Abstract :

With The Increasing Frequency And Sophistication Of Cyber-attacks, Organizations Are Seeking Effective Risk Mitigation Strategies Such As Cyber Insurance. However, Designing Optimal Cyber Insurance Policies Is Challenging Due To Information Asymmetry, Interdependent Security Risks, And Varying Levels Of Organizational Preparedness. This Project Proposes A Framework That Incorporates Prescreening Mechanisms And Security Interdependence To Design Efficient Cyber Insurance Policies. The System Evaluates Organizations Based On Their Cybersecurity Posture Before Issuing Insurance Policies. Machine Learning Techniques Can Be Used To Assess Risk Levels Based On Historical Data, Vulnerabilities, And Security Practices. The Concept Of Security Interdependence Highlights How The Security Of One Organization Can Impact Others Within A Network. By Considering These Factors, Insurers Can Design Fair Premium Pricing And Reduce Moral Hazard. The Proposed Approach Improves Risk Assessment, Enhances Security Awareness, And Promotes Better Cybersecurity Practices Among Insured Entities. It Provides A Scalable And Intelligent Solution For Designing Adaptive Cyber Insurance Policies.

Published:

08-4-2026

Issue:

Vol. 26 No. 4 (2026)

Page Nos:

1948-1953

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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