Cyber security usually favors action: when an abnormality is detected, systems react visibly (block, alert, rotate) even when evidence is weak. However, work on abstention and selective prediction shows that deferring commitment can be rational under uncertainty, trading coverage for lower expected risk. At the same time, operational realities such as alert overload and adaptive adversaries imply that visible defensive reactions can backfire by increasing analyst burden and providing feedback that supports attacker probing and policy inference. This paper presents quantum-inspired abstention as a first-class security action. Using a quantum decision-theoretic lens, I model defensive commitment as a “measurement” that collapses an uncertain belief state into an externally observable response, and I define abstention as deliberate non-commitment that suppresses or delays measurement when uncertainty and leakage risk are high. I integrate these ideas into a conceptual framework and a minimal loss decomposition separating security loss, operational cost, and leakage-driven adversarial learning. I illustrate the approach through SOC triage and network intrusion detection scenarios, and I provide a lightweight simulation that instantiates the trade-offs among these losses—without requiring quantum hardware.
Michael Nguyen Phuc (Mon,) studied this question.