Urgency in Cybersecurity Risk Management: Toward a Solid Theory

Mann, Z. Á.

Forschungsartikel in Sammelband (Konferenz) | Peer reviewed

Zusammenfassung

IT systems are exposed to a rapidly changing landscape of serious security risks. Given the limited resources available to an organization, it is becoming more and more important to properly prioritize security risks, so that the organization can focus its efforts on the most critical risks. Traditionally, risks are assessed in terms of two aspects: occurrence probability and caused damage. However, for real-time risk prioritization, a third aspect is also of critical importance: urgency. Urgency stems from time-related considerations, such as the time needed by adversaries to exploit a vulnerability or the time needed for system administrators to put a countermeasure in place. These time-related considerations are orthogonal to the traditional aspects of occurrence probability and caused damage, and are largely ignored by existing risk management approaches. This paper proposes a way for introducing the notion of urgency into risk assessment. Our aim is to devise an intuitive approach for assessing risks, taking urgency into account, based on a solid theoretical underpinning. We establish a mathematical model using probability theory, and derive formulas for time-aware risk assessment in different settings.

Details zur Publikation

Herausgeber*innenIEEE
Buchtitel 2024 IEEE 37th Computer Security Foundations Symposium (CSF)
Seitenbereich651-664
VerlagWiley-IEEE Computer Society Press
ErscheinungsortEnschede
StatusVeröffentlicht
Veröffentlichungsjahr2024
Sprache, in der die Publikation verfasst istEnglisch
Konferenz2024 IEEE 37th Computer Security Foundations Symposium (CSF), Enschede, Niederlande (Königreich der)
DOI10.1109/CSF61375.2024.00051
StichwörterComputational modeling; Organizations; Machine learning; Solids; Mathematical models; Real-time systems; Risk management; cybersecurity; IT security; security risks; risk assessment; risk prioritization; risk mitigation; probabilistic models

Autor*innen der Universität Münster

Mann, Zoltan Adam
Professur für Praktische Informatik (Prof. Mann)