An Adversarial Risk Analysis Framework for Cybersecurity.

Area of Science:

• Cybersecurity and Information Assurance
• Risk Management and Decision Science

Background:

• Cyber risk analysis is vital for organizations to identify threats, prioritize asset defense, and select security controls.
• Existing risk analysis methods, often using risk matrices, have limitations leading to inefficient resource allocation.
• Current approaches may not adequately address both intentional and unintentional cyber threats or integrate diverse security measures like insurance.

Purpose of the Study:

• To propose a comprehensive framework for cybersecurity risk analysis.
• To incorporate both intentional and non-intentional threats within the risk analysis process.
• To explore the integration of insurance as a component of an organization's security portfolio.

Main Methods:

• Development of a novel, comprehensive framework for cybersecurity risk analysis.
• Inclusion of a wide spectrum of threats, encompassing both malicious (intentional) and accidental (non-intentional) sources.
• Integration of insurance as a risk mitigation strategy within the proposed framework.

Main Results:

• The proposed framework offers a more holistic approach to cybersecurity risk assessment.
• It provides a structured method for considering diverse threat types and mitigation options.
• A simplified case study demonstrates the framework's applicability and potential for complex scenarios.

Conclusions:

• The developed framework enhances cybersecurity risk analysis by addressing limitations of traditional methods.
• It supports more informed decisions regarding security controls and resource allocation, including insurance.
• The framework serves as a valuable template for organizations seeking robust cybersecurity risk management.