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A Model for Threat Assessment

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Fusion Methodologies in Crisis Management

Abstract

A concept for characterizing, predicting and recognizing threat situations is developed. The goal is to establish a systematic approach to automation of some of these functions. Approaches are discussed to address the fundamental problems of (a) sparse and ambiguous indicators of potential or actualized threat activity buried in massive background data; and (b) uncertainty in threat capabilities, intent and opportunities.

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Notes

  1. 1.

    We argue in Steinberg (2015a) and Steinberg (2015b) that it makes more sense to distinguish inference problems on the basis of type of entity state variables rather than by type of entity: a given entity can be addressed at more than one level. For example, a vehicle can be the “target” of a level 1 fusion process if level 1 states (e.g., its location, velocity, size, weight, type, identity, or activity) are being estimated. The same vehicle can be the “target” of a level 2 process if it is considered as a complex or a structure, such that level 2 states (e.g., the relationships among its components or its subassemblies) are being estimated. It could also be the subject of a level 3 process if it is considered as a dynamic process, such that level 3 states (e.g., its course of action and outcome states) are being estimated. It could even be the subject of a level 4 process if it is considered as the system performing the estimation and level 4 states (e.g., the operating conditions and performance relative to users’ objectives) are being estimated.

  2. 2.

    McMichael, Jarrad, and colleagues at CSIRO (Commonwealth Scientific and Industrial Research Organisation) developed methods for efficient storage, search, and manipulation of such dynamic belief networks, employing what they call grammatical methods for representing and reasoning about situations and scenarios (McMichael and Jarrad 2005).

  3. 3.

    Means of threat assessment in the absence of complete, high-confidence models of such factors are addressed in Sect. 15.6.

  4. 4.

    Section 15.6 discusses categories of inference problems in which predictive statistical models of entities and activities of concern are not available.

  5. 5.

    Technology Readiness Levels as defined by the US Department of Defense are (TRL1) basic principles observed and reported; (TRL2) technology concept and/or application formulated; (TRL3) analytical and experimental critical function and or characteristic proof-of-concept; (TRL4) component and/or breadboard validation in laboratory environment; (TRL5) component and/or breadboard validation in relevant environment; (TRL6) system/subsystem model or prototype demonstration in relevant environment; (TRL7) system prototype demonstration in operational environment; (TRL8) actual system completed and qualified; and (TRL9) actual system proven in successful mission operations (paraphrased from Nolte et al. (2003)).

  6. 6.

    Such inferences are examples of Category 3 reasoning as discussed in Sect. 15.7.

  7. 7.

    JPL defined Concept Maturity Levels (CMLs) as (CML1) Cocktail Napkin (i.e., rudimentary understanding of the concept); (CML2) Initial Feasibility; (CML3) Trade Space; (CML4) Point Design; (CML5) Concept Baseline; (CML6) Initial Design; and (CML7) Integrated Baseline (Wessen et al. 2010).

  8. 8.

    Interpersonal interactions and influences add to complexity and model issues. There are well-known issues of emergent group behavior that are arguably not predictable by constructive modeling.

  9. 9.

    Methods for evaluating and compensating for source data quality are discussed in (Snidaro et al. 2015, Steinberg et al. 2014).

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Authors and Affiliations

  1. Independent Consultant, Lake Ridge, VA, USA

    Alan N. Steinberg

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  1. Alan N. Steinberg
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Correspondence to Alan N. Steinberg .

Editor information

Editors and Affiliations

  1. State University of New York at Buffalo, Buffalo, New York, USA

    Galina Rogova

  2. State University of New Yorkat Buffalo, Buffalo, New York, USA

    Peter Scott

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Steinberg, A.N. (2016). A Model for Threat Assessment. In: Rogova, G., Scott, P. (eds) Fusion Methodologies in Crisis Management. Springer, Cham. https://doi.org/10.1007/978-3-319-22527-2_15

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  • DOI: https://doi.org/10.1007/978-3-319-22527-2_15

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22526-5

  • Online ISBN: 978-3-319-22527-2

  • eBook Packages: EngineeringEngineering (R0)

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