Cyber Risk Management for Critical Infrastructure: A Risk Analysis Model and Three Case Studies

Area of Science:

• Cyber Security
• Risk Management
• Decision Analysis

Background:

• Effective cyber security management requires budget allocation across various protection options.
• Assessing the benefits and costs of these options is crucial for informed decision-making.
• Risk analyses must account for both historical data and potential future high-consequence events.

Purpose of the Study:

• To present a general probabilistic risk analysis framework for organizational cyber security.
• To demonstrate forward-looking risk analyses using three distinct case studies.
• To support risk management decisions by providing loss distributions with and without countermeasures.

Main Methods:

• Probabilistic risk analysis framework.
• Statistical analysis of historical cyber attack data.
• Bayesian analysis for high-consequence future scenarios.
• Systems analysis for cyber risks in critical infrastructure (e.g., electric grid).
• Sequential decision analysis for cyber security system upgrades.

Main Results:

• A framework for probabilistic cyber security risk assessment.
• Identification of an optimal connectivity level for smart grids.
• Analysis of strategic software upgrade decisions against evolving threats.
• Distributions of potential losses from cyber attacks under various scenarios.
• Quantification of the impact of countermeasures on cyber security risk.

Conclusions:

• The presented framework aids in making informed cyber security risk management decisions.
• Forward-looking analyses are essential for addressing novel and high-impact cyber threats.
• Balancing connectivity and security is critical for systems like the smart grid.
• Proactive strategies for system upgrades are necessary to stay ahead of adversaries.