Beyond Resilience: Antifragility in Critical Infrastructure Cybersecurity

• URL: http://arxiv.org/abs/2607.29550v1
• Date: Fri, 31 Jul 2026 15:42:18 GMT
• Title: Beyond Resilience: Antifragility in Critical Infrastructure Cybersecurity
• Abstract summary: This paper develops a Theory of Antifragility (AFT) for critical infrastructure cybersecurity.<n> OTadja sectors show significantly higher shares of disruptive mixed events than comparison sectors.<n>Findings establish two prerequisites for future antifragility testing: differentiated burden and adaptive observability.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Critical infrastructure cybersecurity increasingly requires frameworks that move beyond recovery toward bounded improvement under disruption, yet empirically grounded theories for operational technology remain limited. This paper develops a Theory of Antifragility (AFT) for critical infrastructure (CI) cybersecurity, anchored in a five-state Resilient System Model and a bounded mathematical definition based on Jensen gain and post-disruption gain. A two-layer empirical design pairs a CI-relevant subset of the CISSM Cyber Events Database with the HAI hardware-in-the-loop industrial control dataset and tests three confirmatory hypotheses and one exploratory proposition. OT-adjacent sectors show significantly higher shares of disruptive or mixed events than comparison sectors (65.3 percent versus 46.8 percent, p less than 0.001), together with a greater concentration of physical-attack and data-attack subtypes. In HAI, attack-labeled observations were 7.43 times more likely than normal observations to exceed the 95th percentile of baseline deviation (p less than 0.001). Across successive attack windows, mean process-state deviation declined significantly (Spearman rho = -0.688, p = 0.007), indicating measurable response variation rather than proof of adaptive gain. Together, the findings establish two prerequisites for future antifragility testing: differentiated fragility burden and process-level perturbation observability.

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