Adaptive Risk Scoring in Unified Risk-Based Vulnerability Management (URBVM): Balancing Threat Context with Asset Value

Authors

santosh kumar kande

Abstract

As organizations deal with a rising number of cybersecurity threats, effective vulnerability management has become more and more important. Risk and business effect are frequently not aligned by traditional vulnerability prioritizing techniques. In Unified Risk-Based Vulnerability Management (URBVM), Adaptive Risk Scoring (ARS) offers a dynamic method by striking a balance between asset value and real-time threat context to guarantee optimal remediation. This study examines the creation and application of an ARS model, revealing how well it works to lower exposure to cyber risk while enhancing operational effectiveness. Combining machine learning-driven risk scores with contextualized threat knowledge adds uniqueness and allows for environmental adaptation.

Keywords

Adaptive Risk Scoring, URBVM, Threat Context, Asset Value, Vulnerability Management, Machine Learning, Cybersecurity Risk

Adaptive Risk Scoring in Unified Risk-Based Vulnerability Management (URBVM): Balancing Threat Context with Asset Value. santosh kumar kande. 2024. IJIRCT, Volume 10, Issue 1. Pages 1-3. https://www.ijirct.org/viewPaper.php?paperId=2412081