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Anomaly and Specification Based Cognitive Approach for Mission-Level Detection and Response

(Extended Abstract)
  • Paul Rubel
  • Partha Pal
  • Michael Atighetchi
  • D. Paul Benjamin
  • Franklin Webber
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5230)

Abstract

In 2005 a survivable system we built was subjected to red-team evaluation. Analyzing, interpreting, and responding to the defense mechanism reports took a room of developers. In May 2008 we took part in another red-team exercise. During this exercise an autonomous reasoning engine took the place of the room of developers. Our reasoning engine uses anomaly and specification-based approaches to autonomously decide if system and mission availability is in jeopardy, and take necessary corrective actions. This extended abstract presents a brief summary of the reasoning capability we developed: how it categorizes the data into an internal representation and how it uses deductive and coherence based reasoning to decide whether a response is warranted.

Keywords

Deductive Reasoning Adapter Logic Reasoning Engine Reasoning Capability Defense Mechanism Report 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Freuder, E., Wallace, R.: Partial constraint satisfaction. Artificial Intelligence, special issue on constraint-based reasoning 58(1-3), 21–70 (1992)MathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Paul Rubel
    • 1
  • Partha Pal
    • 1
  • Michael Atighetchi
    • 1
  • D. Paul Benjamin
    • 2
  • Franklin Webber
    • 1
  1. 1.BBN TechnologiesCambridgeUSA
  2. 2.Pace UniversityNew YorkUSA

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