A Metric-Driven IT Risk Scoring Framework: Incorporating Contextual and Organizational Factors

Risk analysis is a critical process for organizations seeking to manage their cybersecurity posture effectively. However, traditional risk analysis frameworks, such as the Common Vulnerability Scoring System (CVSS), primarily evaluate technical impacts without incorporating organizational context and dynamic risk factors. This paper presents a metric-based risk analysis framework designed to provide a more adaptable and context-aware risk-scoring framework. The proposed model enables risk owners to define customized threat scenarios and dynamically adjust metric weights based on organizational needs. Unlike traditional approaches, our method integrates contextual parameters to improve the accuracy and relevance of risk calculations. Experimental evaluations demonstrate that the proposed framework enhances risk prioritization and provides more actionable insights for decision-makers. This study contributes to the field by addressing the limitations of existing risk analysis models and offering a systematic approach for cybersecurity risk management.

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Publication Details

Published
2025-08-07
DOI
https://doi.org/10.1109/acdsa65407.2025.11166074
Primary Topic
Big Data and Business Intelligence
Type
article
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article

A Metric-Driven IT Risk Scoring Framework: Incorporating Contextual and Organizational Factors

Barış Çeliktaş, Nezih Mahmut Unal
Big Data and Business Intelligence
article

A Metric-Driven IT Risk Scoring Framework: Incorporating Contextual and Organizational Factors

Barış Çeliktaş, Nezih Mahmut Unal
article en

Abstract

Risk analysis is a critical process for organizations seeking to manage their cybersecurity posture effectively. However, traditional risk analysis frameworks, such as the Common Vulnerability Scoring System (CVSS), primarily evaluate technical impacts without incorporating organizational context and dynamic risk factors. This paper presents a metric-based risk analysis framework designed to provide a more adaptable and context-aware risk-scoring framework. The proposed model enables risk owners to define customized threat scenarios and dynamically adjust metric weights based on organizational needs. Unlike traditional approaches, our method integrates contextual parameters to improve the accuracy and relevance of risk calculations. Experimental evaluations demonstrate that the proposed framework enhances risk prioritization and provides more actionable insights for decision-makers. This study contributes to the field by addressing the limitations of existing risk analysis models and offering a systematic approach for cybersecurity risk management.

Işık University (TR)
Openalex Percentile: Top 58%
Big Data and Business Intelligence
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A Metric-Driven IT Risk Scoring Framework: Incorporating Contextual and Organizational Factors — Barış Çeliktaş, Nezih Mahmut Unal · (2025) | TGRS Research Map | TGRS