Measuring Quality of Information Assurance (QoIA)

Abstract

Current information assurance techniques do not allow us to state quantitatively how assured our systems and networks are. As a result, (a) security and assurance measures can only be designed and built into information systems in an ad hoc fashion, (b) it is difficult to characterize the capabilities of security measures, and (c) information systems cannot deliver quality of information assurance (QolA) guarantees. This seedling project had two objectives: (1) to explore an economics theoretic framework for measuring assurance and (2) to explore a theory of QolA management. For each objective, the study defines the problem space, offers some potentially feasible solutions, and creates a technology development roadmap for a 5 to 7 year time horizon. The key idea is to use incentive-based, economic models of attacker intent, objectives and strategies (AIOS) to measure a system's overall assurance capacity. As a result, a preliminary framework for AlOS modeling and inference is developed along with an approach which uses AlOS inferences to measure a system's assurance capacity. Two real-world assurance measuring case studies were conducted. Finally, a preliminary framework for measuring QolA and delivering QolA services in mission critical database systems is proposed.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2003
Accession Number
ADA419205

Entities

People

  • Peng Liu

Organizations

  • Pennsylvania State University

Tags

Communities of Interest

  • Cyber

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Case Studies
  • Commerce
  • Computational Complexity
  • Computer Programs
  • Computers
  • Databases
  • Detection
  • Economic Models
  • Economics
  • Information Assurance
  • Information Science
  • Information Systems
  • Intrusion Detection
  • Intrusion Detectors
  • Security
  • Statistics

Fields of Study

  • Computer science

Readers

  • Cybersecurity.
  • Distributed Systems and Data Platform Development
  • Instructional Design and Training Evaluation.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • Space