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Context Assumptions for Threat Assessment Systems

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Context-Enhanced Information Fusion

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

Decision support systems enable users to quickly assess data, but they require significant resources to develop and are often relevant to limited domains. This chapter identifies the implicit assumptions that require contextual analysis for decision support systems to be effective for providing a relevant threat assessment. The impacts of the design and user assumptions are related to intelligence errors and intelligence failures that come from a misrepresentation of context. The intent of this chapter is twofold. The first is to enable system users to characterize trust using the decision support system by establishing the context of the decision. The second is to show technology designers how their design decisions impact system integration and usability. We organize the contextual information for threat analysis by categorizing six assumptions: (1) specific problem, (2) acquirable data, (3) use of context, (4) reproducible analysis, (5) actionable intelligence, and (6) quantifiable decision making. The chapter concludes with a quantitative example of context assessment for threat analysis.

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Acknowledgments

This work is partly supported by the Air Force Office of Scientific Research (AFOSR) under the Dynamic Data Driven Application Systems program and the Air Force Research Lab.

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Authors and Affiliations

  1. Raytheon, Chantilly, VA, USA

    Steven A. Israel

  2. Air Force Research Lab, Rome, NY, USA

    Erik Blasch

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  1. Steven A. Israel
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  2. Erik Blasch
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Correspondence to Erik Blasch .

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Editors and Affiliations

  1. Department Mathematics and Computer Science, University of Udine, Udine, Italy

    Lauro Snidaro

  2. University Carlos III, Department of Computer Science and Engg. University Carlos III, Colmenarejo, Spain

    Jesús García

  3. Center Multisource Info. Fusion & Dept, Univ. at Buffalo, of Industrial and Engg Center Multisource Info. Fusion & Dept, Buffalo, New York, USA

    James Llinas

  4. Information Directorate, Air Force Research Laboratory Information Directorate, Rome, New York, USA

    Erik Blasch

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Israel, S.A., Blasch, E. (2016). Context Assumptions for Threat Assessment Systems. In: Snidaro, L., García, J., Llinas, J., Blasch, E. (eds) Context-Enhanced Information Fusion. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-319-28971-7_5

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  • DOI: https://doi.org/10.1007/978-3-319-28971-7_5

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