Making the Case for Cybersecurity
Assurance cases that focus on risk modeling were introduced in Nikolai Mansourov, Djenana Campara’ s work [ 9 ]. Several technical approaches to assurance cases have emerged across different communities as described in: Mazen Mohamed, et. al. [ 11 ], Sarker, et. al. [ 12 ], and Ardebili, et. al. [ 13 ].
Formal methods have contributed rigorous verification techniques( e. g. theorem proving, model checking) to assure correctness in critical systems, but these approaches remain difficult to scale and integrate with broader lifecycle assurance, see Kulik, et. al. [ 14 ]. System-level assurance frameworks similarly provide structured methodologies for evaluating system security but often lack the adaptability to handle modern threats and continuously evolving systems, see Akmir Shulka, et. al. [ 10 ].
From a regulatory perspective, ISO / SAE 21434 [ 4 ] requires structured cybersecurity assurance cases across the automotive lifecycle. This marks a broader trend: organizations must increasingly demonstrate— not just declare— the adequacy of their defenses using structured, justifiable arguments. Though ISO / SAE 21434 is domain-specific, its principles are widely applicable.
8 USE CASES AND APPLICATIONS OF THE FRAMEWORK
A major application of this framework lies in transforming cybersecurity into a continuous process of test, evaluation, and assurance. Traditional approaches to cybersecurity— whether focused on vulnerability scans, checklist compliance, or point-in-time risk assessments— are increasingly misaligned with the pace and complexity of modern system delivery.
8.1 ENABLING CONTINUOUS TEST AND EVALUATION
In agile and DevSecOps environments, systems are developed, updated, and deployed on rapid timelines. Yet test and evaluation( T & E)— including cybersecurity assessments— remains one of the slowest and most manual phases of the lifecycle. Risk-centric DevSecOps changes this by integrating automated, model-based reasoning into every pipeline stage.
System models, risk claims, threat intelligence, and runtime telemetry are all structured into a living cybersecurity argument, where each subclaim( e. g.“ this control mitigates this attack on this node”) is traceable to test artifacts and verification outcomes. When a change occurs— such as a software update or a newly disclosed vulnerability— the argument identifies which claims are affected and automatically triggers the relevant tests. This enables incremental re-evaluation rather than full regression testing, reducing cost and time while maintaining assurance.
In this way, T & E becomes an ongoing, explainable, and mission-aligned process. Test results don’ t just pass or fail requirements— they resolve formal claims in a continuously evolving security assurance case.
54 May 2025