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Infrastructure Vulnerability Assessment Model (I-VAM).

Barry Charles Ezell1

  • 1Society of Risk Analysis, U.S. Army Capabilities Integration Center, Fort Monroe, VA, USA. Barry.ezell@monroe.army.smil.mil

Risk Analysis : an Official Publication of the Society for Risk Analysis
|July 21, 2007
PubMed
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This study introduces the Infrastructure Vulnerability Assessment Model (I-VAM) to quantify critical infrastructure vulnerability. The model provides a data-driven approach for assessing system susceptibility to threats, aiding decision-making.

Area of Science:

  • Engineering
  • Risk Management
  • Systems Science

Background:

  • Quantifying critical infrastructure vulnerability remains an underexplored area in academic literature.
  • Existing methods often lack a quantitative framework for assessing system susceptibility to diverse threat scenarios.

Purpose of the Study:

  • To present a novel model, the Infrastructure Vulnerability Assessment Model (I-VAM), for quantifying system vulnerability.
  • To define vulnerability as a quantifiable measure of a system's susceptibility to defined threat scenarios.

Main Methods:

  • The Infrastructure Vulnerability Assessment Model (I-VAM) was developed and applied to a clean water system.
  • Subject matter experts (SMEs) were integral for establishing value functions, weights, and assessing protection measures.

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  • Simulation techniques were employed to manage uncertainty, aggregate expert data, and generate a vulnerability (Omega) density function.

    • Main Results:

    • The application of I-VAM to a clean water system demonstrated its practical utility.
    • The model successfully quantified vulnerability, providing a density function that accounts for uncertainty and expert assessments.

    Conclusions:

    • The Infrastructure Vulnerability Assessment Model (I-VAM) offers a valuable quantitative tool for decision-makers, moving beyond qualitative vulnerability assessments.
    • I-VAM's applicability extends to various critical infrastructures, including supervisory control and data acquisition (SCADA) and distributed control systems (DCS).