Building trustworthy systems: guided state estimation as a feasible approach for interpretation, decision and action based on sensor data

James, J.R.; Mabry, Frank

doi:10.1109/hicss.2004.1265186

Cited by 6 publications

(4 citation statements)

References 6 publications

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“…While the work to date on FVI-NTS provides support for the trusted sharing of systems of files, it is strictly static in form. Operation of many systems generally necessitates the availability of real-time content (James and MCClain 1999, James and Mabry, 2004). Operation of many systems also frequently requires that information being transmitted be shared with only those trusted to receive it.…”

Section: Real-time Extensionsmentioning

confidence: 99%

Flowing Valued Information and Cyber-Physical Situational Awareness

James¹,

Mabry²,

Leger³

et al. 2012

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Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number.

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Section: Real-time Extensionsmentioning

confidence: 99%

Flowing Valued Information and Cyber-Physical Situational Awareness

James¹,

Mabry²,

Leger³

et al. 2012

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“…Many systems in economics (Smith and Foley 2002;Sergeev 2001;Jaynes 1986), environmental sciences (Georgescu-Roegen 1971), molecular biology (Ptashne 1992), power engineering (Hauer et al 2001), sociology (Newman 2000), military command/control/communications/intelligence (C 3 I) (James and Mabry 2004), and transportation systems, exhibit this unanticipated emergent behavior and are thus candidates for membership in the class of systems characterized by complex adaptive behavior with the potential for unanticipated degradation (Watts and Strogatz 1998;Albert et al 2000) in robustness. However, exploiting the emergent behavior of complex systems (Feng et al 2000) by design has been the subject of discussion with respect to building controls (Huberman and Clearwater 1995)and using price as the only signal for electric power systems control (Alvarado 2003).…”

Section: Introductionmentioning

confidence: 99%

Modeling Power Systems as Complex Adaptive Systems

Chassin¹,

Malard²,

Posse³

et al. 2004

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Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.

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“…Among the earliest and most widespread is the application of a control systems approach [55] including hybrid mechanisms [56]. Particularly for behavioral modeling, agent-based systems have also been investigated in detail [57], [58].…”

Section: Related Workmentioning

confidence: 99%

Modeling critical infrastructure requirements

Wolthusen

Proceedings From the Fifth Annual IEEE SMC Information Assurance Workshop, 2004.

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Abstract-Critical infrastructures in industrialized nations form a highly interdependent network that must be protected against both intrinsic defects and active attacks. This requires local as well as joint situational awareness based on current, accurate, and semantically unambiguous data as well as simulations, particularly of attack scenarios, necessitating in turn automated information sharing measures that can span transitive dependency networks.Since the infrastructure elements are frequently civilianowned, providing provable assertions on the precise nature of the data shared and the extent of dissemination is crucial. In this paper, a layered graph-theoretical modeling technique is used; at a lower layer, a standards-based ontological model is described in which resources and interactions are formed into a common exchange format. From this, a simple dependency model amenable to combinatorial optimization and simulation is described, which is then also used as the foundation for the application of the schematic protection model by Sandhu to the information sharing problem.

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Building trustworthy systems: guided state estimation as a feasible approach for interpretation, decision and action based on sensor data

Cited by 6 publications

References 6 publications

Flowing Valued Information and Cyber-Physical Situational Awareness

Flowing Valued Information and Cyber-Physical Situational Awareness

Modeling Power Systems as Complex Adaptive Systems

Modeling critical infrastructure requirements

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