Prioritization of Information Assurance (IA) Technology in a Resource Constrained Environment

Abstract

Classical risk analysis is a static process that does not account for rapid evolutionary or generational changes in technology and technological solutions. This thesis defines a process that expands classical risk analysis to increase visualization of the security environment of an information system. It provides a comparative analysis of system attributes and encourages focused communications between decision-makers and information systems technicians. Personal interviews with domain experts from four organizations were used to construct a baseline model. Face validity of the model was determined during sessions with the domain experts. The model was calibrated to two specific scenarios using a pair of surveys to set link values and establish data for the initial nodes. A verification phase compared rough results from the model with expert opinion. The model evaluated, prioritized and graphically illustrated shortfalls within two information systems based on the relative importance of specific criteria established by the domain experts. It facilitated the extraction of implicit or tacit knowledge from the domain experts that would not emerge during a classical risk analysis.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2001
Accession Number
ADA457789

Entities

People

  • Carl P. Brodhun Iii

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Cyber
  • Energy and Power Technologies
  • Engineered Resilient Systems

DTIC Thesaurus Topics

  • Application Software
  • Business Administration
  • Computer Network Security
  • Computer Networks
  • Computers
  • Cybersecurity
  • Delphi Method
  • Information Assurance
  • Information Operations
  • Information Security
  • Information Systems
  • Network Protocols
  • Organizational Structure
  • Risk
  • Risk Analysis
  • Systems Engineering
  • Transport Protocols

Readers

  • Artificial Intelligence
  • Computational Modeling and Simulation
  • Cybersecurity.