Abstract:In environments where adversaries engage in active surveillance and covert communication, defenders face the dual challenge of when to deploy steganography and whether it yields operational benefit. We present a novel game-theoretic model of steganographic operations that captures strategic interactions between a defender and an adversary through calibrated monetary primitives and nonlinear utility mappings. We derive mixed-strategy equilibria that drive conditional and unconditional success rates for hiding and detection, and introduce a time-varying adversarial advantage metric that quantifies when an attacker's incentives temporarily exceed the defender's detection capacity. By linking this advantage to a new currency-unit risk measure, we extend the classical risk formula into a decision-aware, monetised framework. A Monte Carlo simulation pipeline embeds payload shifts, detector learning, and scenario uncertainty to deliver distributions of success probabilities and expected losses rather than a static snapshot. Empirical calibration using breach cost statistics, regulatory fine caps, and expert elicitations supports strategic prescriptions for steganographic deployment, detector investment, and governance trade-offs. Our results provide actionable insight into when steganography strengthens organisational resilience, and when it may yield marginal or negative value.
From: Obinna Omego Ph.D. [view email]
[v1]
Mon, 23 Dec 2024 20:02:52 UTC (2,378 KB)
[v2]
Fri, 3 Jan 2025 07:27:30 UTC (2,378 KB)
[v3]
Sat, 8 Aug 2026 00:53:21 UTC (706 KB)
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