On the Comparative Analysis of Trends in Cybersecurity Risk Assessment, Governance, and Compliance Frameworks

Document Type

Conference Proceeding

Source of Publication

2024 International Jordanian Cybersecurity Conference (IJCC)

Publication Date

12-18-2024

Abstract

This paper proposes an evaluation framework and systematic review of recent trends for cybersecurity risk assessment governance and compliance. The proposed framework incorporates several metrics for assessing model effectiveness. The findings highlight research opportunities in scalable privacy-preservation techniques, cross-domain validation, and standardized performance benchmarks. Federated learning models achieve the highest privacy rating while maintaining strong performance in precision and automation, suggesting distributed learning architectures as a promising direction for future governance, risk, and compliance framework development. Based on these findings, we recommend for future frameworks supported by regulatory considerations that balance privacy, performance, and ethical requirements, and combine quantum-resistant architectures with privacypreserving features.

ISBN

979-8-3315-1846-2

Publisher

IEEE

Volume

00

First Page

136

Last Page

142

Disciplines

Computer Sciences

Keywords

Cybersecurity, Risk Assessment, Governance, Compliance, Privacy Preservation

Indexed in Scopus

no

Open Access

no

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