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This study introduces a new framework to understand systemic cyber risk, modeling cascading failures to estimate economic damage from cyber incidents and inform cyber insurance policies.

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Area of Science:

  • Economics
  • Computer Science
  • Risk Management

Background:

  • Recent years have seen major cyber attacks, increasing focus on cyber risk management and insurance.
  • Understanding the full extent of cyber risk, particularly systemic risk from interdependent systems, remains a challenge.
  • Existing research has focused on direct costs of cyber attacks, neglecting systemic impacts.

Purpose of the Study:

  • To develop a theoretical framework for systemic cyber risk.
  • To construct a quantitative model for estimating economic damage from cascading cyber failures.
  • To apply input-output analysis to the cyber domain for aggregate loss estimation.

Main Methods:

  • Developed a theoretical framework defining systemic cyber risk through cascading, common cause, or independent failures.
  • Constructed a quantitative model of cascading failures to estimate economic damage.
  • Adapted sector-level input-output analysis for the cyber domain to estimate aggregate losses.

Main Results:

  • The study provides a novel framework for understanding systemic cyber risk.
  • A quantitative model was developed to estimate economic losses from cyber incidents.
  • Input-output analysis was successfully extended to the cyber domain for risk assessment.

Conclusions:

  • The developed model aids in estimating aggregate losses from firm-level cyber incidents.
  • Findings have implications for the cyber insurance market and policy development.
  • The input-output analysis approach is applicable to various risk analysis domains beyond cyber security.