Why explainability matters in an AI-assisted SOC
An automated recommendation becomes useful only when an analyst can understand and verify its reasoning.
AI can help analysts process security data, but an unexplained recommendation can introduce new risk rather than reduce it.
What explainability means in a SOC
Explainability is the ability to show why a system produced a recommendation, which evidence influenced it and how confident the system is. In security operations, this information must be useful under time pressure.
Trust should be earned, not assumed
An analyst should not accept a model output simply because it is labelled “AI.” Trust should come from consistent performance, visible evidence, clear limitations and the ability to challenge the result.
What an explanation should contain
- The event or behaviour that triggered concern.
- The supporting logs, relationships or contextual signals.
- The reason for the assigned severity or priority.
- Alternative interpretations and uncertainty.
- Recommended actions and the risk of taking them.
Human control remains essential
High-impact actions such as isolating systems, disabling accounts or blocking infrastructure should use appropriate approval and audit controls. The goal is decision support, not unreviewed autonomy.
Calyvex research direction
Our work explores how an assistance layer could combine alert evidence, plain-language reasoning and controlled response guidance while keeping the analyst responsible for sensitive decisions.