fairly thoroughly studied. As these infrastructure networks are